Systems and methods for learning-based high-performance, energy-efficient, and secure on-chip communication design framework
AssigneeThe George Washington University
InventorsKe WANG, Hao ZHENG, Ahmed LOURI
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Abstract
Systems and methods are disclosed for improving on-chip security, while minimizes the latency and cost of security techniques to improve system-level performance and power simultaneously. The framework uses machine learning algorithms, such as an artificial neural network (ANN), for runtime attack detection with higher accuracy. Further, a learning-based attack mitigation method using deep reinforcement learning is disclosed, where the method may be used to isolate the malicious components and to optimize network latency and energy-efficiency.
Claims20
A router comprising:
- an input port;
- an output port;
- a dynamic error detection and correction circuit;
- an artificial neural network module;
- and
- a controller, wherein the controller instructs the artificial neural network module to detect malicious circuit modifications in a router.
A system comprising:
- one or more processing cores;
- and
- one or more routers, wherein each of the routers is comprised of an input port, and output port, a dynamic error detection and correction circuit, a bypass channel, an artificial neural network module, and a controller;
- wherein one or more of the controllers instructs the artificial neural network module to detect malicious circuit modifications in the one or more routers.
A method for network security comprising:
- receiving one or more data packets from an input port at the artificial neural network module of one or more routers, wherein each router is comprised of a controller and wherein the artificial neural network is trained to detect malicious circuit modifications;
- analyzing runtime attributes of the data packets at the artificial neural network module;
- identifying malicious circuit modifications from the runtime attributes of the data packets;
- and
- transmitting an instruction from the controller to use the bypass channel to isolate routers in which the malicious circuit modifications are detected.
Dependencies are inferred from the claim text.