Accession Number:



Machine Learning in Cybersecurity: A Guide

Descriptive Note:

Technical Report

Corporate Author:

Carnegie Mellon University Software Engineering Institute Pittsburgh United States

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Decision-makers should ask certain questions before employing machine-learning ML or artificial intelligence AI solutions and receive satisfactory answers. This document suggests important questions when employing ML or AI in cybersecurity and outlines what a satisfactory answer should contain. We focus on questions about quality and usefulness. The questions we discuss are 1. What are you trying to find out 2. What information is needed to answer the target question 3. How do you anticipate that the MLAI tool will address that question 4. Is the design of the MLAI tool robust to the well-known attacks against MLAI in our adversarial, cybersecurity environment 5. How can the input datas bias be managed 6. Does the evaluation of the MLAI tool properly account for well-known study design errors and biases7. What alternative tools have you considered What are the advantages and disadvantages of each

Subject Categories:

  • Cybernetics

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