High Level Fusion in the Cyber Domain

Abstract

The objective of this report is to summarize the work performed during the summer at AFRL, Rome Research site by a team of researchers from SUNY at Buffalo and Rochester Institute of Technology (RIT). The team began their research with lessons learned from the testing of INFERD v1, and applied research methods to overcome the deficiencies found. These deficiencies and an overview of the old methodology of INFERD are discussed along with the results of this research. Work discussed in the report includes attack identification and tracking techniques, identification of cyber threats and modeling and generation of cyber environments for generation of data sets.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2005
Accession Number
ADA441263

Entities

People

  • Adam Stotz
  • Eric Bohannon
  • Jared Holsopple
  • Jason Kistner
  • Michael Holender
  • Michael Kühl
  • Moises Sudit
  • Shanchieh Yang

Organizations

  • University at Buffalo

Tags

Communities of Interest

  • Cyber

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Bayesian Networks
  • Computer Networks
  • Computers
  • Cyberattacks
  • Detection
  • Hidden Markov Models
  • Industrial Engineering
  • Intrusion Detection
  • Intrusion Detection Systems
  • Intrusion Detectors
  • Operating Systems
  • Probability
  • Reliability
  • Situational Awareness
  • Systems Engineering

Readers

  • Instructional Design and Training Evaluation.
  • Military Science and Technology Research and Modernization.
  • Research Science/Academic Research

Technology Areas

  • Cyber