Detection of Botnet using deep learning algorithm: application of machine learning in cyber-security

被引：0

作者：

Sivakumar, A. ^{[1
]}

Rubia, J. Jency ^{[2
]}

Vijayan, Hima ^{[3
]}

Sivakumaran, C. ^{[4
]}

机构：

[1] SRM Inst Sci & Technol, Dept Data Sci & Business Syst, Kattankulathur, Tamil Nadu, India

[2] K Ramakrishnan Coll Engn, Dept Elect & Commun Engn, Trichy, Tamil Nadu, India

[3] SA Engn Coll, Dept Informat Technol, Chennai, India

[4] Photon Technol, Chennai 600017, India

来源：

INTERNATIONAL JOURNAL OF ELECTRONIC SECURITY AND DIGITAL FORENSICS | 2024年 / 16卷 / 02期

关键词：

adversarial attack; security; machine learning; deep learning; LSTM; PRIVACY;

D O I：

10.1504/IJESDF.2024.137030

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Machine learning has been made possible as a result of the availability and accessibility of a massive amount of data gathered by internet-connected sensors. The concept of machine learning exhibits and spreads the notion that a computer has the potential to develop itself over the course of time. We investigate a variety of security applications from a variety of angles in which ML models play a key role, and we compare the accuracy outcomes of these models using a variety of conceivable dimensions. To provide an accurate depiction of the qualities associated with security, we have shown the threat model and defence strategies against adversarial attack techniques. The proposed method shows about 88% accuracy for the used data. These attacks are based on the fact that the adversaries are aware of the model.

引用

页码：213 / 222

页数：11

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