An Assessment of ML-Powered Security Appliances for Situational Awareness

Abstract

Network security teams may find the adoption and deployment of a security appliance to be expensive and time-consuming. This document presents a review process that examines how an appliance fits into and contributes to an organizations situational awareness and security posture, including identification of utility, adoption issues, and how to mitigate such issues. The review grows out of the Workflow Review of Analysis Products developed by the SEI Situational Awareness team.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2021
Accession Number
AD1146733

Entities

People

  • Joshua Fallon
  • Timothy J. Shimeall

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Cyber

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Computer Network Security
  • Computing System Architectures
  • Cybersecurity
  • Detection
  • Electronic Mail
  • Engineering
  • Governments
  • Identification
  • Information Security
  • Intelligent Systems
  • Intrusion Detection
  • Learning
  • Machine Learning
  • Malware
  • Materials
  • Security
  • Situational Awareness
  • Software Development
  • Supervised Machine Learning
  • Test And Evaluation
  • Training
  • Universities

Fields of Study

  • Computer science

Readers

  • Enterprise Information Systems Architecture and Joint Command Capability Interoperability Support.
  • Software Engineering.

Technology Areas

  • Cyber