Abstract: A method of detecting patterns in network traffic is provided. The method includes receiving packets of network traffic, performing a frequency analysis per field of the packets as a function of frequency of the occurrence of the same data in the corresponding field, and selecting top values which are values associated with each field of the set of fields that satisfy a criterion as having occurred most frequently in the packets as a function of a result of the frequency analysis.

Abstract: A computer implemented method and system for protecting against denial of service attacks by detecting changes in a preferred set of hierarchically-structured items in a network data stream in which a set of network destination prefixes is identified that account for a user specified target of the attack traffic. Changes in the attack traffic profile are detected and new sets of network destination prefixes are generated when the attack has shifted by a predetermined threshold. sets of identified destination prefixes are then translated into route announcements to divert attack traffic to mitigation devices.

Abstract: A computer-implemented method of grouping network traffic metadata includes, based on a selected dimension of the network traffic metadata received from a network router, obtaining a statistic about a flow of network traffic metadata received over an interval for each instance of multiple instances of the dimension. The method further includes distributing the network traffic metadata into a plurality of groups for network traffic metadata from the smallest possible number of instances of the selected dimension to be distributed to each group, with the flow of network traffic metadata distributed optimally for a criteria regarding the statistic amongst the plurality of groups for minimizing cardinality of each group of the plurality of groups with respect to unselected dimensions of the network traffic metadata and providing each group to a columnar database for storage of the network traffic metadata distributed into each group in a different partition of the columnar database.

Abstract: A computer method and system for detecting and preventing over-mitigation of network attacks (e.g., Denial of Service (DoS) attacks) upon a protected computer network by a network security element. A determination is made as to whether captured data packets transmitting to a protected network are associated with legitimate network traffic (e.g., non-attack traffic). A matching pattern of the captured data packets determined legitimate network traffic is generated and test traffic packets utilizing the matching pattern of the captured data packets are then generated. The generated test traffic packets are then injected into the network security element/filter. A determination is then made as to whether if the injected test traffic packets are treated as a malicious traffic (e.g., a DoS attack), or as legitimate traffic, by the network security filter. If treated as malicious traffic (e.g.

Abstract: A method and system for aggregating into a unique aggregated group (AG), protection groups (PGs) that are possible classifications with at least a threshold probability for a same unique combination of IP addresses. The PGs and the unique combination of IP addresses are included in the AG. Each of the IP addresses of the unique combination of IP addresses have respective associated probabilities for each PG included in the AG. The method further includes selecting and providing for display AGs based on the probabilities associated with the respective IP addresses included in the AGs, and providing for display at least one interactive graphical element in association with each AG selected for display. User activation of one of the interactive graphical element accepts assignment of one or more selected IP addresses included in the AG to a selected one of the one or more PGs included in the AG.

Abstract: A method and system for automatically classifying protected devices of a protected network to protection groups providing customized protection. The method includes accessing network flow information that includes network statistics processed from observed data obtained by packet interception devices, accessing at least one model that was trained using machine learning and a training data set of the network flow information to classify protected devices having addresses that correspond to destination addresses associated with the training data set to respective protection groups as a function of the network statistics that correspond to the training data set, and classifying a protected device that has an address that corresponds to a destination address associated with a portion of the network flow information to at least one of the protection groups using the at least one model and machine learning and as a function of the network statistics that correspond to the portion of the network flow information.

Abstract: A computer implemented method and system for identifying a preferred set of hierarchically structured items in streaming data for analyzing Netflow data to identify those network destinations that are currently the target of a DDoS attack and to automatically select a set of network prefixes such that diversion routes for the prefixes are sent to the routers to divert attack traffic to TMS devices, The method includes searching sets of Hierarchical Heavy Hitters wherein each set corresponds to a different fraction of a total volume of network traffic and scoring each set according to an arbitrary scoring function. A certain set is selected and scored with a ‘good’ score and a member of the ‘good’ scored set is ranked in accordance with an arbitrary ranking function. A subset of the ‘good’ scored set is selected such that the volume associated with the subset is in close proximity to a user-specified total whereby the selected subset becomes a set of recommended prefixes.

Abstract: A method and system for detecting impersonated network traffic by a protected computing device and a network protection system. The method includes the computing device receiving installation of a browser application, the browser application configured to generate requests to communicate with other computers via the World Wide Web and receiving a configuration for the browser application. The browser application is configured to obtain a short-lived password (SLP) in coordination with generating a request and insert the short-lived password into the generated request before transmitting the request. The SLP is synchronized with an expected value generated by the network protection system. The transmitted request is passed to the network protection system and treated as legitimate network traffic by the network protection system only if the network protection system detects and verifies the SLP.

Abstract: A method of detecting patterns for automated filtering of data is provided. The method includes receiving network traffic including bad traffic and good traffic, wherein an attack is known to be applied to the bad traffic, and the good traffic is known to be free of an applied attack. Processing the good and bad traffic includes generating, for each unique packet, each potential unique combination of the packet's fields, storing each combination with associated bad match and good match counters, and incrementing a combination's respective good and bad match counters for each occurrence it matches one of the packets of the respective good and bad traffic. The combinations are sorted based on the good match counter associated with each combination, a number of fields in each combination, and the bad match counter associated with each combination. One or more combination is selected based on results of the sorting for provision to a network traffic filtering component.

Abstract: A system and computer-implemented method to detect particular Domain Name System (DNS) misuse, wherein the method includes obtaining monitored network data. The monitored network data includes respective instances of request traffic. The request traffic is associated with DNS requests that request resolution of a name that belongs to at least one identified domain. Each DNS request is sent from a source address of one or more stub resolver; the source address of the stub resolver may be spoofed. Each instance of request traffic includes the source address, the name for which DNS resolution is requested to be resolved, and the at least one identified domain associated with a corresponding DNS request. The method further includes tracking over time, using a probabilistic algorithm, an approximation of a first cardinality of names belonging to a selected domain of the at least one identified domain included in the instances of request traffic.

Abstract: A computer method and system to determine one or more sub-groups of protected network servers for receiving common network filter settings for mitigating Denial of Services (Dos) attacks. Network traffic associated with the plurality of network servers is captured and collated for each of the plurality of network servers. The collated network traffic is then analyzed to determine a profile of one or more network services provided by each of the plurality of network servers. Each of the plurality of network servers is then tagged with one or more network services determined provided by each network server based upon analysis of the collated network traffic. Metadata is then determined from the collated network traffic that is associated with each of the plurality of network servers.

Abstract: A method, system, and computer-implemented method to manage threats to a protected network having a plurality of internal production systems is provided. The method includes monitoring network traffic from the plurality of internal production systems of a protected network for domain names. For each internal production system, a first collection of each unique domain name that is output by the internal production system is determined over the course of a long time interval. For each internal production system, a second collection of each unique domain name that is output by the internal production system is determined over the course of a short time interval. Domain names in the first and second collections associated with the plurality of internal production systems are compared to determine suspicious domain names that meet a predetermined condition. A request is output to treat the suspicious the suspicious domain names as being suspicious.

Abstract: A method and system are provided for monitoring a protected network. The method includes, in a scoring phase, receiving a learned model having clusters of learning requests of learning network traffic observed during non-strain operation of the protected network, wherein each cluster has an associated characteristic learning response time. The method further includes receiving a score request to score a network service request of the network traffic, classifying the network service request with one of the clusters by comparing fields of the network service request to fields used for clustering the learning requests with the cluster, calculating a score based on the characteristic learning response times generated for the learned cluster to which the network service request is classified, and adjusting supportive handling of the network service request based on the score.

Abstract: The method and system are provided for monitoring a protected network for strain. The method includes receiving a learned model having clusters of learning requests of learning network traffic observed during non-strain operation of the protected network, observing network traffic, classifying each of the traffic requests with one of the clusters based on fields of the traffic request and fields used for clustering the learning requests, determining an analysis response time for respective traffic requests associated with the classified traffic requests, determining an analysis response time characteristic per cluster based on an analysis response time associated with the respective classified traffic requests classified with the cluster, determining a difference per cluster between the analysis response time and the learning response times associated with the cluster, and notifying a mitigation device when the difference determined for enough of the clusters exceeds a predetermined threshold.

Abstract: A system and computer-implemented method of monitoring a network is provided. The method includes receiving a packet of network traffic, wherein the packet has an associated source and destination address pair, where this pair constitutes a connection pair. The method further includes comparing the packet to a plurality of patterns and/or compare a source or destination address of the packet to known malicious addresses, and upon determining that the packet matches a pattern of the plurality of patterns or the source or destination address of the packet matches a known malicious address. The method further includes deploying a honeypot in a container for the pattern matching the packet, if not yet deployed, and forwarding all network traffic for the connection pair to the honeypot.

Abstract: A computer-implemented method of grouping network traffic metadata includes, based on a selected dimension of the network traffic metadata received from a network router, obtaining a statistic about a flow of network traffic metadata received over an interval for each instance of multiple instances of the dimension. The method further includes distributing the network traffic metadata into a plurality of groups for network traffic metadata from the smallest possible number of instances of the selected dimension to be distributed to each group, with the flow of network traffic metadata distributed optimally for a criteria regarding the statistic amongst the plurality of groups for minimizing cardinality of each group of the plurality of groups with respect to unselected dimensions of the network traffic metadata and providing each group to a columnar database for storage of the network traffic metadata distributed into each group in a different partition of the columnar database.

Abstract: A logical expression engine and computer-implemented method for optimizing evaluation of a logical expression is provided. The method includes receiving an original logical expression to be applied by a computer program for processing input information, the original logical expression having at least one operator and a subexpression disposed on each side of a related operator of the at least one related operator. The method further includes receiving statistics accumulated about how the computer program applies the subexpressions of the original logical expression for processing the input information received by the computer program, using the accumulated statistics to optimize the order in which the subexpressions would be applied by the computer program, and outputting for application by the computer program an optimized logical expression having the subexpressions ordered in accordance with the optimized order.

Abstract: A computer method and system for detecting denial of service network attacks by analyzing intercepted data packets on a network to determine a user account associated with a preselected target host sought to be accessed via a user account login attempt. Determine if the login attempt exceeds a predetermined login value for previous failed login attempts associated with the user account sought to be accessed. Determine a geographic location associated with the login attempt if determined the login attempt exceeded the predetermined login value. Determine if a prior login attempt to the user account sought to be accessed was successful from the determined geographic location. Authenticate the login attempt to the user account sought to be accessed in the event it was determined a prior successful login attempt was made to the user account from the determined geographic location or no prior login attempts originated from the determined geographic location.

Abstract: A computer method and system for detecting a Denial of Service (DoS) attack by detecting changes in recent cardinality of a network traffic flow. Packet traffic flows are received from external device (networks), and a cardinality estimation is then performed on a received packet traffic flow. A series of cardinalities is maintained for prior packet traffic flows. Changes in cardinalities associated with prior packet traffic flows are detected when compared to cardinalities of a current packet traffic flow. An alert condition for the network traffic flow is generated regarding a suspected DoS attack based upon the detected changes in cardinalities regarding comparison of the cardinalities associated with prior packet traffic flows compared to cardinalities of a current packet traffic flow.

Abstract: Detecting a Denial of Service (DoS) attack in a network by a network edge router device whereby network traffic flows from the edge router to a core router in the network. Storing DoS attack traffic information in storage associated with the edge router which receives network traffic. Determining in the edge router if a portion of the received network traffic matches at least a portion of the stored DoS attack information. Determining in the edge router an alert condition exists if a portion of the received network traffic is determined to match at least a portion of the stored DoS attack information. Send an alert signal from the edge router to an attack mitigation device if it is determined an alert condition exists causing the attack mitigation device to transition to a mitigation state for mitigating effects of a DoS attack upon the network.