Cyberspace Sciences and Information Intelligence Research Group

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About CSIIR

Missions and Goals

Cyberspace is defined as "a domain characterized by the use of electronics and the electromagnetic spectrum to store, modify, and exchange data via networked systems and associated physical infrastructures" and Information Intelligence is defined as "knowledge resulting from discovery, collection, processing, integration, analysis, evaluation, interpretation, and/or understanding of available information." Cyberspace is the dynamic globally interconnected information infrastructure critical and essential to our nation’s security, economy, and the interaction of modern society.

The Cyberspace Sciences and Information Intelligence Research (CSIIR) Group has and is building a world class research organization focused on performing scientific research in:

Cyber Security - The protection & control of data, physical systems, networks & network infrastructures

Structured Heterogeneous Data - Knowledge discovery of complex disparate data in cyberspace to provide real-time actionable intelligence

 


Our objective is developing and producing innovative end-to-end integrated solutions to hard and challenging cyberspace problems. Protect, Control, and Exploit Cyberspace.

Research Areas

Cyber Security (Protection and Control in Cyberspace)

  • Distributed Real-Time Cyberspace Discovery and Analysis for Cyber Situation Awareness
  • Real-Time Cyber Knowledge Discovery for Anomaly and Attack Detection
  • Active Response and Forensics for Cyber Defense
  • Vulnerability and Malware Analysis via Software Reverse Engineering, Function Extraction and Semantic Analysis
  • Embedded Device Security
  • Medical Device Security
  • Anti-Phishing and Whaling
  • Control Systems Security of the Energy Infrastructure
  • Intelligent Insider Threat Detection and Prevention

Structured Heterogeneous Data (Knowledge Discovery in Cyberspace)

  • Graph-Based Solutions for Large Datasets and Fast Response Times
  • Hypothesis Generation and Deception Detection within Large Structured Datasets
  • Social Network Analysis
  • Evaluative Metrics and Methods for Risk Assessment and Decision Support
  • Probabilistic Modeling and Automated Reasoning

 


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