Deep Focus: Increasing User "Depth of Field" to Improve Threat Detection (Oxford Workshop Poster)

Abstract

We believe insider threat detection methods can be improved by monitoring and analyzing features of user behavior not typically associated with indicators of malicious insider behavior. Anomalous behaviors and statistical outliers observed in such data sets may identify new indicators or help reduce high false positive rates associated with existing indicators.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2014
Accession Number
ADA610980

Entities

People

  • Alex Kent
  • Brian Lindauer
  • Bronwyn Woods
  • David Jensen
  • Jason Clark
  • Joshua Neil
  • Phil Legg
  • Roy Maxion
  • Sadie Creese
  • William R. Claycomb

Organizations

  • Carnegie Mellon University

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Data Sets
  • Detection
  • Indicators
  • Information Operations
  • Insider Threats
  • Instructions
  • Monitoring
  • Security
  • Software Development
  • Threats
  • Workshops

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Cybersecurity.
  • Regression Analysis.