Multi Feature Detection and Signature Sharing of Android Malware using Blockchain

Abstract

Android devices like smartphones and tablets has been gaining much popularity and accelerated usage for its low cost and increase in functionality and services. Due to its openness and free availability, Android Based system has become not only a major stakeholder in the market but has also become an attractive target for cybercriminals. The main objective of this project is to reduce false positive rate in malware detection by analyzing Different malware families are developing a corresponding Multi-Feature Model (MFM) on Android-based systems by following a fuzzy method of comparison. A file hash value is generated if a malware is suspected and send to the blockchain network As alleged identity of the malware file. If there is the same file hash value on the blockchain, the file is found to be malicious by the malware detection program, and the result is sent to the blockchain network as a vote. This system can ensure data security and consistency with the use of blockchain. The results show that the proposed system can achieve efficient detection accuracy and reduced false positive and negative rates.