Large-Scale Intelligent Intrusion Detection System
- Physical Optics Corporation,Torrance, CA (United States). Applied Technologies Division
An effective and practical cybersecurity tool is needed to provide cybersecurity monitoring, situational awareness, reporting, intrusion prevention, and remediation in high performance computing (HPC) facilities, centers, infrastructure, or resources. This tool should provide an intelligent shield to fend off new-generation cyberattacks and secure HPC facilities, infrastructure, and large-scale systems. To address this need, Physical Optics Corporation (POC) has completed a Phase I SBIR project, Large-Scale Intelligent Intrusion Detection (LSIID) system. LSIID is based on integration of risk-based analysis using Markov decision processes (MDPs), a Bayesian inference model, unsupervised and supervised machine learning techniques, an intelligent intrusion detection decision mechanism using historical and time information, and the existing Bro intrusion detection system’s event managing engine. This combination provides the artificial intelligence (AI) needed to detect and mitigate both known and new cyberattacks in HPC networks and hosts. During Phase I, a large-scale intelligent intrusion detection system architecture, framework design, and algorithms were developed. The feasibility of the approach was demonstrated by assembling, testing, and evaluation of a technology readiness level (TRL)-4 prototype. Test and evaluation results demonstrated the capability of LSIID to defend HPC systems against known and new attacks in real time, resulting in a powerful intelligent large-scale intrusion detection/protection system. Plans were also devised for enhancement of intrusion detection/protection capabilities of LSIID and its integration with HPC systems in Phase II.
- Research Organization:
- Physical Optics Corporation,Torrance, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- DOE Contract Number:
- SC0017194
- OSTI ID:
- 1415488
- Type / Phase:
- SBIR (Phase I)
- Report Number(s):
- DOE-POC-0017194; 10014
- Country of Publication:
- United States
- Language:
- English
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