Human-Computer Decision Systems

Abstract

Security decision systems aim to distinguish malicious activity from benign and often use a combination of human expert and automated analysis, including machine learning (ML). Systems using only human experts scale badly; pure ML systems are susceptible to structured attack by adversaries and, in most cases, have unsatisfactory performance on their own.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2015
Accession Number
AD1147074

Entities

People

  • Brian Lindauer

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy
  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Artifacts
  • Computers
  • Copyrights
  • Department Of Defense
  • Engineering
  • Governments
  • Guarantees
  • Learning
  • Machine Learning
  • Materials
  • Security
  • Simulations
  • Software Development
  • Universities

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks