Malware Detection Using Machine Learning Algorithms

Authors

  • Yash Tiwari Department of Computer Science & Engineering, Goel Institute of Technology and Management, Lucknow, Uttar Pradesh, India Author
  • Soheb Ansari Department of Computer Science & Engineering, Goel Institute of Technology and Management, Lucknow, Uttar Pradesh, India Author
  • Arman Raja Department of Computer Science & Engineering, Goel Institute of Technology and Management, Lucknow, Uttar Pradesh, India Author
  • Ayush Upadhay Department of Computer Science & Engineering, Goel Institute of Technology and Management, Lucknow, Uttar Pradesh, India Author
  • Ms. Namita Srivastava Department of Computer Science & Engineering, Goel Institute of Technology and Management, Lucknow, Uttar Pradesh, India Author

DOI:

https://doi.org/10.32628/IJSRSET251252

Abstract

With the exponential growth of internet-connected devices, malware has become a pressing cybersecurity threat. Traditional signature-based methods struggle to detect new or evolving malware, motivating the integration of machine learning (ML) into detection systems. This paper explores the application of various ML algorithms in malware detection, comparing their performance, accuracy, and implementation challenges. A structured approach combining data preprocessing, feature extraction, model training, and evaluation is discussed. Results show that ML-based approaches significantly improve detection accuracy and adaptability against novel threats.

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References

Anderson, H. S., & Roth, P. (2016). EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models.

Saxe, J., & Berlin, K. (2015). Deep neural network based malware detection using two dimensional binary program features.

Raff, E., et al. (2018). Malware detection by eating a whole exe.

Ye, Y., Li, T., Adjeroh, D., & Iyengar, S. S. (2017). A survey on malware detection using data mining techniques.

Souri, A., & Hosseini, R. (2018). A state-of-the-art survey of malware detection approaches using data mining techniques. Human-centric Computing and Information Sciences, 8(1), 1-22. https://doi.org/10.1186/s13673-018-0145-x.

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Published

26-05-2025

Issue

Section

Research Articles

How to Cite

[1]
Yash Tiwari, Soheb Ansari, Arman Raja, Ayush Upadhay, and Ms. Namita Srivastava, “Malware Detection Using Machine Learning Algorithms”, Int J Sci Res Sci Eng Technol, vol. 12, no. 3, pp. 442–446, May 2025, doi: 10.32628/IJSRSET251252.