A Study on Malicious Code Detection Using Blockchain and Deep Learning
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Damages by malware have recently been increasing. Conventional signature-based antivirus solutions are helplessly vulnerable tounprecedented new threats such as Zero-day attack and ransomware. Despite that, many enterprises have retained signature-based antivirussolutions as part of the multiple endpoints security strategy. They do recognize the problem. This paper proposes a solution using theblockchain and deep learning technologies as the next-generation antivirus solution. It uses the antivirus software that updates throughan existing DB server to supplement the detection unit and organizes the blockchain instead of the DB for deep learning using varioussamples and forms to increase the detection rate of new malware and falsified malware.
Abstract
Damages by malware have recently been increasing. Conventional signature-based antivirus solutions are helplessly vulnerable tounprecedented new threats such as Zero-day attack and ransomware. Despite that, many enterprises have retained signature-based antivirussolutions as part of the multiple endpoints security strategy. They do recognize the problem. This paper proposes a solution using theblockchain and deep learning technologies as the next-generation antivirus solution. It uses the antivirus software that updates throughan existing DB server to supplement the detection unit and organizes the blockchain instead of the DB for deep learning using varioussamples and forms to increase the detection rate of new malware and falsified malware.
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