Electronic communication and collaboration services[1] such as Outlook.com, Skype, Gmail, Slack, and OneDrive carry valuable private and confidential communications that need protection. But these same services also provide a means for attackers to steal information or seize control of users’ computers for nefarious purposes, via viruses, worms, spam, phishing attacks, and other forms of malware.
Preventing the theft of user information and the dissemination of malware is a core feature of electronic communication and collaboration services. This requires significant processing of users’ communications and data both in-transit and after delivery. This processing can and should be done without compromising the user’s privacy or the confidentiality of their communications[2].
Message processing data flow:
To protect against malware distributed via electronic communications and collaboration systems such as email servers[3], the content follows a conceptually simple flow.
Starting with “A” the message is received by the recipient’s email service. The message’s envelope, as well as the message contents and any attachments, are passed on to the anti-malware portion of the email service (“B”) which determines whether or not the message is malware. Based on what the anti-malware service determines, the message is delivered to the user as appropriate (“C”). Some messages are determined to be malware with near certainty and are never delivered to the user. Instead they are deleted as quickly as possible[4]. Some messages are likely to be spam, however the service is not always certain. So the message is delivered to the user’s mailbox but into their spam/junk-mail folder. The remaining valid messages are delivered to the user’s inbox. The service can never determine with absolute certainty whether or not a message is malicious; it is always a probabilistic assessment. If the service is wrong either way; i.e. the user is exposed to malware or the user indicates that a message originally thought to be spam is not, the message may be added to a database of messages (“E”) used to train the next version of the anti-malware logic (“F”), thus permitting the system to “learn” over time and become more effective.
Clearly this entire process entails considerable processing of the messages. The types of processing are diverse and done in two key phases: message processing (“A” – “D”) and model building (“E” – “F”).
Anti-malware is particularly important for in-transit messages because attacks most typically enter the service through communications being transmitted. It is, however, also performed against already received and processed messages. As new attacks are identified – usually after the attack has been launched and some infected content has evaded the filters and been delivered to users – the anti-malware service is updated to defend against those attacks, and the service is rerun against recently delivered message to retroactively remove instances of said attack.
Processing message:
The types of processing done on messages to determine whether or not they are malicious include simple rules (e.g. messages without senders are likely not valid), reputations systems (messages from a certain set of IP addresses or senders are likely not valid, such as lists managed by the Spamhaus project[5]), digital thumbprints (comparing the thumbprint of the message or attachment to the thumbprints of known bad messages), honey pots (email addresses with no user and thus mailboxes that could never get any valid messages – anything delivered to them is spam or malware), and complex machine-learned models which process the contents of the message or the attachment[6]. As new forms of attack are encountered, new forms of defense must be quickly developed to keep users safe.
This requires processing of the message envelope, body, and attachment. For example:
- Message envelopes indicate not only the message recipient but also the supposed sender, and the server path which the message followed to reach the recipient. This is critical, not only to determine the recipient (needed to ensure the message is delivered to the intended recipients), but also to determine how probable it is that the sender is who they claim to be. It is common for attackers to “spoof” a sender, i.e. pretend they are a certain sender even though they are not. Knowing the path taken by the message can help determine if it has been sent by a spoof sender. For example, if a message originates from a trusted sending service which verifies the identity of the sender, then passes through a series of trusted intermediate services to the destination, the probability that the sender has been spoofed is much lower.
- Message bodies are among the most critical elements of the message which need to be processed to determine if the message is likely spam or a phishing attack. For example, text about “great deals on pharmaceuticals” is often indicative of spam. Without processing the body of the message, it is impossible to determine this. Attackers know that defenders watch out for such phrases, so they often try to hide them as text within an image. To the reader this looks similar, but defenders must run the images through optical character recognition algorithms to convert the images into text that can then be compared against a set of suspicious phrases. For example:
Another example of message body analysis is comparing the text of hyper-links to the URL. If a hyperlink’s text says “Click here to reset your Facebook password” but the URL points to “http://12345.contoso.com“, it is likely a phishing attack because Facebook password reset links should never be any URL other a correct Facebook one. Because most users do not check the URL before clicking on the hyperlink, it is important to protect them from such attacks. Without processing the message body, this is impossible.
- It is equally important to analyze attachments; otherwise attackers use them to deliver malicious payloads or contents to users. Attachments can be executables that open a user’s computer to attacker control. They can also be phishing attacks with the mismatched hyperlink text and URL scenario we described above embedded into the attachment. Any attack in the body of a message can appear in an attachment, and attachments can include additional forms of attack.
Model building:
Model building is the portion of machine learning in which the logic that does the evaluation is updated. It is the “learning” part of the machine learning; where the evaluation algorithm is updated based on new data so that it produces the desired output, not only based on data and results it has previous seen and been trained on, but also based on any new data or results.
The entire computer science sub-discipline of machine learning is the science of learning algorithms, and of this training phase, so a full treatise is beyond the scope of this paper. Generally speaking however, learning algorithms for detecting malware can be developed that respect the privacy of recipients because what is necessary is an understanding of the attack and the pattern of the attack, not the victims of that attack.
Privacy: data protection and confidentiality implications
Protecting the personal data of both sender and recipients, and communications confidentiality, during message processing (“A” – “D” above) can be done without diminishing the efficacy of the anti-malware service because that service acts as a stateless function. The service process the message and creates new metadata indicating whether or not the message should be delivered, without retaining any knowledge of the contents of the message and without exposing the message to anyone except the intended recipients. The recipient’s communication service processes and accesses the content on behalf of the recipient; and it is the recipient’s expectation to be protected against spam and malicious communications.. Failing to process every user’s every message would expose the entire service, and all its users, to known infections, which would be irresponsible.
Protecting personal data and confidentiality during the model building phase (“E” – “F” above) is done by a selection of algorithms and approaches that preserve privacy and confidentiality, those in which personal data is not retained or exposed (for example, selection of privacy preserving machine learning feature vectors), by restricting the use of the communication to building anti-malware capabilities[7], or by building user-specific models which solely benefit that user. The first two techniques have been used historically, but the third is becoming increasingly common as users’ expectations of what qualifies as nuisance communications (i.e. spam) become more individualized[8].
Using communication data for model building in anti-malware capabilities is done without explicit user consent. Malware is an ongoing struggle between attackers and the people providing the communications safety service, with attackers trying to find ways to get messages past the safety service. As new attacks emerge the safety service must respond quickly[9], using as much information as is available (which often necessitates sharing information with the anti-malware elements of other services). Attackers are increasingly using machine learning to create and launch attacks[10], requiring defenders to respond in kind with increasingly advanced machine learning-based defenses. One way to do this is to automate the creation of new versions of the anti-malware model so the service quickly inoculates all users against new attacks. The effectiveness of anti-malware depends on knowing about, and inoculating all users against, these attacks. This data can be used without exposing personal data or compromising confidentiality. All users of a service, and the entire service itself, are at risk if we fail to constantly process content in order to detect new forms of infection for every user. Similar to failing to inoculate a few members of a large population against an infectious disease, failing to process all users against these attacks would be irresponsible and would ultimately put the entire population at risk.
For anti-malware it important to note that the sender is generally malicious, and unlikely to grant consent to build better defenses against their attack. Requiring consent from all parties will make it impossible for services to provide a safe, secure, and nuisance-free communications and collaboration environment for all.
[1] It is difficult to differentiate between communication and collaboration, or between messages and other collaboration artifacts. Consider a document jointly authored by many people, each of whom leaves comments in the document to express ideas and input. Those same comments could be transmitted as email, chats, or through voice rather than comments in a document. Rather than treat them as separate, we recognize collaboration and communication as linked and refer to them interchangeably.
[2] Privacy, protection of personal data and confidentiality are frequently treated as synonymous, but we draw a distinction. For the purposes of this paper we treat data protection as the act of protecting knowledge of who a piece of data is about, and confidentiality as protecting that information. For example, consider a piece of data that indicates Bob is interested in buying a car. Data protection can be achieved by removing any knowledge that the data is about Bob; knowing simply that someone is interested in buying a car protects Bob’s privacy. Protecting confidentiality is preventing Bob’s data from being exposed to anyone but him. In this specific instance, Bob may only be concerned with protecting his personal data. However, if the information related to Microsoft’s interest in buying LinkedIn, Microsoft would be very interested in protecting the confidentiality of that data.
[3] Henceforth in this paper we will refer to this as an email service, but it is understood that similar problems and solutions apply to other communication and collaboration services.
[4] A staggering 77.8% of all messages sent to an email service are spam, with 90.4% of them being identified as such with sufficient certainty to prevent them ever being delivered to users.
[5] https://www.spamhaus.org/
[6] Use of machine learning in anti-spam services is one of the oldest, most pervasive, and most useful applications of that technology, dating back to at least 1998 (http://robotics.stanford.edu/users/sahami/papers-dir/spam.pdf)
[7] Services like Office365 that provide subscription-funded productivity services to users are incentivized to preserve the confidentiality of user data; the user is the customer, not the product.
[8] To my daughter, communications about new Lego toys are not a nuisance, they are interesting and desirable. However to me they are an imposition.
[9] Today, a typical spam campaign lasts under an hour. Yet in that time it gets through often enough to make it worthwhile to the attacker.
[10] https://erpscan.com/press-center/blog/machine-learning-for-cybercriminals
– Jim Kleewein, Technical Fellow, Microsoft
Electronic communication and collaboration services[1] such as Outlook.com, Skype, Gmail, Slack, and OneDrive carry valuable private and confidential communications that need protection. But these same services also provide a means for attackers to steal information or seize control of users’ computers for nefarious purposes, via viruses, worms, spam, phishing attacks, and other forms of malware.
Preventing the theft of user information and the dissemination of malware is a core feature of electronic communication and collaboration services. This requires significant processing of users’ communications and data both in-transit and after delivery. This processing can and should be done without compromising the user’s privacy or the confidentiality of their communications[2].
Message processing data flow:
To protect against malware distributed via electronic communications and collaboration systems such as email servers[3], the content follows a conceptually simple flow.
Starting with “A” the message is received by the recipient’s email service. The message’s envelope, as well as the message contents and any attachments, are passed on to the anti-malware portion of the email service (“B”) which determines whether or not the message is malware. Based on what the anti-malware service determines, the message is delivered to the user as appropriate (“C”). Some messages are determined to be malware with near certainty and are never delivered to the user. Instead they are deleted as quickly as possible[4]. Some messages are likely to be spam, however the service is not always certain. So the message is delivered to the user’s mailbox but into their spam/junk-mail folder. The remaining valid messages are delivered to the user’s inbox. The service can never determine with absolute certainty whether or not a message is malicious; it is always a probabilistic assessment. If the service is wrong either way; i.e. the user is exposed to malware or the user indicates that a message originally thought to be spam is not, the message may be added to a database of messages (“E”) used to train the next version of the anti-malware logic (“F”), thus permitting the system to “learn” over time and become more effective.
Clearly this entire process entails considerable processing of the messages. The types of processing are diverse and done in two key phases: message processing (“A” – “D”) and model building (“E” – “F”).
Anti-malware is particularly important for in-transit messages because attacks most typically enter the service through communications being transmitted. It is, however, also performed against already received and processed messages. As new attacks are identified – usually after the attack has been launched and some infected content has evaded the filters and been delivered to users – the anti-malware service is updated to defend against those attacks, and the service is rerun against recently delivered message to retroactively remove instances of said attack.
Processing message:
The types of processing done on messages to determine whether or not they are malicious include simple rules (e.g. messages without senders are likely not valid), reputations systems (messages from a certain set of IP addresses or senders are likely not valid, such as lists managed by the Spamhaus project[5]), digital thumbprints (comparing the thumbprint of the message or attachment to the thumbprints of known bad messages), honey pots (email addresses with no user and thus mailboxes that could never get any valid messages – anything delivered to them is spam or malware), and complex machine-learned models which process the contents of the message or the attachment[6]. As new forms of attack are encountered, new forms of defense must be quickly developed to keep users safe.
This requires processing of the message envelope, body, and attachment. For example:
- Message envelopes indicate not only the message recipient but also the supposed sender, and the server path which the message followed to reach the recipient. This is critical, not only to determine the recipient (needed to ensure the message is delivered to the intended recipients), but also to determine how probable it is that the sender is who they claim to be. It is common for attackers to “spoof” a sender, i.e. pretend they are a certain sender even though they are not. Knowing the path taken by the message can help determine if it has been sent by a spoof sender. For example, if a message originates from a trusted sending service which verifies the identity of the sender, then passes through a series of trusted intermediate services to the destination, the probability that the sender has been spoofed is much lower.
- Message bodies are among the most critical elements of the message which need to be processed to determine if the message is likely spam or a phishing attack. For example, text about “great deals on pharmaceuticals” is often indicative of spam. Without processing the body of the message, it is impossible to determine this. Attackers know that defenders watch out for such phrases, so they often try to hide them as text within an image. To the reader this looks similar, but defenders must run the images through optical character recognition algorithms to convert the images into text that can then be compared against a set of suspicious phrases. For example:
Another example of message body analysis is comparing the text of hyper-links to the URL. If a hyperlink’s text says “Click here to reset your Facebook password” but the URL points to “http://12345.contoso.com“, it is likely a phishing attack because Facebook password reset links should never be any URL other a correct Facebook one. Because most users do not check the URL before clicking on the hyperlink, it is important to protect them from such attacks. Without processing the message body, this is impossible.
- It is equally important to analyze attachments; otherwise attackers use them to deliver malicious payloads or contents to users. Attachments can be executables that open a user’s computer to attacker control. They can also be phishing attacks with the mismatched hyperlink text and URL scenario we described above embedded into the attachment. Any attack in the body of a message can appear in an attachment, and attachments can include additional forms of attack.
Model building:
Model building is the portion of machine learning in which the logic that does the evaluation is updated. It is the “learning” part of the machine learning; where the evaluation algorithm is updated based on new data so that it produces the desired output, not only based on data and results it has previous seen and been trained on, but also based on any new data or results.
The entire computer science sub-discipline of machine learning is the science of learning algorithms, and of this training phase, so a full treatise is beyond the scope of this paper. Generally speaking however, learning algorithms for detecting malware can be developed that respect the privacy of recipients because what is necessary is an understanding of the attack and the pattern of the attack, not the victims of that attack.
Privacy: data protection and confidentiality implications
Protecting the personal data of both sender and recipients, and communications confidentiality, during message processing (“A” – “D” above) can be done without diminishing the efficacy of the anti-malware service because that service acts as a stateless function. The service process the message and creates new metadata indicating whether or not the message should be delivered, without retaining any knowledge of the contents of the message and without exposing the message to anyone except the intended recipients. The recipient’s communication service processes and accesses the content on behalf of the recipient; and it is the recipient’s expectation to be protected against spam and malicious communications.. Failing to process every user’s every message would expose the entire service, and all its users, to known infections, which would be irresponsible.
Protecting personal data and confidentiality during the model building phase (“E” – “F” above) is done by a selection of algorithms and approaches that preserve privacy and confidentiality, those in which personal data is not retained or exposed (for example, selection of privacy preserving machine learning feature vectors), by restricting the use of the communication to building anti-malware capabilities[7], or by building user-specific models which solely benefit that user. The first two techniques have been used historically, but the third is becoming increasingly common as users’ expectations of what qualifies as nuisance communications (i.e. spam) become more individualized[8].
Using communication data for model building in anti-malware capabilities is done without explicit user consent. Malware is an ongoing struggle between attackers and the people providing the communications safety service, with attackers trying to find ways to get messages past the safety service. As new attacks emerge the safety service must respond quickly[9], using as much information as is available (which often necessitates sharing information with the anti-malware elements of other services). Attackers are increasingly using machine learning to create and launch attacks[10], requiring defenders to respond in kind with increasingly advanced machine learning-based defenses. One way to do this is to automate the creation of new versions of the anti-malware model so the service quickly inoculates all users against new attacks. The effectiveness of anti-malware depends on knowing about, and inoculating all users against, these attacks. This data can be used without exposing personal data or compromising confidentiality. All users of a service, and the entire service itself, are at risk if we fail to constantly process content in order to detect new forms of infection for every user. Similar to failing to inoculate a few members of a large population against an infectious disease, failing to process all users against these attacks would be irresponsible and would ultimately put the entire population at risk.
For anti-malware it important to note that the sender is generally malicious, and unlikely to grant consent to build better defenses against their attack. Requiring consent from all parties will make it impossible for services to provide a safe, secure, and nuisance-free communications and collaboration environment for all.
[1] It is difficult to differentiate between communication and collaboration, or between messages and other collaboration artifacts. Consider a document jointly authored by many people, each of whom leaves comments in the document to express ideas and input. Those same comments could be transmitted as email, chats, or through voice rather than comments in a document. Rather than treat them as separate, we recognize collaboration and communication as linked and refer to them interchangeably.
[2] Privacy, protection of personal data and confidentiality are frequently treated as synonymous, but we draw a distinction. For the purposes of this paper we treat data protection as the act of protecting knowledge of who a piece of data is about, and confidentiality as protecting that information. For example, consider a piece of data that indicates Bob is interested in buying a car. Data protection can be achieved by removing any knowledge that the data is about Bob; knowing simply that someone is interested in buying a car protects Bob’s privacy. Protecting confidentiality is preventing Bob’s data from being exposed to anyone but him. In this specific instance, Bob may only be concerned with protecting his personal data. However, if the information related to Microsoft’s interest in buying LinkedIn, Microsoft would be very interested in protecting the confidentiality of that data.
[3] Henceforth in this paper we will refer to this as an email service, but it is understood that similar problems and solutions apply to other communication and collaboration services.
[4] A staggering 77.8% of all messages sent to an email service are spam, with 90.4% of them being identified as such with sufficient certainty to prevent them ever being delivered to users.
[5] https://www.spamhaus.org/
[6] Use of machine learning in anti-spam services is one of the oldest, most pervasive, and most useful applications of that technology, dating back to at least 1998 (http://robotics.stanford.edu/users/sahami/papers-dir/spam.pdf)
[7] Services like Office365 that provide subscription-funded productivity services to users are incentivized to preserve the confidentiality of user data; the user is the customer, not the product.
[8] To my daughter, communications about new Lego toys are not a nuisance, they are interesting and desirable. However to me they are an imposition.
[9] Today, a typical spam campaign lasts under an hour. Yet in that time it gets through often enough to make it worthwhile to the attacker.
[10] https://erpscan.com/press-center/blog/machine-learning-for-cybercriminals
– Jim Kleewein, Technical Fellow, Microsoft
Electronic communication and collaboration services[1] such as Outlook.com, Skype, Gmail, Slack, and OneDrive carry valuable private and confidential communications that need protection. But these same services also provide a means for attackers to steal information or seize control of users’ computers for nefarious purposes, via viruses, worms, spam, phishing attacks, and other forms of malware.
Preventing the theft of user information and the dissemination of malware is a core feature of electronic communication and collaboration services. This requires significant processing of users’ communications and data both in-transit and after delivery. This processing can and should be done without compromising the user’s privacy or the confidentiality of their communications[2].
Message processing data flow:
To protect against malware distributed via electronic communications and collaboration systems such as email servers[3], the content follows a conceptually simple flow.
Starting with “A” the message is received by the recipient’s email service. The message’s envelope, as well as the message contents and any attachments, are passed on to the anti-malware portion of the email service (“B”) which determines whether or not the message is malware. Based on what the anti-malware service determines, the message is delivered to the user as appropriate (“C”). Some messages are determined to be malware with near certainty and are never delivered to the user. Instead they are deleted as quickly as possible[4]. Some messages are likely to be spam, however the service is not always certain. So the message is delivered to the user’s mailbox but into their spam/junk-mail folder. The remaining valid messages are delivered to the user’s inbox. The service can never determine with absolute certainty whether or not a message is malicious; it is always a probabilistic assessment. If the service is wrong either way; i.e. the user is exposed to malware or the user indicates that a message originally thought to be spam is not, the message may be added to a database of messages (“E”) used to train the next version of the anti-malware logic (“F”), thus permitting the system to “learn” over time and become more effective.
Clearly this entire process entails considerable processing of the messages. The types of processing are diverse and done in two key phases: message processing (“A” – “D”) and model building (“E” – “F”).
Anti-malware is particularly important for in-transit messages because attacks most typically enter the service through communications being transmitted. It is, however, also performed against already received and processed messages. As new attacks are identified – usually after the attack has been launched and some infected content has evaded the filters and been delivered to users – the anti-malware service is updated to defend against those attacks, and the service is rerun against recently delivered message to retroactively remove instances of said attack.
Processing message:
The types of processing done on messages to determine whether or not they are malicious include simple rules (e.g. messages without senders are likely not valid), reputations systems (messages from a certain set of IP addresses or senders are likely not valid, such as lists managed by the Spamhaus project[5]), digital thumbprints (comparing the thumbprint of the message or attachment to the thumbprints of known bad messages), honey pots (email addresses with no user and thus mailboxes that could never get any valid messages – anything delivered to them is spam or malware), and complex machine-learned models which process the contents of the message or the attachment[6]. As new forms of attack are encountered, new forms of defense must be quickly developed to keep users safe.
This requires processing of the message envelope, body, and attachment. For example:
- Message envelopes indicate not only the message recipient but also the supposed sender, and the server path which the message followed to reach the recipient. This is critical, not only to determine the recipient (needed to ensure the message is delivered to the intended recipients), but also to determine how probable it is that the sender is who they claim to be. It is common for attackers to “spoof” a sender, i.e. pretend they are a certain sender even though they are not. Knowing the path taken by the message can help determine if it has been sent by a spoof sender. For example, if a message originates from a trusted sending service which verifies the identity of the sender, then passes through a series of trusted intermediate services to the destination, the probability that the sender has been spoofed is much lower.
- Message bodies are among the most critical elements of the message which need to be processed to determine if the message is likely spam or a phishing attack. For example, text about “great deals on pharmaceuticals” is often indicative of spam. Without processing the body of the message, it is impossible to determine this. Attackers know that defenders watch out for such phrases, so they often try to hide them as text within an image. To the reader this looks similar, but defenders must run the images through optical character recognition algorithms to convert the images into text that can then be compared against a set of suspicious phrases. For example:
Another example of message body analysis is comparing the text of hyper-links to the URL. If a hyperlink’s text says “Click here to reset your Facebook password” but the URL points to “http://12345.contoso.com“, it is likely a phishing attack because Facebook password reset links should never be any URL other a correct Facebook one. Because most users do not check the URL before clicking on the hyperlink, it is important to protect them from such attacks. Without processing the message body, this is impossible.
- It is equally important to analyze attachments; otherwise attackers use them to deliver malicious payloads or contents to users. Attachments can be executables that open a user’s computer to attacker control. They can also be phishing attacks with the mismatched hyperlink text and URL scenario we described above embedded into the attachment. Any attack in the body of a message can appear in an attachment, and attachments can include additional forms of attack.
Model building:
Model building is the portion of machine learning in which the logic that does the evaluation is updated. It is the “learning” part of the machine learning; where the evaluation algorithm is updated based on new data so that it produces the desired output, not only based on data and results it has previous seen and been trained on, but also based on any new data or results.
The entire computer science sub-discipline of machine learning is the science of learning algorithms, and of this training phase, so a full treatise is beyond the scope of this paper. Generally speaking however, learning algorithms for detecting malware can be developed that respect the privacy of recipients because what is necessary is an understanding of the attack and the pattern of the attack, not the victims of that attack.
Privacy: data protection and confidentiality implications
Protecting the personal data of both sender and recipients, and communications confidentiality, during message processing (“A” – “D” above) can be done without diminishing the efficacy of the anti-malware service because that service acts as a stateless function. The service process the message and creates new metadata indicating whether or not the message should be delivered, without retaining any knowledge of the contents of the message and without exposing the message to anyone except the intended recipients. The recipient’s communication service processes and accesses the content on behalf of the recipient; and it is the recipient’s expectation to be protected against spam and malicious communications.. Failing to process every user’s every message would expose the entire service, and all its users, to known infections, which would be irresponsible.
Protecting personal data and confidentiality during the model building phase (“E” – “F” above) is done by a selection of algorithms and approaches that preserve privacy and confidentiality, those in which personal data is not retained or exposed (for example, selection of privacy preserving machine learning feature vectors), by restricting the use of the communication to building anti-malware capabilities[7], or by building user-specific models which solely benefit that user. The first two techniques have been used historically, but the third is becoming increasingly common as users’ expectations of what qualifies as nuisance communications (i.e. spam) become more individualized[8].
Using communication data for model building in anti-malware capabilities is done without explicit user consent. Malware is an ongoing struggle between attackers and the people providing the communications safety service, with attackers trying to find ways to get messages past the safety service. As new attacks emerge the safety service must respond quickly[9], using as much information as is available (which often necessitates sharing information with the anti-malware elements of other services). Attackers are increasingly using machine learning to create and launch attacks[10], requiring defenders to respond in kind with increasingly advanced machine learning-based defenses. One way to do this is to automate the creation of new versions of the anti-malware model so the service quickly inoculates all users against new attacks. The effectiveness of anti-malware depends on knowing about, and inoculating all users against, these attacks. This data can be used without exposing personal data or compromising confidentiality. All users of a service, and the entire service itself, are at risk if we fail to constantly process content in order to detect new forms of infection for every user. Similar to failing to inoculate a few members of a large population against an infectious disease, failing to process all users against these attacks would be irresponsible and would ultimately put the entire population at risk.
For anti-malware it important to note that the sender is generally malicious, and unlikely to grant consent to build better defenses against their attack. Requiring consent from all parties will make it impossible for services to provide a safe, secure, and nuisance-free communications and collaboration environment for all.
[1] It is difficult to differentiate between communication and collaboration, or between messages and other collaboration artifacts. Consider a document jointly authored by many people, each of whom leaves comments in the document to express ideas and input. Those same comments could be transmitted as email, chats, or through voice rather than comments in a document. Rather than treat them as separate, we recognize collaboration and communication as linked and refer to them interchangeably.
[2] Privacy, protection of personal data and confidentiality are frequently treated as synonymous, but we draw a distinction. For the purposes of this paper we treat data protection as the act of protecting knowledge of who a piece of data is about, and confidentiality as protecting that information. For example, consider a piece of data that indicates Bob is interested in buying a car. Data protection can be achieved by removing any knowledge that the data is about Bob; knowing simply that someone is interested in buying a car protects Bob’s privacy. Protecting confidentiality is preventing Bob’s data from being exposed to anyone but him. In this specific instance, Bob may only be concerned with protecting his personal data. However, if the information related to Microsoft’s interest in buying LinkedIn, Microsoft would be very interested in protecting the confidentiality of that data.
[3] Henceforth in this paper we will refer to this as an email service, but it is understood that similar problems and solutions apply to other communication and collaboration services.
[4] A staggering 77.8% of all messages sent to an email service are spam, with 90.4% of them being identified as such with sufficient certainty to prevent them ever being delivered to users.
[5] https://www.spamhaus.org/
[6] Use of machine learning in anti-spam services is one of the oldest, most pervasive, and most useful applications of that technology, dating back to at least 1998 (http://robotics.stanford.edu/users/sahami/papers-dir/spam.pdf)
[7] Services like Office365 that provide subscription-funded productivity services to users are incentivized to preserve the confidentiality of user data; the user is the customer, not the product.
[8] To my daughter, communications about new Lego toys are not a nuisance, they are interesting and desirable. However to me they are an imposition.
[9] Today, a typical spam campaign lasts under an hour. Yet in that time it gets through often enough to make it worthwhile to the attacker.
[10] https://erpscan.com/press-center/blog/machine-learning-for-cybercriminals
– Jim Kleewein, Technical Fellow, Microsoft
The following is provided from Microsoft Security and Compliance blogs at TechCommunity:
Last September, we announced new capabilities in Office 365 Message Encryption that enable users to seamlessly collaborate on protected emails with anyone. This release included Do Not Forward an out-of-the-box policy that encrypts emails and Office attachments, and restricts the content and email from being forwarded, printed or copied.
Today, we are happy to share that we are releasing another out-of-the-box policy called encrypt only. With the encrypt-only policy, users can send encrypted email to any recipient, whether they are inside or outside the organization, and the protection follows the lifecycle of the email. That means recipients can copy, print and forward the email, and encryption will not be removed. This new policy provides more flexibility in the type of protection that can be applied to your sensitive emails.
This is valuable for organizations that want persistent encryption, but do not want to add additional restrictions. For example, a doctor looking to protect an email containing sensitive personal information, can apply the encrypt-only policy, and the patient receiving the email can easily consume the protected message regardless of their email provider, and forward that email to another trusted party.
With this new, flexible policy, users and admins can apply different levels of protection to best fit their data protection needs.
Read more to understand what the encrypt-only policy looks like and how to apply the policy.
How the encrypt-only policy works
The encrypt-only policy is an out-of-the box policy that can be used without additional configuration, and as the name suggests, only applies encryption to the email. You can apply the policy through end-user controls in Outlook or through automatic admin managed controls in the Exchange admin center. Users can apply this policy to individual emails through end-user controls in Outlook, and Admins can apply this policy automatically to any email that matches the set criteria through admin-managed controls in the Exchange admin center.
Customers that have enabled the new Office 365 Message Encryption capabilities will see the encrypt-only policy first through Outlook on the web and in the Exchange admin center under mail flow rules. Updates to Outlook for Windows and Outlook for Mac are planned for the coming months.
How to send an email with the encrypt-only policy in Outlook on the web
Users can apply protection with the encrypt-only policy by clicking on the protect button and changing the permissions to just encrypt. While the other options encrypt the message, the encrypt option will apply the encrypt-only policy to the message, therefore enabling recipients to forward, copy and print the message.
Applying this option will offer added flexibility for recipients to share the email with other trusted parties while encryption continues to persist and throughout the lifecycle of the email.
In Outlook on the web, users can click on the protect button to change the permissions of the email. Once a user clicks on protect, the users can click on encrypt, to only encrypt the email. Once the encrypt-only policy is applied, the user will see a notification that encryption has been applied.
How to apply the encrypt-only policy through Exchange mail flow rules
As an administrator, you can apply the encrypt-only policy automatically to emails that meet certain conditions by creating a mail flow rule. When you do this, email affected by the encrypt-only policy is encrypted in transport by Office 365.
For instructions on creating a mail flow rule that employs the encrypt-only policy, see define mail flow rules to encrypt email messages in Office 365.
You as an administrator can create new mail flow rule to automatically apply the encrypt-only policy to emails.
How to read encrypt-only email using Outlook on the web and Outlook mobile
Office 365 recipients can easily read and reply to emails that have been applied with the encrypt-only policy using Outlook on the web and Outlook mobile directly from the client.
Users can read the encrypted message natively directly in Outlook on the web and Outlook mobile.
The inline reading experience for Outlook desktop (Windows and Mac) will be available in the coming months. In the meantime, Office 365 users using Outlook desktop will see the encrypted mail as an html mail with an rpmsg_v2 attachment.
How to read encrypt-only emails for non-Office 365 users (on-prem, Gmail, and Outlook.com users)
Non-Office 365 users, receive an html mail with an rpmsg_v4 attachment. Once they click Read Message they are redirected to the Office 365 Message Encryption portal where they can reply, forward, print, or take other allowed actions. More information can be found in this article.
Get started!
The new encrypt-only policy rolls out starting today as part of Office 365 Message Encryption.
Office 365 Message Encryption is offered in Office 365 E3 and E5, or as an add-on -you can find the full list of where Office 365 Message Encryption is offered here.
Please let us know what you think here or give us your feedback on uservoice!
The above was provided from Microsoft Security and Compliance blogs at TechCommunity
Last September, we announced new capabilities in Office 365 Message Encryption that enable users to seamlessly collaborate on protected emails with anyone. This release included Do Not Forward an out-of-the-box policy that encrypts emails and Office attachments, and restricts the content and email from being forwarded, printed or copied.
Today, we are happy to share that we are releasing another out-of-the-box policy called encrypt only. With the encrypt-only policy, users can send encrypted email to any recipient, whether they are inside or outside the organization, and the protection follows the lifecycle of the email. That means recipients can copy, print and forward the email, and encryption will not be removed. This new policy provides more flexibility in the type of protection that can be applied to your sensitive emails.
This is valuable for organizations that want persistent encryption, but do not want to add additional restrictions. For example, a doctor looking to protect an email containing sensitive personal information, can apply the encrypt-only policy, and the patient receiving the email can easily consume the protected message regardless of their email provider, and forward that email to another trusted party.
With this new, flexible policy, users and admins can apply different levels of protection to best fit their data protection needs.
Read more to understand what the encrypt-only policy looks like and how to apply the policy.
How the encrypt-only policy works
The encrypt-only policy is an out-of-the box policy that can be used without additional configuration, and as the name suggests, only applies encryption to the email. You can apply the policy through end-user controls in Outlook or through automatic admin managed controls in the Exchange admin center. Users can apply this policy to individual emails through end-user controls in Outlook, and Admins can apply this policy automatically to any email that matches the set criteria through admin-managed controls in the Exchange admin center.
Customers that have enabled the new Office 365 Message Encryption capabilities will see the encrypt-only policy first through Outlook on the web and in the Exchange admin center under mail flow rules. Updates to Outlook for Windows and Outlook for Mac are planned for the coming months.
How to send an email with the encrypt-only policy in Outlook on the web
Users can apply protection with the encrypt-only policy by clicking on the protect button and changing the permissions to just encrypt. While the other options encrypt the message, the encrypt option will apply the encrypt-only policy to the message, therefore enabling recipients to forward, copy and print the message.
Applying this option will offer added flexibility for recipients to share the email with other trusted parties while encryption continues to persist and throughout the lifecycle of the email.
In Outlook on the web, users can click on the protect button to change the permissions of the email. Once a user clicks on protect, the users can click on encrypt, to only encrypt the email. Once the encrypt-only policy is applied, the user will see a notification that encryption has been applied.
How to apply the encrypt-only policy through Exchange mail flow rules
As an administrator, you can apply the encrypt-only policy automatically to emails that meet certain conditions by creating a mail flow rule. When you do this, email affected by the encrypt-only policy is encrypted in transport by Office 365.
For instructions on creating a mail flow rule that employs the encrypt-only policy, see define mail flow rules to encrypt email messages in Office 365.
You as an administrator can create new mail flow rule to automatically apply the encrypt-only policy to emails.
How to read encrypt-only email using Outlook on the web and Outlook mobile
Office 365 recipients can easily read and reply to emails that have been applied with the encrypt-only policy using Outlook on the web and Outlook mobile directly from the client.
Users can read the encrypted message natively directly in Outlook on the web and Outlook mobile.
The inline reading experience for Outlook desktop (Windows and Mac) will be available in the coming months. In the meantime, Office 365 users using Outlook desktop will see the encrypted mail as an html mail with an rpmsg_v2 attachment.
How to read encrypt-only emails for non-Office 365 users (on-prem, Gmail, and Outlook.com users)
Non-Office 365 users, receive an html mail with an rpmsg_v4 attachment. Once they click Read Message they are redirected to the Office 365 Message Encryption portal where they can reply, forward, print, or take other allowed actions. More information can be found in this article.
Get started!
The new encrypt-only policy rolls out starting today as part of Office 365 Message Encryption.
Office 365 Message Encryption is offered in Office 365 E3 and E5, or as an add-on -you can find the full list of where Office 365 Message Encryption is offered here.
Please let us know what you think here or give us your feedback on uservoice!
Last September, we announced new capabilities in Office 365 Message Encryption that enable users to seamlessly collaborate on protected emails with anyone. This release included Do Not Forward an out-of-the-box policy that encrypts emails and Office attachments, and restricts the content and email from being forwarded, printed or copied.
Today, we are happy to share that we are releasing another out-of-the-box policy called encrypt only. With the encrypt-only policy, users can send encrypted email to any recipient, whether they are inside or outside the organization, and the protection follows the lifecycle of the email. That means recipients can copy, print and forward the email, and encryption will not be removed. This new policy provides more flexibility in the type of protection that can be applied to your sensitive emails.
This is valuable for organizations that want persistent encryption, but do not want to add additional restrictions. For example, a doctor looking to protect an email containing sensitive personal information, can apply the encrypt-only policy, and the patient receiving the email can easily consume the protected message regardless of their email provider, and forward that email to another trusted party.
With this new, flexible policy, users and admins can apply different levels of protection to best fit their data protection needs.
Read more to understand what the encrypt-only policy looks like and how to apply the policy.
How the encrypt-only policy works
The encrypt-only policy is an out-of-the box policy that can be used without additional configuration, and as the name suggests, only applies encryption to the email. You can apply the policy through end-user controls in Outlook or through automatic admin managed controls in the Exchange admin center. Users can apply this policy to individual emails through end-user controls in Outlook, and Admins can apply this policy automatically to any email that matches the set criteria through admin-managed controls in the Exchange admin center.
Customers that have enabled the new Office 365 Message Encryption capabilities will see the encrypt-only policy first through Outlook on the web and in the Exchange admin center under mail flow rules. Updates to Outlook for Windows and Outlook for Mac are planned for the coming months.
How to send an email with the encrypt-only policy in Outlook on the web
Users can apply protection with the encrypt-only policy by clicking on the protect button and changing the permissions to just encrypt. While the other options encrypt the message, the encrypt option will apply the encrypt-only policy to the message, therefore enabling recipients to forward, copy and print the message.
Applying this option will offer added flexibility for recipients to share the email with other trusted parties while encryption continues to persist and throughout the lifecycle of the email.
In Outlook on the web, users can click on the protect button to change the permissions of the email. Once a user clicks on protect, the users can click on encrypt, to only encrypt the email. Once the encrypt-only policy is applied, the user will see a notification that encryption has been applied.
How to apply the encrypt-only policy through Exchange mail flow rules
As an administrator, you can apply the encrypt-only policy automatically to emails that meet certain conditions by creating a mail flow rule. When you do this, email affected by the encrypt-only policy is encrypted in transport by Office 365.
For instructions on creating a mail flow rule that employs the encrypt-only policy, see define mail flow rules to encrypt email messages in Office 365.
You as an administrator can create new mail flow rule to automatically apply the encrypt-only policy to emails.
How to read encrypt-only email using Outlook on the web and Outlook mobile
Office 365 recipients can easily read and reply to emails that have been applied with the encrypt-only policy using Outlook on the web and Outlook mobile directly from the client.
Users can read the encrypted message natively directly in Outlook on the web and Outlook mobile.
The inline reading experience for Outlook desktop (Windows and Mac) will be available in the coming months. In the meantime, Office 365 users using Outlook desktop will see the encrypted mail as an html mail with an rpmsg_v2 attachment.
How to read encrypt-only emails for non-Office 365 users (on-prem, Gmail, and Outlook.com users)
Non-Office 365 users, receive an html mail with an rpmsg_v4 attachment. Once they click Read Message they are redirected to the Office 365 Message Encryption portal where they can reply, forward, print, or take other allowed actions. More information can be found in this article.
Get started!
The new encrypt-only policy rolls out starting today as part of Office 365 Message Encryption.
Office 365 Message Encryption is offered in Office 365 E3 and E5, or as an add-on -you can find the full list of where Office 365 Message Encryption is offered here.
Please let us know what you think here or give us your feedback on uservoice!
Last September, we announced new capabilities in Office 365 Message Encryption that enable users to seamlessly collaborate on protected emails with anyone. This release included Do Not Forward an out-of-the-box policy that encrypts emails and Office attachments, and restricts the content and email from being forwarded, printed or copied.
Today, we are happy to share that we are releasing another out-of-the-box policy called encrypt only. With the encrypt-only policy, users can send encrypted email to any recipient, whether they are inside or outside the organization, and the protection follows the lifecycle of the email. That means recipients can copy, print and forward the email, and encryption will not be removed. This new policy provides more flexibility in the type of protection that can be applied to your sensitive emails.
This is valuable for organizations that want persistent encryption, but do not want to add additional restrictions. For example, a doctor looking to protect an email containing sensitive personal information, can apply the encrypt-only policy, and the patient receiving the email can easily consume the protected message regardless of their email provider, and forward that email to another trusted party.
With this new, flexible policy, users and admins can apply different levels of protection to best fit their data protection needs.
Read more to understand what the encrypt-only policy looks like and how to apply the policy.
How the encrypt-only policy works
The encrypt-only policy is an out-of-the box policy that can be used without additional configuration, and as the name suggests, only applies encryption to the email. You can apply the policy through end-user controls in Outlook or through automatic admin managed controls in the Exchange admin center. Users can apply this policy to individual emails through end-user controls in Outlook, and Admins can apply this policy automatically to any email that matches the set criteria through admin-managed controls in the Exchange admin center.
Customers that have enabled the new Office 365 Message Encryption capabilities will see the encrypt-only policy first through Outlook on the web and in the Exchange admin center under mail flow rules. Updates to Outlook for Windows and Outlook for Mac are planned for the coming months.
How to send an email with the encrypt-only policy in Outlook on the web
Users can apply protection with the encrypt-only policy by clicking on the protect button and changing the permissions to just encrypt. While the other options encrypt the message, the encrypt option will apply the encrypt-only policy to the message, therefore enabling recipients to forward, copy and print the message.
Applying this option will offer added flexibility for recipients to share the email with other trusted parties while encryption continues to persist and throughout the lifecycle of the email.
In Outlook on the web, users can click on the protect button to change the permissions of the email. Once a user clicks on protect, the users can click on encrypt, to only encrypt the email. Once the encrypt-only policy is applied, the user will see a notification that encryption has been applied.
How to apply the encrypt-only policy through Exchange mail flow rules
As an administrator, you can apply the encrypt-only policy automatically to emails that meet certain conditions by creating a mail flow rule. When you do this, email affected by the encrypt-only policy is encrypted in transport by Office 365.
For instructions on creating a mail flow rule that employs the encrypt-only policy, see define mail flow rules to encrypt email messages in Office 365.
You as an administrator can create new mail flow rule to automatically apply the encrypt-only policy to emails.
How to read encrypt-only email using Outlook on the web and Outlook mobile
Office 365 recipients can easily read and reply to emails that have been applied with the encrypt-only policy using Outlook on the web and Outlook mobile directly from the client.
Users can read the encrypted message natively directly in Outlook on the web and Outlook mobile.
The inline reading experience for Outlook desktop (Windows and Mac) will be available in the coming months. In the meantime, Office 365 users using Outlook desktop will see the encrypted mail as an html mail with an rpmsg_v2 attachment.
How to read encrypt-only emails for non-Office 365 users (on-prem, Gmail, and Outlook.com users)
Non-Office 365 users, receive an html mail with an rpmsg_v4 attachment. Once they click Read Message they are redirected to the Office 365 Message Encryption portal where they can reply, forward, print, or take other allowed actions. More information can be found in this article.
Get started!
The new encrypt-only policy rolls out starting today as part of Office 365 Message Encryption.
Office 365 Message Encryption is offered in Office 365 E3 and E5, or as an add-on -you can find the full list of where Office 365 Message Encryption is offered here.
Please let us know what you think here or give us your feedback on uservoice!
Last September, we announced new capabilities in Office 365 Message Encryption that enable users to seamlessly collaborate on protected emails with anyone. This release included Do Not Forward an out-of-the-box policy that encrypts emails and Office attachments, and restricts the content and email from being forwarded, printed or copied.
Today, we are happy to share that we are releasing another out-of-the-box policy called encrypt only. With the encrypt-only policy, users can send encrypted email to any recipient, whether they are inside or outside the organization, and the protection follows the lifecycle of the email. That means recipients can copy, print and forward the email, and encryption will not be removed. This new policy provides more flexibility in the type of protection that can be applied to your sensitive emails.
This is valuable for organizations that want persistent encryption, but do not want to add additional restrictions. For example, a doctor looking to protect an email containing sensitive personal information, can apply the encrypt-only policy, and the patient receiving the email can easily consume the protected message regardless of their email provider, and forward that email to another trusted party.
With this new, flexible policy, users and admins can apply different levels of protection to best fit their data protection needs.
Read more to understand what the encrypt-only policy looks like and how to apply the policy.
How the encrypt-only policy works
The encrypt-only policy is an out-of-the box policy that can be used without additional configuration, and as the name suggests, only applies encryption to the email. You can apply the policy through end-user controls in Outlook or through automatic admin managed controls in the Exchange admin center. Users can apply this policy to individual emails through end-user controls in Outlook, and Admins can apply this policy automatically to any email that matches the set criteria through admin-managed controls in the Exchange admin center.
Customers that have enabled the new Office 365 Message Encryption capabilities will see the encrypt-only policy first through Outlook on the web and in the Exchange admin center under mail flow rules. Updates to Outlook for Windows and Outlook for Mac are planned for the coming months.
How to send an email with the encrypt-only policy in Outlook on the web
Users can apply protection with the encrypt-only policy by clicking on the protect button and changing the permissions to just encrypt. While the other options encrypt the message, the encrypt option will apply the encrypt-only policy to the message, therefore enabling recipients to forward, copy and print the message.
Applying this option will offer added flexibility for recipients to share the email with other trusted parties while encryption continues to persist and throughout the lifecycle of the email.
In Outlook on the web, users can click on the protect button to change the permissions of the email. Once a user clicks on protect, the users can click on encrypt, to only encrypt the email. Once the encrypt-only policy is applied, the user will see a notification that encryption has been applied.
How to apply the encrypt-only policy through Exchange mail flow rules
As an administrator, you can apply the encrypt-only policy automatically to emails that meet certain conditions by creating a mail flow rule. When you do this, email affected by the encrypt-only policy is encrypted in transport by Office 365.
For instructions on creating a mail flow rule that employs the encrypt-only policy, see define mail flow rules to encrypt email messages in Office 365.
You as an administrator can create new mail flow rule to automatically apply the encrypt-only policy to emails.
How to read encrypt-only email using Outlook on the web and Outlook mobile
Office 365 recipients can easily read and reply to emails that have been applied with the encrypt-only policy using Outlook on the web and Outlook mobile directly from the client.
Users can read the encrypted message natively directly in Outlook on the web and Outlook mobile.
The inline reading experience for Outlook desktop (Windows and Mac) will be available in the coming months. In the meantime, Office 365 users using Outlook desktop will see the encrypted mail as an html mail with an rpmsg_v2 attachment.
How to read encrypt-only emails for non-Office 365 users (on-prem, Gmail, and Outlook.com users)
Non-Office 365 users, receive an html mail with an rpmsg_v4 attachment. Once they click Read Message they are redirected to the Office 365 Message Encryption portal where they can reply, forward, print, or take other allowed actions. More information can be found in this article.
Get started!
The new encrypt-only policy rolls out starting today as part of Office 365 Message Encryption.
Office 365 Message Encryption is offered in Office 365 E3 and E5, or as an add-on -you can find the full list of where Office 365 Message Encryption is offered here.
Please let us know what you think here or give us your feedback on uservoice!
Last week, I attended a great Microsoft session concerning Compliance and Data Protection across the Office products, focusing on Archiving, Retention / Hold, Discovery and Data Loss Protection concerning compliance in 2013 products. I mentioned that I have clients who are interested in Office 365 but need some comfort concerning compliance, and queried if there was further information available. Was informed that there was a document available that described this which I must share with you all.
This document covers topics such as Office 365 Built in Security, like monitoring, isolation, automated operations, secure network and encrypted data. It describes security best practice, and the customer controls. It talks about how compliance is enabled through DPL, audit and retention, eDiscovery and Data spillage. It also describes the standards of compliance met, like ISO 27001, FISMA, HIPAA BAA, EU Model Clauses, and the CSA (Cloud Security Alliance).
If you are embarking on SharePoint migration to Office 365, or having a hybrid operation with on-premise SharePoint and Office 365, I would recommend reading this paper, as it will give you valuable information proving to the customer that Office 365 includes security features, protects data and provides administrators with the ability to configure, integrate and manage security.
To give you a taster, here’s the intro:
The ability for organizations to control and customize security features in cloud-based productivity services, such as email, calendars, content management, collaboration, and unified communications, is becoming an essential requirement for virtually every company. Today, IT teams are being required to deliver access to productivity services and associated documents and data from more devices, platforms, and places than ever before. While user benefits are undeniable, broader access makes security management more challenging. Each endpoint represents a potential attack surface and another point of management for security professionals. At the same time, organizations face ever-evolving threats from around the world and must manage the risk created by their own users accidentally losing or compromising sensitive data. For these reasons, organizations require a cloud service that has both (a) built-in robust security features and (b) a wide variety of customizable security features that organizations can tune to meet their individual requirements. Organizations expanding remote access while maintaining security best practices may find it difficult and expensive to add this combination of security functionality if they deploy productivity services solely on-premises.
You can download the article from here:
http://www.geoffevelyn.com/downloads/Security-in-Office-365-Whitepaper.pdf
And from here:
http://www.microsoft.com/en-us/download/details.aspx?id=26552
