Malicious Application Detection in Windows Using SVM Algorithm

Year : 2023 | Volume :01 | Issue : 01 | Page : 30-36
By

Manish Kapoor

R.M. Samant

Suraj Sawant

Aishwarya Joshi

Neha Tawade

  1. Student Department of Information Technology, NBN Sinhgad School of Engineering, Pune Maharashtra India
  2. HOD Department of Information Technology, NBN Sinhgad School of Engineering, Pune Maharashtra India
  3. Student Department of Information Technology, NBN Sinhgad School of Engineering, Pune Maharashtra India
  4. Student Department of Information Technology, NBN Sinhgad School of Engineering, Pune Maharashtra India
  5. Student Department of Information Technology, NBN Sinhgad School of Engineering, Pune Maharashtra India

Abstract

In recent years, both the development of Windows application clients and the uses of smart mobile phones have increased significantly. As the number of Windows application users continues to grow, there is a rise in malicious individuals who develop harmful Windows applications with the intent of unlawfully obtaining confidential information and engaging in fraudulent activities. These applications are designed to target vulnerable areas such as mobile banking and digital wallets, aiming to deceive users and misuse their sensitive data. There are so many malicious software, tools, and programmers that are available. However, it is essential to establish a system that is capable and effective for identifying and thwarting freshly developed dangerous programmes written by hackers or programmers. This system should be able to recognise and react to sophisticated threats in an efficient manner. The purpose of this study is to identify fraudulent Windows apps using machine learning techniques.

Keywords: Malicious Application Detection in Windows Using SVM Algorithm

[This article belongs to International Journal of Mobile Computing Technology(ijmct)]

How to cite this article: Manish Kapoor, R.M. Samant, Suraj Sawant, Aishwarya Joshi, Neha Tawade. Malicious Application Detection in Windows Using SVM Algorithm. International Journal of Mobile Computing Technology. 2023; 01(01):30-36.
How to cite this URL: Manish Kapoor, R.M. Samant, Suraj Sawant, Aishwarya Joshi, Neha Tawade. Malicious Application Detection in Windows Using SVM Algorithm. International Journal of Mobile Computing Technology. 2023; 01(01):30-36. Available from: https://journals.stmjournals.com/ijmct/article=2023/view=114732


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Regular Issue Subscription Review Article
Volume 01
Issue 01
Received June 7, 2023
Accepted July 3, 2023
Published August 3, 2023
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