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Intrusion Detection and High-Speed Packet Classification Using Memristor Crossbars

Bontupalli, Venkataramesh
http://orcid.org/0000-0002-3216-4347
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1449623641

Abstract Details

2015, Master of Science (M.S.), University of Dayton, Electrical Engineering.
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].
Tarek Taha, Dr (Advisor)
Eric Balster, Dr (Committee Member)
Vamsy Chodavarapu, Dr (Committee Member)
73 p.
Computer Engineering; Electrical Engineering
Intrusion Detection; Memristor Crossbars; High Speed Packet Classification; Low Power; Network Security; SNORT; String Matching; Regular Expression Matching

Recommended Citations

Citations

  • Bontupalli, V. (2015). Intrusion Detection and High-Speed Packet Classification Using Memristor Crossbars [Master's thesis, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1449623641

    APA Style (7th edition)

  • Bontupalli, Venkataramesh. Intrusion Detection and High-Speed Packet Classification Using Memristor Crossbars. 2015. University of Dayton, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1449623641.

    MLA Style (8th edition)

  • Bontupalli, Venkataramesh. "Intrusion Detection and High-Speed Packet Classification Using Memristor Crossbars." Master's thesis, University of Dayton, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1449623641

    Chicago Manual of Style (17th edition)

dayton1449623641
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© 2015, all rights reserved.
This open access ETD is published by University of Dayton and OhioLINK.