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http://dx.doi.org/10.3745/KTCCS.2021.10.2.39

A Study on Malicious Code Detection Using Blockchain and Deep Learning  

Lee, Deok Gyu (서원대학교 정보보안학과)
Publication Information
KIPS Transactions on Computer and Communication Systems / v.10, no.2, 2021 , pp. 39-46 More about this Journal
Abstract
Damages by malware have recently been increasing. Conventional signature-based antivirus solutions are helplessly vulnerable to unprecedented new threats such as Zero-day attack and ransomware. Despite that, many enterprises have retained signature-based antivirus solutions as part of the multiple endpoints security strategy. They do recognize the problem. This paper proposes a solution using the blockchain and deep learning technologies as the next-generation antivirus solution. It uses the antivirus software that updates through an existing DB server to supplement the detection unit and organizes the blockchain instead of the DB for deep learning using various samples and forms to increase the detection rate of new malware and falsified malware.
Keywords
Malicious Code; Code Detection; Blockcahin; Deep Learning;
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