Other

Tt Government Solutions, Inc.

Tti Inventions D LLC

Nytell Software LLC

Balakrishnan Dasarathy

Arnold Leslie Neidhardt

Shrirang Gadgil

Clifford Behrens

Ravichander Vaidyanathan

Hiralal Agrawal

Brian A Coan

D Scott Alexander

Mark W Garrett

A computer-enabled method of learning the behavior of a program. A processor can execute a target program during a learning interval while varying a plurality of stimuli provided to the target program so as to produce a multiplicity of different sequences of events which differ in combinations of types of events in respective sequences, orders in which the types of events occur in respective sequences, or in the combinations and in the orders in which the types of events occur. The multiplicity of event sequences can be recorded, and a second program can be executed by a processor to: determine a plurality of clusters based on similarities between the event sequences in their entirety; and determine a plurality of signatures corresponding to the plurality of clusters. Each signature can be the longest common subsequence of all sequences in the respective cluster and thus representative of the cluster. In such method, each of the plurality of signatures can be a benchmark representative of acceptable behavior of the target program.

Learning program behavior for anomaly detection

A method for controlling network access comprises receiving a request to allow a communication flow over a network and temporarily allowing the communication flow over the network before a response to the request is transmitted. Further, the availability of one or more network resources may be determined and compared with resources required for the requested communication flow. Priority of the communication flow may also be determined, and the temporarily allowed communication flow may be responded to based on the available resources, the requested resources, and the priority.

Non-blocking admission control

The present invention relates to on-line admission-control decisions. Specifically, the invention concerns general delay bounds for both deterministic and statistical cases for Differentiated Services (DiffServ) networks. More specifically, a detailed method of calculation in each case is followed by simpler methods of calculation that are more appropriate for on-line admission-control decisions. Relatively involved occupancy bound calculations for various service classes take place only at the time of network configuration or reconfiguration. At the time of admission control only simple occupancy threshold compliance calculations need to be performed. Concrete illustrations are provided for deriving bounds for the EF and AF classes provided by DiffServ. These results are applicable to both layer-3 networks that support DiffServ and layer-2 networks that support the more restricted class of service functions.

Calculations for admission control

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Bridgewater, NJ, United States of America

Balakrishnan Dasarathy