Scalable and robust unsupervised android malware fingerprinting using community-based network partitioning
Abstract
The daily amount of Android malicious applications (apps) targeting the app repositories is increasing, and their number is overwhelming the process of fingerprinting. To address this issue, we propose an enhanced Cypider framework, a set of techniques and tools aiming to perform a systematic detection of mobile malware by building a scalable and obfuscation resilient similarity network infrastructure of malicious apps. Our approach is based on...
Paper Details
Title
Scalable and robust unsupervised android malware fingerprinting using community-based network partitioning
Published Date
Oct 1, 2020
Journal
Volume
97
Pages
101965 - 101965
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