Embedded YARA rules strengthening YARA rules utilising fuzzy hashing and fuzzy rules for malware analysis.pdf (1.49 MB)
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Embedded YARA rules: strengthening YARA rules utilising fuzzy hashing and fuzzy rules for malware analysis

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journal contribution
posted on 18.02.2022, 15:55 authored by Nitin Naik, Paul JenkinsPaul Jenkins, Nick Savage, Longzhi Yang, Tossapon Boongoen, Natthakan Iam-On, Kshirasagar Naik, Jingping Song
The YARA rules technique is used in cybersecurity to scan for malware, often in its default form, where rules are created either manually or automatically. Creating YARA rules that enable analysts to label files as suspected malware is a highly technical skill, requiring expertise in cybersecurity. Therefore, in cases where rules are either created manually or automatically, it is desirable to improve both the performance and detection outcomes of the process. In this paper, two methods are proposed utilising the techniques of fuzzy hashing and fuzzy rules, to increase the effectiveness of YARA rules without escalating the complexity and overheads associated with YARA rules. The first proposed method utilises fuzzy hashing referred to as enhanced YARA rules in this paper, where if existing YARA rules fails to detect the inspected file as malware, then it is subjected to fuzzy hashing to assess whether this technique would identify it as malware. The second proposed technique called embedded YARA rules utilises fuzzy hashing and fuzzy rules to improve the outcomes further. Fuzzy rules countenance circumstances where data are imprecise or uncertain, generating a probabilistic outcome indicating the likelihood of whether a file is malware or not. The paper discusses the success of the proposed enhanced YARA rules and embedded YARA rules through several experiments on the collected malware and goodware corpus and their comparative evaluation against YARA rules.

Funding

Portsmouth University

History

Published in

Complex & Intelligent Systems

Publisher

Springer International Publishing

Version

VoR (Version of Record)

Citation

Naik, N., Jenkins, P., Savage, N., Yang, L., Boongoen, T., Iam-On, N., Naik, K. and Song, J. (2021) 'Embedded YARA rules: strengthening YARA rules utilising fuzzy hashing and fuzzy rules for malware analysis', Complex & Intelligent Systems, 7(2), pp.687-702. https://doi.org/10.1007/s40747-020-00233-5

Print ISSN

2199-4536

Electronic ISSN

2198-6053

Cardiff Met Affiliation

  • Cardiff School of Technologies

Cardiff Met Authors

Paul Jenkins

Copyright Holder

© The Authors

Language

en