Skip to content

Fuzzy-import hashing: a static analysis technique for malware detection

Research output: Contribution to journalArticlepeer-review

  • Nitin Naik
  • Paul Jenkins
  • Dr Nick Savage
  • Longzhi Yang
  • Tossapon Boongoen
  • Natthakan Iam-On

The advent of new malware types and their attack vectors poses serious challenges for security experts in discovering effective malware detection and analysis techniques. The preliminary step in malware analysis is filtering out samples of counterfeit malware from the suspicious samples by classifying them into most likely and unlikely malware categories. This will enable effective utilisation of resources and expertise for the most likely category of samples in subsequent stages and avoid nugatory effort. This process requires a very fast and resource-optimised method as it is applied on a large sample size. Fuzzy hashing and import hashing methods satisfy these requirements of malware analysis, though, with some limitations. Therefore, the proper integration of these methods, may overcome some of the limitations and improve the detection accuracy without affecting the overall performance of analysis. Hence, this paper proposes a fuzzy-import hashing technique, which is the integration of two methods, namely, fuzzy hashing and import hashing. This integration can offer several benefits such as an improved detection rate by complementing each other when one method cannot detect malware, then the other method can; and the generation of fuzzfied results for subsequent clustering or classification, as the import hashing result can be easily merged with the fuzzy hashing result. The success of this proposed fuzzy-import hashing method is demonstrated through several experiments namely: on the collected malware and goodware corpus; a comparative evaluation against the established YARA rules and application in fuzzy c-means clustering.

Original languageEnglish
Article number301139
Number of pages12
JournalForensic Science International: Digital Investigation
Volume37
Early online date1 Apr 2021
DOIs
Publication statusPublished - 1 Jun 2021

Documents

  • FSIDI-301139-Fuzzy-Import-Hashing-DrNaik

    Accepted author manuscript (Post-print), 678 KB, PDF document

    Due to publisher’s copyright restrictions, this document is not freely available to download from this website until: 1/04/22

    Licence: CC BY-NC-ND

Related information

Relations Get citation (various referencing formats)

ID: 27161659