Abstract: A system and a method for detecting anomalous attacks in Internet network flow operate by counting a number of Internet traffic messages that are detected as anomalous attacks to provide a count; computing a running average of the number of messages that are detected as anomalous attacks; and comparing the count to the running average to provide an anomalous attack alarm if the count is greater than a multiple of the running average. The attacks can include at least one of spoofing attacks or denial of service attacks. A computer readable storage medium stores instructions of a computer program, which when executed by a computer system, results in performance of steps of the method.

Abstract: A solution to the problem of automated policy generation for mobile ad hoc networks includes an optimization-based, utility-driven approach aimed at generating optimal policies with respect to the given network objectives. The combination of optimization heuristics and network simulation is used to solve the problem. Specifically, the problem of automated generation of network management policies based on available network plans and related information is solved by converting the policy generation into the following optimization problem: given network information and objectives as input, generate optimal policies as output. The optimization process is guided by a utility function based on performance evaluation criteria reflecting the network objectives.

Abstract: A system and a method for detecting anomalous attacks in Internet network flow operate by counting a number of Internet traffic messages that are detected as anomalous attacks to provide a count; computing a running average of the number of messages that are detected as anomalous attacks; and comparing the count to the running average to provide an anomalous attack alarm if the count is greater than a multiple of the running average. The attacks can include at least one of spoofing attacks or denial of service attacks. A computer readable storage medium stores instructions of a computer program, which when executed by a computer system, results in performance of steps of the method.

Abstract: A solution to the problem of automated policy generation for mobile ad hoc networks includes an optimization-based, utility-driven approach aimed at generating optimal policies with respect to the given network objectives. The combination of optimization heuristics and network simulation is used to solve the problem. Specifically, the problem of automated generation of network management policies based on available network plans and related information is solved by converting the policy generation into the following optimization problem: given network information and objectives as input, generate optimal policies as output. The optimization process is guided by a utility function based on performance evaluation criteria reflecting the network objectives.

Abstract: A solution to the problem of automated policy generation for mobile ad hoc networks includes an optimization-based, utility-driven approach aimed at generating optimal policies with respect to the given network objectives. The combination of optimization heuristics and network simulation is used to solve the problem. Specifically, the problem of automated generation of network management policies based on available network plans and related information is solved by converting the policy generation into the following optimization problem: given network information and objectives as input, generate optimal policies as output. The optimization process is guided by a utility function based on performance evaluation criteria reflecting the network objectives.

Abstract: A solution to the problem of automated policy generation for mobile ad hoc networks includes an optimization-based, utility-driven approach aimed at generating optimal policies with respect to the given network objectives. The combination of optimization heuristics and network simulation is used to solve the problem. Specifically, the problem of automated generation of network management policies based on available network plans and related information is solved by converting the policy generation into the following optimization problem: given network information and objectives as input, generate optimal policies as output. The optimization process is guided by a utility function based on performance evaluation criteria reflecting the network objectives.