Title

Intrusion detection and high-speed packet classification using memristor crossbars

Date of Award

2015

Degree Name

M.S. in Electrical Engineering

Department

Department of Electrical and Computer Engineering

Advisor/Chair

Advisor: Tarek Taha

Abstract

Intrusion Detection Systems (IDS) are intelligent specialized systems designed to interpret intrusion attempts from incoming network traffic. IDSs aim at minimizing the risk of accessing unauthorized data and potential vulnerabilities in critical systems by examining every packet entering a system. Packet inspection and Pattern matchings are often computationally intensive processes and that are the most power hungry functionalities in network intrusion detection systems. This thesis presents a high throughput, low latency and low power memristor crossbar architecture for packet header and payload matching that could be used for high-speed packet classification and malware detection. The memristor crossbar systems can perform intrusion detection through a brute force approach for static contents/signatures and a state machine approach for regular expressions. A large portion of the work completed in this thesis has been published in [1-2].

Keywords

Intrusion detection systems (Computer security), Packet switching (Data transmission), Memristors, Computer Engineering, Electrical Engineering, Intrusion Detection, Memristor Crossbars, High Speed Packet Classification, Low Power, Network Security, SNORT, String Matching, Regular Expression Matching

Rights Statement

Copyright 2015, author

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