ISSN :2582-9793

Blockchain Malware Detection Tool Based on Signature Technique

Original Research (Published On: 27-Nov-2023 )
Blockchain Malware Detection Tool Based on Signature Technique
DOI : https://dx.doi.org/10.54364/AAIML.2023.1194

Su-Cheng Haw, Siti Husna Abdul Rahman, Chastan Nevin Gabriel and Ahmad Anwar Zainuddin

Adv. Artif. Intell. Mach. Learn., 3 (4):1654-1670

Su-Cheng Haw : Multimedia University, Malaysia

Siti Husna Abdul Rahman : Multimedia University

Chastan Nevin Gabriel : Multimedia University

Ahmad Anwar Zainuddin : International Islamic University Malaysia

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DOI: https://dx.doi.org/10.54364/AAIML.2023.1194

Article History: Received on: 12-Sep-23, Accepted on: 20-Nov-23, Published on: 27-Nov-23

Corresponding Author: Su-Cheng Haw

Email: sucheng@mmu.edu.my

Citation: Siti Husna Abdul Rahman, Chastan Nevin Gabriel, Su-Cheng Haw, Ahmad Anwar Zainuddin (2023). Blockchain Malware Detection Tool Based on Signature Technique. Adv. Artif. Intell. Mach. Learn., 3 (4 ):1654-1670


Abstract

    

Downloading software or files from the internet can be risky as it is hard to know if they are safe and do not contain viruses. Traditional anti-virus software uses a centralized database to identify malware, but this method has drawbacks due to its centralized design, which creates a single point of failure. Blockchain technology has become a solution to many problems faced in the tech industry, including the need for a decentralized and secure way for users to verify and confirm the presence of malware in a file. The decentralized database, permanence, immutability, anonymity, and auditability of blockchain technology make it an ideal solution for malware detection. In fact, malware data has been compiled in databases that antivirus manufacturers use to identify malware. However, blockchain technology provides a more secure and decentralized way to store this data, which can be shared between users and allow them to rapidly update whether a file is safe or not. This paper presents a blockchain-based malware detection tool designed to enhance security and prevent the spread of malware in digital networks. The tool based on Java programming language incorporates signature-based methods to effectively identify and detect malicious codes in malware. The proposed tool contributes to the field of cybersecurity by leveraging blockchain technology to enhance malware detection process.

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