Fuzzy Hashing on Firmwares Images : A Comparative Analysis

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

1 Scopus Citations
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Author(s)

  • Daojing He
  • Xiaohu Yu
  • Shanshan Zhu
  • Sammy Chan
  • Mohsen Guizani

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)45-50
Journal / PublicationIEEE Internet Computing
Volume27
Issue number2
Online published1 Dec 2022
Publication statusPublished - Mar 2023

Abstract

With the fast development of the Internet of Things (IoT) technology, there are more and more attacks against IoT devices, and IoT security issues have attracted considerable attention. Due to the widespread phenomenon that different IoT firmwares reuse the same code, code similarity comparison is an important technique for IoT security analysis. Fuzzy hashing generates fingerprints of files by converting them into intermediate expressions and hashing such expressions, evaluating the fingerprint similarity and thus evaluating the similarity of files that are not identical. In this paper, we analyze and compare today's most widely used fuzzy hashing tools, and classify them in detail. In addition, we also analyze the advantages and disadvantages of different algorithms used by these fuzzy hashing tools. Finally, we select a few of the most convincing fuzzy hashing tools, such as ssdeep and TLSH, for performance comparison by experimental analysis on real firmware datasets. © 2022 IEEE

Research Area(s)

  • firmware, fuzzy hashing, homology, Internet of Things

Citation Format(s)

Fuzzy Hashing on Firmwares Images: A Comparative Analysis. / He, Daojing; Yu, Xiaohu; Zhu, Shanshan et al.
In: IEEE Internet Computing, Vol. 27, No. 2, 03.2023, p. 45-50.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review