Telcordia Technologies, Inc.

Vencore Labs, Inc.

Perspecta Labs Inc.

Kddi Corporation

Tt Government Solutions, Inc.

Aditya Naidu

Stanley Pietrowicz

Abhrajit Ghosh

Ayumu Kubota

Rajesh Rasik Talpade

Jason Youzwak

Yukiko Sawaya

Michael M Hylkema

Paul D Martin

Akira Yamada

Yibei Ling

Yutaka Miyake

Harshad Tanna

Ravichander Vaidyanathan

Yitzchak Gottlieb

Federico Jose Garcia

Sabine Winchell

A method, computer system, and computer program product that generates a whitelist for each subject device in a field area network (FAN). The whitelist includes one or more whitelist entries corresponding to one or more peer devices in the same FAN communicating with the subject device. Each whitelist entry includes one or more attribute values expected in respective traffic between the subject device and each peer device that is represented by a respective whitelist entry. The traffic in the FAN is monitored at one or more points of the FAN for anomaly by use of the whitelist.

Traffic anomaly detection for IoT devices in field area network

A computer program product, computer system, and method for performing traffic analysis on a wireless mesh network, includes intercepting a stream of real-time wireless from field probes on the wireless mesh network, wherein the stream comprises non-standard protocol elements and encrypted traffic, creating an ad hoc network parallel to the wireless mesh network, obtaining, from the ad hoc network, the intercepted stream (the analyzing is performed parallel to traffic flow on the wireless mesh network), pre-processing a portion of the intercepted stream the data, where the pre-processing comprises descrambling and processing headers in the stream to differentiate the packets in the stream and create a combined output stream, obtaining the combined output stream and creating indicators by selecting an analysis operator to apply to one or more dissected fields extracted from the output stream, analyzing the packets in the combined output stream utilizing the indicators, and obtaining results from the indicators and reporting, the results from the indicators.

System and method for network traffic profiling and visualization

A computer system, computer program product and method of performing traffic analysis on a communications network includes time stamped packets and related metadata from an intercepted steam of real-time traffic on a backhaul network distinct from the communications network, pre-processing the intercepted stream, including separating a portion of the intercepted stream into dissected fields, creating indicators by selecting an analysis operator to apply to one or more of the dissected fields in a logical expression, analyzing the dissected fields in the output streams utilizing the indicators, and obtaining results from the indicators.

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.

System and method for real-time reporting of anomalous internet protocol attacks

A method, an apparatus and a program for detecting spoofed Internet Protocol (IP) traffic directed to a network having a plurality of autonomous systems (AS) is provided. The method comprises receiving an incoming packet through an AS, the incoming packet containing a source IP address and a destination IP address, acquiring a corresponding source and destination IP address prefixes, converting the corresponding source and destination IP address prefixes into a source AS number and a destination AS number, determining if the incoming packet arrived from an unexpected source based upon the corresponding destination IP address prefix and the converted source and destination AS number using an unexpected pair tuple table generated from network routing information and generating an alert indicating that the incoming packet is not allowed to enter the network.

Method, apparatus and program for detecting spoofed network traffic

Aspects of the invention pertain to analyzing and modifying access control lists that are used in computer networks. Access control lists may have many individual entries that indicate whether information can be passed between certain devices in a computer network. The access control lists may include redundant or conflicting entries. An aspect of the invention converts an order-dependent control list into an order-free equivalent. Redundant entries are identified and removed without adversely affecting the access control list. Redundancy may be identified by evaluating the volume contraction ratio, which is the ratio of the volume of spin-off entries to specific original entry in the access control list. This ratio reflects the extent of order-dependent impact on that entry in a given access control list.

Redundancy detection and resolution and partial order dependency quantification in access control lists

Aspects of the invention pertain to user session management in load balanced clusters. Multiple application servers communicate with a central data server to ensure there is a single session per user ID. The central data server maintains a user session index and a parameter table. Each time a network access is attempted using a given user ID, a load balancer assigns the session to one of the application servers. The assigned application server queries the central data server to determine whether a session status for the user's login ID is inactive or active. If inactive, a new, unique value is assigned as the session number. If active, the session number is evaluated to determine whether multiple sessions exist. In this case, one of the sessions is terminated to ensure a single session per user ID. Preferably, the terminated session is the earlier session.

Systems and methods for single session management in load balanced application server clusters

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Edison, NJ, United States of America

Aditya Naidu