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Title: Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor

Abstract

Resiliency and security in critical infrastructure control systems in the modern world of cyber terrorism constitute a relevant concern. Developing a network security system specifically tailored to the requirements of such critical assets is of a primary importance. This paper proposes a novel learning algorithm for anomaly based network security cyber sensor together with its hardware implementation. The presented learning algorithm constructs a fuzzy logic rule based model of normal network behavior. Individual fuzzy rules are extracted directly from the stream of incoming packets using an online clustering algorithm. This learning algorithm was specifically developed to comply with the constrained computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental test-bed mimicking the environment of a critical infrastructure control system.

Authors:
; ; ;
Publication Date:
Research Org.:
Idaho National Laboratory (INL)
Sponsoring Org.:
USDOE
OSTI Identifier:
1013712
Report Number(s):
INL/CON-10-20411
TRN: US201110%%790
DOE Contract Number:  
DE-AC07-05ID14517
Resource Type:
Conference
Resource Relation:
Conference: CICS - 2011 IEEE Symposium on Computational Intelligence in Cyber Security,Paris, France,04/11/2011,04/15/2011
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; ALGORITHMS; CONTROL SYSTEMS; DETECTION; FUZZY LOGIC; IMPLEMENTATION; LEARNING; PERFORMANCE; SECURITY; SENSORS; Anomaly Detection; Cyber Sensor; Fuzzy Logic System; Online Clustering

Citation Formats

Linda, Ondrej, Vollmer, Todd, Wright, Jason, and Manic, Milos. Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor. United States: N. p., 2011. Web.
Linda, Ondrej, Vollmer, Todd, Wright, Jason, & Manic, Milos. Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor. United States.
Linda, Ondrej, Vollmer, Todd, Wright, Jason, and Manic, Milos. Fri . "Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor". United States. https://www.osti.gov/servlets/purl/1013712.
@article{osti_1013712,
title = {Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor},
author = {Linda, Ondrej and Vollmer, Todd and Wright, Jason and Manic, Milos},
abstractNote = {Resiliency and security in critical infrastructure control systems in the modern world of cyber terrorism constitute a relevant concern. Developing a network security system specifically tailored to the requirements of such critical assets is of a primary importance. This paper proposes a novel learning algorithm for anomaly based network security cyber sensor together with its hardware implementation. The presented learning algorithm constructs a fuzzy logic rule based model of normal network behavior. Individual fuzzy rules are extracted directly from the stream of incoming packets using an online clustering algorithm. This learning algorithm was specifically developed to comply with the constrained computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental test-bed mimicking the environment of a critical infrastructure control system.},
doi = {},
url = {https://www.osti.gov/biblio/1013712}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2011},
month = {4}
}

Conference:
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