Mitigating the Insider Threat with High-Dimensional Anomaly Detection

Abstract

In this project, we explored new techniques for detecting the threat of insider attacks in enterprise networks. In particular, we explored the use of high-dimensional search techniques such as Latent Semantic Indexing to mitigate the problem of high dimensionality that is inherent in intrusion detection. This new technique can be used for both labeled and unlabeled detection, and shows promise for detecting attacks and anomalies earlier than previously possible and detecting attacks that are similar to past ones.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2004
Accession Number
ADA429343

Entities

People

  • Eric van den Berg
  • S. Pramanick
  • Shriram Rajagopalan

Tags

Communities of Interest

  • Cyber
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Anomaly Detection
  • Change Detection
  • Data Mining
  • Denial Of Service Attack
  • Detection
  • Detectors
  • Dimensionality Reduction
  • Factor Analysis
  • Information Retrieval
  • Information Science
  • Insider Threats
  • Intrusion Detection
  • Intrusion Detectors
  • Machine Learning
  • Natural Language Processing
  • Operating Systems

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Computer Vision.
  • Cybersecurity.