Presenter(s)
Venkataramesh Bontupalli
Files
Download Project (473 KB)
Description
Intrusion Detection System (IDS) is an intelligent specialized system designed to interpret the intrusion attempts in incoming network traffic. IDS aims at minimizing the risk of accessing the unauthorized data and potential vulnerabilities of critical systems by the examining the every packet entering into the system. Deep Packet inspection and Pattern matching are computationally intensive processes and most power hungry functionalities in network intrusion detection systems. In particular, every incoming packet is well screened by string matching with previously known malicious signatures/contents essentially known as attacks or intrusions. In particular, nearly 70 % of the execution time and power is utilized against matching the malicious contents against all the incoming packets. Indeed, the heart of every IDS is the detection process itself hence our key focus and efforts are towards developing a memristor crossbar based low power intrusion detection system that would reduce the execution time and power consumption due to its high density grid and massive parallelism. We propose a brute force string matching algorithm implementation on a low power memristor based cross bar array giving rise to detection accuracy of 100% and 0% false positive consuming 0.013mW/signature. As it turns out, memristor cross bar designed, trigger only if there is an exact match between the stored and incoming pattern extending its applications towards text processing, speech processing, computational biology, etc. besides intrusion detection.
Publication Date
4-9-2015
Project Designation
Graduate Research
Primary Advisor
Tarek M. Taha
Primary Advisor's Department
Electrical and Computer Engineering
Keywords
Stander Symposium project
Disciplines
Arts and Humanities | Business | Education | Engineering | Life Sciences | Medicine and Health Sciences | Physical Sciences and Mathematics | Social and Behavioral Sciences
Recommended Citation
"Power Efficient Circuits for Intrusion Detection using Memristor Crossbars" (2015). Stander Symposium Projects. 644.
https://ecommons.udayton.edu/stander_posters/644
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