An Effective Machine Learning-Based File Malware Detection—A Survey

  • Ashwin A. Kumar
  • G. P. Anoosh
  • M. S. Abhishek
  • C. Shraddha
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 637)


The objective of this paper is to enable computers to learn on their own, identify malicious activities, increase scanner efficiency and sensitivity. The machine learning algorithm enables the identification of patterns in observed data, the development of models that explains the world and the prediction of things without explicitly preprogrammed rules and models. There have been huge research interests in the cybersecurity industry as well as in universities in the subjects of how to effectively block malicious documentation without a sign of slowing down. The main aim of the paper is to investigate the efficiency of large files and increase sensitivity in malware detection.


Malware Machine learning Scanner Vulnerabilities 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Ashwin A. Kumar
    • 1
  • G. P. Anoosh
    • 1
  • M. S. Abhishek
    • 1
  • C. Shraddha
    • 1
  1. 1.Department of Computer Science and EngineeringVidyavardhaka College of EngineeringMysuruIndia

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