Abstract:
Endpoint security systems and methods include a distance estimation module configured to calculate a travel distance between a source Internet Protocol (IP) address and an IP address for a target network endpoint system from a received packet received by the target network endpoint system based on time-to-live (TTL) information from the received packet. A machine learning model is configured to estimate an expected travel distance between the source IP address and the target network endpoint system IP address based on a sparse set of known source/target distances. A spoof detection module is configured to determine that the received packet has a spoofed source IP address based on a comparison between the calculated travel distance and the expected travel distance. A security module is configured to perform a security action at the target network endpoint system responsive to the determination that the received packet has a spoofed source IP address.
Abstract:
Methods and systems for anomaly detection and correction include generating original signature matrices that represent a state of a system of multiple time series. The original signature matrices are encoded using convolutional neural networks. Temporal patterns in the encoded signature matrices are modeled using convolutional long-short term memory neural networks for each respective convolutional neural network. The modeled signature matrices using deconvolutional neural networks. An occurrence of an anomaly is determined using a loss function based on a difference between the decoded signature matrices and the original signature matrices. A corrective action is performed responsive to the determination of the occurrence of the anomaly.
Abstract:
Endpoint security systems and methods include a distance estimation module configured to calculate a travel distance between a source Internet Protocol (IP) address and an IP address for a target network endpoint system from a received packet received by a network gateway system based on time-to-live (TTL) information from the received packet. A machine learning model is configured to estimate an expected travel distance between the source IP address and the target network endpoint system IP address based on a sparse set of known source/target distances. A spoof detection module is configured to determine that the received packet has a spoofed source IP address based on a comparison between the calculated travel distance and the expected travel distance. A security module is configured to perform a security action at the network gateway system responsive to the determination that the received packet has a spoofed source IP address.
Abstract:
In a software defined network having switches including first and last switches and intermediate switches, wherein a default routing path exists between the first and last switches, a system and method are provided for computing path latency. The method includes inserting a respective monitoring rule(s) in each switch, mandating for each switch, forwarding a received rule matching packet to a next switch, and further mandating for the first switch and the last switch, sending a PacketIn message to a controller. The method includes inserting, in each switch, a respective monitoring probe(s) matching the respective monitoring rule(s) in a same switch to initiate mandates specified by the respective monitoring rule(s) in the same switch responsive to an arrival of the packet thereat. The method includes time-stamping the PacketIn messages to generate PacketIn timestamps, aggregating the PacketIn timestamps, and estimating the path latency from an aggregation of PacketIn timestamps.
Abstract:
Methods and systems for network management include performing path regression to determine an end-to-end path across physical links for each data flow in a network. A per-flow utilization of each physical link in the network is estimated based on the determined end-to-end paths. A management action is performed in the network based on the estimated per-flow utilization.
Abstract:
A computer implemented method for network monitoring includes providing network packet event characterization and analysis for network monitoring that includes supporting summarization and characterization of network packet traces collected across multiple processing elements of different types in a virtual network, including a trace slicing to organize individual packet events into path-based trace slices, a trace characterization to extract at least 2 types of feature matrix describing those trace slices, and a trace analysis to cluster, rank and query packet traces based on metrics of the feature matrix.
Abstract:
Systems and methods for controlling legacy switch routing in one or more hybrid networks of interconnected computers and switches, including generating a network underlay for the one or more hybrid networks by generating a minimum spanning tree (MST) and a forwarding graph (FWG) over a physical network topology of the one or more hybrid networks, determining an optimal path between hosts on the FWG by optimizing an initial path with a minimum cost mapping, and adjusting the initial path to enforce the optimal path by generating and installing special packets in one or more programmable switches to trigger installation of forwarding rules for one or more legacy switches.
Abstract:
Systems and methods for controlling legacy switch routing in one or more hybrid networks of interconnected computers and switches, including generating a network underlay for the one or more hybrid networks by generating a minimum spanning tree (MST) and a forwarding graph (FWG) over a physical network topology of the one or more hybrid networks, determining an optimal path between hosts on the FWG by optimizing an initial path with a minimum cost mapping, and adjusting the initial path to enforce the optimal path by generating and installing special packets in one or more programmable switches to trigger installation of forwarding rules for one or more legacy switches.
Abstract:
A computer implemented method for network monitoring includes providing network packet event characterization and analysis for network monitoring that includes supporting summarization and characterization of network packet traces collected across multiple processing elements of different types in a virtual network, including a trace slicing to organize individual packet events into path-based trace slices, a trace characterization to extract at least 2 types of feature matrix describing those trace slices, and a trace analysis to cluster, rank and query packet traces based on metrics of the feature matrix.
Abstract:
Method and systems for controlling a hybrid network having software-defined network (SDN) switches and legacy switches include initializing a hybrid network topology by retrieving information on a physical and virtual infrastructure of the hybrid network; generating a path between two nodes on the hybrid network based on the physical and virtual infrastructure of the hybrid network; generating a virtual local area network by issuing remote procedure call instructions to legacy switches in accordance with a network configuration request; and generating an SDN network slice by issuing SDN commands to SDN switches in accordance with the network configuration request.