Role of Logistic Regression in Malware Detection: A Systematic Literature Review

  • Farooq M
  • Akram Z
  • Alvi A
  • et al.
N/ACitations
Citations of this article
8Readers
Mendeley users who have this article in their library.

Abstract

When brain, the first virus known introduced in computer systems, requirement of security was raised. Malware Detection turn out to be more vital when network is used for transferring Secret Information. Nowadays our central attributes i.e., Banking, Agriculture, Robotics, Virtual Social Life, Online Multiplayer Gaming, Private Conversations etc. is practicing internet and Malware will abolish everything if we discount it. Lots of new malwares are located by the passage of time, so we need a reliable, fast and trustworthy machine learning technique to handle them. Logistic Regression Classifier is useable for handling such a huge data, majorly counted in this paper. This is a complete SLR that delivers progressive approach in the field of malware detection. It legally reduces time and the cost of researchers. Limitations and future directions of machine learning classifiers to detect malwares are discussed in this paper.

Cite

CITATION STYLE

APA

Farooq, M. S., Akram, Z., Alvi, A., & Omer, U. (2022). Role of Logistic Regression in Malware Detection: A Systematic Literature Review. VFAST Transactions on Software Engineering, 10(2), 36–46. https://doi.org/10.21015/vtse.v10i2.963

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free