Abstract: Matching an internet service with an IP host address to attribute network traffic to the internet service by mapping one or more server names to an internet service by a network device by detecting a DNS Response to a DNS Query. Inspect the DNS Response to determine an association of a service consumer's IP address with an internet service's server IP address relating to a certain internet service to maintain an array of indexed entries having an association of the service consumer's IP address with an internet service's server IP address relating to a certain internet service for a certain length of time using a probabilistic data structure for the indexed entries.

Abstract: Matching an internet service with an IP host address to attribute network traffic to the internet service by mapping one or more server names to an internet service by a network device by detecting a DNS Response to a DNS Query. Inspect the DNS Response to determine an association of a service consumer's IP address with an internet service's server IP address relating to a certain internet service to maintain an array of indexed entries having an association of the service consumer's IP address with an internet service's server IP address relating to a certain internet service for a certain length of time using a probabilistic data structure for the indexed entries.

Abstract: A method includes receiving summary messages summarizing respective aggregated traffic metadata packets output from the at least one traffic management device and an engine. Each summary message identifies an origination pair having a traffic management device and an aggregation engine and a sequence number. The method further includes tracking per subinterval of a series of sub-intervals, highest and lowest sequence numbers and a count of summary messages received for each unique origination pair from the beginning of the subinterval. The method further includes accumulating, per interval, accumulated highest and lowest sequence numbers and an accumulated count of summary messages for each unique origination pair from the beginning of the interval and for all previous subintervals for tracking dropped aggregated traffic metadata packets for the interval.

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 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 includes receiving summary messages summarizing respective aggregated traffic metadata packets output from the at least one traffic management device and an engine. Each summary message identifies an origination pair having a traffic management device and an aggregation engine and a sequence number. The method further includes tracking per subinterval of a series of sub-intervals, highest and lowest sequence numbers and a count of summary messages received for each unique origination pair from the beginning of the subinterval. The method further includes accumulating, per interval, accumulated highest and lowest sequence numbers and an accumulated count of summary messages for each unique origination pair from the beginning of the interval and for all previous subintervals for tracking dropped aggregated traffic metadata packets for the interval.

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 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.