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Automatically Attributing Mobile Threat Actors by Vectorized ATT&CK Matrix and Paired Indicator.

Kyoungmin Kim¹, Youngsup Shin¹, Justin Lee¹

¹Institute of Cyber Security & Privacy (ICSP), Korea University, Seoul 02841, Korea.

Sensors (Basel, Switzerland)

|October 13, 2021

Summary

This summary is machine-generated.

This study introduces an automated system for cyber attribution, enhancing mobile security. By analyzing tactics, techniques, and procedures (TTPs), it accurately identifies Advanced Persistent Threat (APT) groups and reduces false flags in mobile malware detection.

Keywords:

cyber security mobile security threat intelligence

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Area of Science:

Cybersecurity
Mobile Security
Threat Intelligence

Background:

Mobile devices are increasingly targeted by Advanced Persistent Threat (APT) groups.
Smartphones store sensitive data, making them attractive targets for cyberattacks.
Existing research lacks focus on automated cyber attribution for mobile threats.

Purpose of the Study:

To develop an automated system for cyber attribution of mobile threats.
To leverage MITRE's ATT&CK for mobile framework for analysis.
To improve the accuracy of identifying threat actors behind mobile attacks.

Main Methods:

Utilized MITRE's ATT&CK for mobile framework to analyze tactics, techniques, and procedures (TTPs).
Developed an automated system for cyber attribution.
Compared indicators of compromise (IoCs) to reduce false flags.
Analyzed 12 threat actors and 120 malware samples.

Main Results:

Successfully developed and tested an automated cyber attribution system for mobile threats.
Demonstrated a reduction in false flags through IoC comparison.
Provided a method for attributing mobile malware to specific threat actors.

Conclusions:

The automated system effectively attributes mobile cyber threats.
The approach enhances the accuracy of threat intelligence.
This research contributes to understanding and mitigating APT activities on mobile platforms.