Abstract:
Systems and methods for an automotive security gateway include an in-gateway security system that monitors local host behaviors in vehicle devices to identify anomalous local host behaviors using a blueprint model trained to recognize secure local host behaviors. An out-of-gateway security system monitors network traffic across remote hosts, local devices, hotspot network, and in-car network to identify anomalous behaviors using deep packet inspection to inspect packets of the network. A threat mitigation system issues threat mitigation instructions corresponding to the identified anomalous local host behaviors and the anomalous remote host behaviors to secure the vehicle devices by removing the identified anomalous local host behaviors and the anomalous remote host behaviors. Automotive security gateway services and vehicle electronic control units operate the vehicle devices according to the threat mitigation instructions.
Abstract:
A computer-implemented method for analyzing operations of privilege changes is presented. The computer-implemented method includes inputting a program and performing source code analysis on the program by generating a privilege control flow graph (PCFG), generating a privilege data flow graph (PDFG), and generating a privilege call context graph (PCCG). The computer-implemented method further includes, based on the source code analysis results, instrumenting the program to perform inspections on execution states at privilege change operations, and performing runtime inspection and anomaly prevention.
Abstract:
Systems and methods for identifying similarities in program binaries, including extracting program binary features from one or more input program binaries to generate corresponding hybrid features. The hybrid features include a reference feature, a resource feature, an abstract control flow feature, and a structural feature. Combinations of a plurality of pairs of binaries are generated from the extracted hybrid features, and a similarity score is determined for each of the pairs of binaries. A hybrid difference score is generated based on the similarity score for each of the binaries combined with input hybrid feature parameters. A likelihood of malware in the input program is identified based on the hybrid difference score.
Abstract:
Systems and methods for an automotive security gateway include an in-gateway security system that monitors local host behaviors in vehicle devices to identify anomalous local host behaviors using a blueprint model trained to recognize secure local host behaviors. An out-of-gateway security system monitors network traffic across remote hosts, local devices, hotspot network, and in-car network to identify anomalous behaviors using deep packet inspection to inspect packets of the network. A threat mitigation system issues threat mitigation instructions corresponding to the identified anomalous local host behaviors and the anomalous remote host behaviors to secure the vehicle devices by removing the identified anomalous local host behaviors and the anomalous remote host behaviors. Automotive security gateway services and vehicle electronic control units operate the vehicle devices according to the threat mitigation instructions.
Abstract:
Methods and systems for profiling requests include generating request units based on collected kernel events that include complete request units and half-open request units. The generated request units are sequenced based on a causality relationship set that describes causality relationships between kernel events.
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:
Methods and systems for profiling requests include generating request units based on collected kernel events that include complete request units and half-open request units. The generated request units are sequenced based on a causality relationship set that describes causality relationships between kernel events.
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.
Abstract:
A system and method for profiling a request in a service system with kernel events including a pre-processing module configured to obtain kernel event traces from the service system and determine starting and ending communication pairs of a request path for a request. A learning module is configured to learn pairwise relationships between the starting and ending communication pairs of training traces of sequential requests. A generation module is configured to generate communication paths for the request path from the starting and ending communication pairs of testing traces of concurrent requests using a heuristic procedure that is guided by the learned pairwise relationships and generate the request path for the request from the communication paths. The system and method precisely determine request paths for applications in a distributed system from kernel event traces even when there are numerous concurrent requests.
Abstract:
A computer implemented method provides efficient monitoring and analysis of a program's memory objects in the operation stage. The invention can visualize and analyze a monitored program's data status with improved semantic information without requiring source code at runtime. The invention can provide higher quality of system management, performance debugging, and root-cause error analysis of enterprise software in the production stage.