A Study on Malicious Code Detection Using Blockchain and Deep Learning


KIPS Transactions on Computer and Communication Systems, Vol. 10, No. 2, pp. 39-46, Feb. 2021
https://doi.org/10.3745/KTCCS.2021.10.2.39,   PDF Download:
Keywords: Malicious Code, Code Detection, Blockcahin, Deep Learning
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.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from September 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[IEEE Style]
D. G. Lee, "A Study on Malicious Code Detection Using Blockchain and Deep Learning," KIPS Transactions on Computer and Communication Systems, vol. 10, no. 2, pp. 39-46, 2021. DOI: https://doi.org/10.3745/KTCCS.2021.10.2.39.

[ACM Style]
Deok Gyu Lee. 2021. A Study on Malicious Code Detection Using Blockchain and Deep Learning. KIPS Transactions on Computer and Communication Systems, 10, 2, (2021), 39-46. DOI: https://doi.org/10.3745/KTCCS.2021.10.2.39.