Nave Bayes Log File Reduction and Analysis

Abstract

The application of Bayes theorem in computer science dates back to the 1960s and continues to be heavily used in Nave Bayes classifiers in machine learning. In this report, we propose the use of a Nave Bayes-based classifier for automated analysis and data reduction of text-based log files generated by various computer systems and the services they provide. The intended application of this technique is to automate the reduction of voluminous log files to a more manageable size and, with reasonable accuracy, retain log lines containing potential indicators of malicious cybersecurity activity or other infrequent interesting activity that should be examined further through other means.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2019
Accession Number
AD1066792

Entities

People

  • Gregory G Shearer
  • Kenneth D. Renard
  • Ralph P. Ritchey

Organizations

  • ICF International
  • United States Army Research Laboratory

Tags

Communities of Interest

  • Autonomy
  • Engineered Resilient Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Cybersecurity
  • Data Reduction
  • Data Set
  • Department Of Defense
  • Detection
  • Digital Data
  • Engineering
  • Identification
  • Information Science
  • Information Security
  • Intrusion Detection
  • Intrusion Detection Systems
  • Intrusion Detectors
  • Literature Surveys
  • Machine Learning
  • Network Protocols
  • Network Science
  • Operating Systems
  • Security
  • Supervised Machine Learning
  • Three Dimensional
  • Web Applications

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Database Systems and Applications
  • Statistical inference.

Technology Areas

  • AI & ML
  • Cyber