Machine Learning in Cybersecurity: A Guide

Abstract

This report lists relevant questions that decision makers should ask of machine-learning practitioners before employing machine learning (ML) or artificial intelligence (AI) solutions in the area of cybersecurity. Like any tool, ML tools should be a good fit for the purpose they are intended to achieve. The questions in this report will improve decision makers ability to select an appropriate ML tool and make it a good fit to address their cybersecurity topic of interest. In addition, the report outlines the type of information that good answers to the questions should contain.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2019
Accession Number
AD1082647

Entities

People

  • Angela Horneman
  • April Galyardt
  • Edward Stoner
  • Jonathan M. Spring
  • Joshua Fallon
  • Leigh Metcalf

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy
  • Cyber

DTIC Thesaurus Topics

  • Aircrafts
  • Artificial Intelligence
  • Commerce
  • Computer Languages
  • Computers
  • Cybersecurity
  • Electronic Mail
  • Engineering
  • Governments
  • Information Security
  • Information Systems
  • Learning
  • Machine Learning
  • Military Aircraft
  • Reasoning
  • Risk Analysis
  • Software Development

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks
  • Cyber