Abstract:
In one embodiment, a device in a network receives an access policy and a class behavioral model for a node in the network that are associated with a class asserted by the node. The device applies the access policy and class behavioral model to traffic associated with the node. The device identifies a deviation in a behavior of the node from the class behavioral model, based on the application of the class behavioral model to the traffic associated with the node. The device causes performance of a mitigation action in the network based on the identified deviation in the behavior of the node from the class behavioral model.
Abstract:
In one embodiment, a device in a network detects an encrypted traffic flow associated with a client in the network. The device captures contextual traffic data regarding the encrypted traffic flow from one or more unencrypted packets associated with the client. The device performs a classification of the encrypted traffic flow by using the contextual traffic data as input to a machine learning-based classifier. The device generates an alert based on the classification of the encrypted traffic flow.
Abstract:
In one embodiment, a device in a first network receives traffic flow information regarding a plurality of traffic flows in the first network. The device labels the traffic flow information by associating classifier labels to the traffic flow information. The device receives a generic traffic classifier that was trained using a training data set that comprises labeled traffic flow information for a plurality of other networks and excludes the traffic flow information regarding the plurality of traffic flows in the first network. The device acclimates the generic traffic classifier to the first network using the labeled traffic flow information regarding the plurality of traffic flows in the first network.
Abstract:
Techniques are presented to identify malware communication with domain generation algorithm (DGA) generated domains. Sample domain names are obtained and labeled as DGA domains, non-DGA domains or suspicious domains. A classifier is trained in a first stage based on the sample domain names. Sample proxy logs including proxy logs of DGA domains and proxy logs of non-DGA domains are obtained to train the classifier in a second stage based on the plurality of sample domain names and the plurality of sample proxy logs. Live traffic proxy logs are obtained and the classifier is tested by classifying the live traffic proxy logs as DGA proxy logs, and the classifier is forwarded to a second computing device to identify network communication of a third computing device as malware network communication with DGA domains via a network interface unit of the third computing device based on the trained and tested classifier.
Abstract:
A server sends information to a client that allows the client to establish a first key at the client. The server then receives a session ID that has been encrypted using the first key. The first key is then established at the server, which can then decrypt the session ID using the first key. After the server validates the session ID, it determines a second key that is different from the first key. The server then receives the session ID encrypted with the second key, and decrypts the session ID encrypted with the second key.
Abstract:
Techniques are provided for obtaining first and second digital certificates from a certificate authority database for establishing a secure exchange between network devices. The first digital certificate contains identity information of a first network device, and the second digital certificate contains classification information of the first network device. In one embodiment, a secure key exchange is initiated with the second network device, and the first and second digital certificates are transmitted as a part of the secure key exchange to the second network device. In another embodiment, the first and second digital certificates are received by an intermediate network device. The first digital certificate is encrypted and is not evaluated by the intermediate network device. The second digital certificate is evaluated for classification information of the first network device. Source information associated with the first network device is stored, and encrypted traffic is processed between the network devices.
Abstract:
A method of providing anti-replay protection, authentication, and encryption with minimal data overhead is provided. A sender uses an arbitrary-length pseudorandom permutation to encrypt messages that include plaintext and successively increasing sequence numbers, to produce ciphertext messages. The sender transmits the ciphertext messages. A receiver receives the ciphertext messages and, for each received ciphertext message, performs the following operations. The receiver decrypts the given ciphertext message to recover plaintext and a candidate sequence number from the message. The receiver determines if the candidate sequence number is in any one of multiple acceptable sequence number windows having respective sequence number ranges that are based on at least one of a highest sequence number previously accepted and a last sequence number that was previously rejected, as established based on processing of previously received ciphertext messages.
Abstract:
A method of providing anti-replay protection, authentication, and encryption with minimal data overhead is provided. A sender uses an arbitrary-length pseudorandom permutation to encrypt messages that include plaintext and successively increasing sequence numbers, to produce ciphertext messages. The sender transmits the ciphertext messages. A receiver receives the ciphertext messages and, for each received ciphertext message, performs the following operations. The receiver decrypts the given ciphertext message to recover plaintext and a candidate sequence number from the message. The receiver determines if the candidate sequence number is in any one of multiple acceptable sequence number windows having respective sequence number ranges that are based on at least one of a highest sequence number previously accepted and a last sequence number that was previously rejected, as established based on processing of previously received ciphertext messages.
Abstract:
In one embodiment, a device in a network receives an attack mitigation request regarding traffic in the network. The device causes an assessment of the traffic, in response to the attack mitigation request. The device determines that an attack detector associated with the attack mitigation request incorrectly assessed the traffic, based on the assessment of the traffic. The device causes an update to an attack detection model of the attack detector, in response to determining that the attack detector incorrectly assessed the traffic.
Abstract:
In one embodiment, a traffic inspection service executed by an intermediary device obtains, from a monitoring agent executed by an endpoint device, keying information for an encrypted traffic session between the endpoint device and a remote entity. The traffic inspection service provides a notification to the monitoring agent that acknowledges receipt of the keying information. The traffic inspection service uses the keying information to decrypt encrypted traffic from the encrypted traffic session. The traffic inspection service applies a policy to the encrypted traffic session between the endpoint device and the remote entity, based on the decrypted traffic from the session.