Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor
Conference
·
OSTI ID:1013712
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.
- Research Organization:
- Idaho National Laboratory (INL)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC07-05ID14517
- OSTI ID:
- 1013712
- Report Number(s):
- INL/CON-10-20411
- Country of Publication:
- United States
- Language:
- English
Similar Records
Towards Resilient Critical Infrastructures: Application of Type-2 Fuzzy Logic in Embedded Network Security Cyber Sensor
Improving Cyber-Security of Smart Grid Systems via Anomaly Detection and Linguistic Domain Knowledge
Cyber Security and Resilient Systems
Conference
·
Mon Aug 01 00:00:00 EDT 2011
·
OSTI ID:1028233
Improving Cyber-Security of Smart Grid Systems via Anomaly Detection and Linguistic Domain Knowledge
Conference
·
Wed Aug 01 00:00:00 EDT 2012
·
OSTI ID:1055968
Cyber Security and Resilient Systems
Conference
·
Wed Jul 01 00:00:00 EDT 2009
·
OSTI ID:963748