Poster: Flexible Function Estimation of IoT Malware Using Graph Embedding Technique

Kei Oshio, Satoshi Takada, Chansu Han, Akira Tanaka, Jun'ichi Takeuchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Most IoT malware is variants generated by editing and reusing parts of the functions based on publicly available source codes. In our previous study, we proposed a method to estimate the functions of a specimen using the Function Call Sequence Graph (FCSG), which is a directed graph of execution sequence of function calls. In the FCSG-based method, the subgraph corresponding to a malware functionality is manually created and called a signature-FSCG. The specimens with the signature-FSCG are expected to have the corresponding functionality. However, this method cannot detect the specimens with a slightly different subgraph from the signature-FSCG. This paper found that these specimens were supposed to have the same functionality for a signature-FSCG. These specimens need more flexible signature matching, and we propose a graph embedding technique to realize it.

Original languageEnglish
Title of host publication2022 IEEE Symposium on Computers and Communications, ISCC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665497923
DOIs
Publication statusPublished - 2022
Event27th IEEE Symposium on Computers and Communications, ISCC 2022 - Rhodes, Greece
Duration: Jun 30 2022Jul 3 2022

Publication series

NameProceedings - IEEE Symposium on Computers and Communications
Volume2022-June
ISSN (Print)1530-1346

Conference

Conference27th IEEE Symposium on Computers and Communications, ISCC 2022
Country/TerritoryGreece
CityRhodes
Period6/30/227/3/22

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Mathematics(all)
  • Computer Science Applications
  • Computer Networks and Communications

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