National Center for Multisource Information Fusion

Abstract : The National Center for Multisource Information Fusion (N-CMIF) research was a joint collaboration between CUBRC, University at Buffalo (UB), Rochester Institute of Technology (RIT) and Penn State University (PSU) to address information fusion research gaps present in situation, threat, and impact assessment (JDL levels 2 and 3) as well as sensor management (JDL level 4) and visualization. While much of the research conducted under N-CMIF emphasized computer security, the research also aimed to address the problems in a manner applicable to other domains. Major accomplishments in N-CMIF include (1) addressing current gaps in information fusion and computer security; (2) the enhancement of the Cyber Attack Simulator (a tool to automatically generate cyber attack scenarios for a given computer network); (3) Future Situation and Impact Awareness (FuSIA) (a level 2/3 framework implemented in Java that enhances situation awareness by identifying the current and future impact of a situation as well as providing run-time performance metrics to evaluate the quality of the assessments); (4) two different sensor management techniques for computer networks; (5) semantic and contextual reasoning of cyber attacks; and (6) the visualization of cyber attacks.

[1]  Sushil Jajodia,et al.  Topological analysis of network attack vulnerability , 2006, PST.

[2]  S. Goldberg,et al.  Introduction to Difference Equations , 1958 .

[3]  Stuart C. Shapiro SNePS: a logic for natural language understanding and commonsense reasoning , 2000 .

[4]  Mark A. Turnquist,et al.  Assessing the performance of interdependent infrastructures and optimizing investments , 2004, 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the.

[5]  Tim Bass,et al.  Intrusion detection systems and multisensor data fusion , 2000, CACM.

[6]  Shanchieh Jay Yang,et al.  Terrain and behavior modeling for projecting multistage cyber attacks , 2007, 2007 10th International Conference on Information Fusion.

[7]  E.A. Lee,et al.  Synchronous data flow , 1987, Proceedings of the IEEE.

[8]  S. Elaydi An introduction to difference equations , 1995 .

[9]  Adam Stotz,et al.  Situational awareness of a coordinated cyber attack , 2005, SPIE Defense + Commercial Sensing.

[10]  James Llinas,et al.  A framework for dynamic hard/soft fusion , 2008, 2008 11th International Conference on Information Fusion.

[11]  Cynthia A. Phillips,et al.  A graph-based system for network-vulnerability analysis , 1998, NSPW '98.

[12]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[13]  Shanchieh Jay Yang,et al.  VTAC: virtual terrain assisted impact assessment for cyber attacks , 2008, SPIE Defense + Commercial Sensing.

[14]  Edward A. Lee,et al.  Causality interfaces for actor networks , 2008, TECS.

[15]  Adam Stotz,et al.  INformation fusion engine for real-time decision-making (INFERD): A perceptual system for cyber attack tracking , 2007, 2007 10th International Conference on Information Fusion.

[16]  Stuart C. Shapiro,et al.  Symbolic Reasoning in the Cyber Security Domain , 2007 .

[17]  Adam Stotz,et al.  Measuring situational awareness and resolving inherent high-level fusion obstacles , 2006, SPIE Defense + Commercial Sensing.

[18]  Kenneth D. Forbus,et al.  Building Problem Solvers , 1993 .

[19]  Larry Wos,et al.  Automated Reasoning: Introduction and Applications , 1984 .

[20]  Richard P. Lippmann,et al.  An Annotated Review of Past Papers on Attack Graphs , 2005 .

[21]  Sheldon M. Ross Introduction to Probability Models. , 1995 .

[22]  Christopher Krügel,et al.  Comprehensive approach to intrusion detection alert correlation , 2004, IEEE Transactions on Dependable and Secure Computing.