A Blockchain-based Framework for Detecting Malicious Mobile Applications in App Stores
Sajad Homayoun, Ali Dehghantanha, Reza M. Parizi, Kim-Kwang Raymond, Choo

TL;DR
This paper introduces a novel blockchain-based framework that enhances the detection of malicious mobile applications in app stores by securely sharing features and detection results among stakeholders.
Contribution
It presents a dual private blockchain system combined with a consortium blockchain to improve malware detection accuracy and facilitate secure feature sharing among vendors.
Findings
Enhanced malware detection accuracy
Secure sharing of features and results among stakeholders
Effective collaboration between antimalware vendors
Abstract
The dramatic growth in smartphone malware shows that malicious program developers are shifting from traditional PC systems to smartphone devices. Therefore, security researchers are also moving towards proposing novel antimalware methods to provide adequate protection. This paper proposes a Blockchain-Based Malware Detection Framework (B2MDF) for detecting malicious mobile applications in mobile applications marketplaces (app stores). The framework consists of two internal and external private blockchains forming a dual private blockchain as well as a consortium blockchain for the final decision. The internal private blockchain stores feature blocks extracted by both static and dynamic feature extractors, while the external blockchain stores detection results as blocks for current versions of applications. B2MDF also shares feature blocks with third parties, and this helps antimalware…
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