Automatically attributing mobile threat actors by vectorized ATT&CK matrix and paired indicator

Kyoungmin Kim, Youngsup Shin, Justin Lee, Kyungho Lee

Research output: Contribution to journalArticlepeer-review

Abstract

During the past decade, mobile attacks have been established as an indispensable attack vector adopted by Advanced Persistent Threat (APT) groups. The ubiquitous nature of the smartphone has allowed users to use mobile payments and store private or sensitive data (i.e., login credentials). Consequently, various APT groups have focused on exploiting these vulnerabilities. Past studies have proposed automated classification and detection methods, while few studies have covered the cyber attribution. Our study introduces an automated system that focuses on cyber attribution. Adopting MITRE’s ATT&CK for mobile, we performed our study using the tactic, technique, and procedures (TTPs). By comparing the indicator of compromise (IoC), we were able to help reduce the false flags during our experiment. Moreover, we examined 12 threat actors and 120 malware using the automated method for detecting cyber attribution.

Original languageEnglish
Article number6522
JournalSensors
Volume21
Issue number19
DOIs
Publication statusPublished - 2021 Oct 1

Keywords

  • Cyber security
  • Mobile security
  • Threat intelligence

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

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