MACHINE LEARNING – POWERED SYSTEM TO DETECT MALICIOUS SOFTWARE

Authors:

Dr. K. Siva Rama Krishna, J. Reshma, M.Supriya, D. Naga Anusha

Page No: 542-550

Abstract:

Malware's current state is still grave, and it continues to pose a severe threat to the modern world. Cybercrime has thus become a significant problem for computer users. Malware assaults are one of the various ways that cyber-attacks are planned. Occasionally known as harmful software. Viruses, Trojan horses, worms, rootkits, adware, and ransomware are all examples of malware. These are the main tools used by online attackers. An organization must use a variety of security measures to protect its network and system, which makes malware detection an extremely laborious operation. Detecting malicious programs typically involves using behavior-based and signature-based detection techniques.

Description:

SVM, KNN, Naive Bayes, Decision Tree, Logistic Regression, Random Forest, MalConv CNN, Malconv LSTM.

Volume & Issue

Volume-12,ISSUE-3

Keywords

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