Evaluating Automatically Generated YARA Rules and Enhancing Their Effectiveness

Nitin Naik, Paul Jenkins, Roger Cooke, Jonathan Gillett, Yaochu Jin

Research output: Chapter in Book/Published conference outputConference publication

Abstract

Emerging as a widely accepted technique for malware analysis, YARA rules due to its flexible and customisable nature, allows malware analysts to develop rules according to the requirements of a specific security domain. YARA rules can be automatically generated using tools, however, they may require post-processing for their optimisation, and may not be effective for the specific security domain. This compels the requirement to enhance automatically generated YARA rules and increase their effectiveness for malware analysis without increasing computational overheads. Reflecting on the above requirement, this paper initially evaluates automatically generated YARA rules using three YARA tools: yarGen, yaraGenerator and yabin. These tools are Python-based open-source tools used to generate YARA rules automatically utilising different underlying techniques. Subsequently, it proposes a method to enhance automatically generated YARA rules using a fuzzy hashing method. This proposed enhancement method can improve the effectiveness of YARA rules irrespective of the chosen YARA tool used to generate YARA rules, which is demonstrated through several experiments on samples of collected malware and goodware.
Original languageEnglish
Title of host publication2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
PublisherIEEE
Pages1146-1153
Number of pages8
ISBN (Electronic)978-1-7281-2547-3
ISBN (Print)978-1-7281-2548-0
DOIs
Publication statusPublished - 5 Jan 2021
Event2020 IEEE Symposium Series on Computational Intelligence (SSCI) - Canberra, Australia
Duration: 1 Dec 20204 Dec 2020

Publication series

Name2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020

Conference

Conference2020 IEEE Symposium Series on Computational Intelligence (SSCI)
Abbreviated titleSSCI
Country/TerritoryAustralia
CityCanberra
Period1/12/204/12/20

Bibliographical note

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Keywords

  • Fuzzy Hashing
  • Indicator of Compromise
  • IoC String.
  • Malware Analysis
  • Malware Analysis; YARA Rules; Fuzzy Hashing; yarGen
  • Ransomware
  • YARA Rules
  • yabin
  • yarGen, yaraGenerator
  • yaraGenerator; yabin; Ransomware; Indicator of Compromise; IoC String.

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