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Original Article
Software Framework for Detecting Offline USB-Based Attacks on Standalone Systems
Jessica Magdalin G.K1
Logeshwaran B2
Prabhakaran K3
Sujith B4
Dr. H. Abdul Rauf5
1 2 3 4 Department of Computer Science and Engineering (Cyber Security), United Institute of Technology, Coimbatore, Tamil Nadu, India. 5 Principal, United Institute of Technology, Coimbatore, Tamil Nadu, India.
Published Online: May-June 2026
Pages: 82-90
Cite this article
↗ https://www.doi.org/10.59256/ijire.20260703009
References
1. E. Kaspersky, C. Maslennikov, and D. Nazarov, "USB-based malware propagation: Attack vectors, detection challenges, and
mitigation strategies," in Proc. Virus Bulletin International Conference, Geneva, Switzerland, Oct. 2009, pp. 1–16.
2. C. Kolbitsch, P. M. Comparetti, C. Kruegel, E. Kirda, X. Zhou, and X. Wang, "Effective and efficient malware detection at the end
host," in Proc. 18th USENIX Security Symposium, Montreal, Canada, Aug. 2009, pp. 351–366.
3. R. Lyda and J. Hamrock, "Using entropy analysis to find encrypted and packed malware," IEEE Security & Privacy, vol. 5, no. 2, pp.
40–45, Mar.–Apr. 2007.
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and Distributed System Security Symposium (NDSS), San Diego, USA, Feb. 2009, pp. 1–18.
5. J. Kinable and O. Kostakis, "Malware classification based on call graph clustering," Journal in Computer Virology, vol. 7, no. 4, pp.
233–245, Nov. 2011.
6. H. Li, X. Chen, Y. Wang, and J. Zhang, "Analysis of USB storage device usage and security policy enforcement in enterprise
environments," Computers & Security, vol. 56, pp. 47–62, Jul. 2016.
7. A. Sharma and R. K. Gupta, "A survey of machine learning approaches for offline malware classification in resource-constrained
environments," International Journal of Information Security, vol. 19, no. 3, pp. 311–332, Jun. 2020.
8. S. Raghavan, "Digital forensics and the challenges of standalone and air-gapped system security," Journal of Digital Forensics,
Security and Law, vol. 8, no. 1, pp. 25–45, 2013.
9. M. Sikorski and A. Honig, Practical Malware Analysis: The Hands-On Guide to Dissecting Malicious Software. San Francisco, CA,
USA: No Starch Press, 2012.
10. B. Carrier, File System Forensic Analysis. Upper Saddle River, NJ, USA: Addison-Wesley, 2005.
11. A. Moser, C. Kruegel, and E. Kirda, "Limits of static analysis for malware detection," in Proc. 23rd Annual Computer Security
Applications Conference (ACSAC), Miami Beach, FL, USA, Dec. 2007, pp. 421–430.
12. G. E. Dahl, J. W. Stokes, L. Deng, and D. Yu, "Large-scale malware classification using random projections and neural networks,"
in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver, Canada, May 2013, pp.
3422–3426.
13. I. Kirat, G. Vigna, and C. Kruegel, "BareCloud: Bare-metal analysis-based evasive malware detection," in Proc. 23rd USENIX
Security Symposium, San Diego, CA, USA, Aug. 2014, pp. 287–301.
14. R. Sommer and V. Paxson, "Outside the closed world: On using machine learning for network intrusion detection," in Proc. IEEE
Symposium on Security and Privacy, Oakland, CA, USA, May 2010, pp. 305–316.
15. C. Shannon, "A mathematical theory of communication," The Bell System Technical Journal, vol. 27, no. 3, pp. 379–423, Jul. 1948.
mitigation strategies," in Proc. Virus Bulletin International Conference, Geneva, Switzerland, Oct. 2009, pp. 1–16.
2. C. Kolbitsch, P. M. Comparetti, C. Kruegel, E. Kirda, X. Zhou, and X. Wang, "Effective and efficient malware detection at the end
host," in Proc. 18th USENIX Security Symposium, Montreal, Canada, Aug. 2009, pp. 351–366.
3. R. Lyda and J. Hamrock, "Using entropy analysis to find encrypted and packed malware," IEEE Security & Privacy, vol. 5, no. 2, pp.
40–45, Mar.–Apr. 2007.
4. U. Bayer, P. M. Comparetti, C. Hlauschek, C. Kruegel, and E. Kirda, "Scalable, behavior-based malware clustering," in Proc. Network
and Distributed System Security Symposium (NDSS), San Diego, USA, Feb. 2009, pp. 1–18.
5. J. Kinable and O. Kostakis, "Malware classification based on call graph clustering," Journal in Computer Virology, vol. 7, no. 4, pp.
233–245, Nov. 2011.
6. H. Li, X. Chen, Y. Wang, and J. Zhang, "Analysis of USB storage device usage and security policy enforcement in enterprise
environments," Computers & Security, vol. 56, pp. 47–62, Jul. 2016.
7. A. Sharma and R. K. Gupta, "A survey of machine learning approaches for offline malware classification in resource-constrained
environments," International Journal of Information Security, vol. 19, no. 3, pp. 311–332, Jun. 2020.
8. S. Raghavan, "Digital forensics and the challenges of standalone and air-gapped system security," Journal of Digital Forensics,
Security and Law, vol. 8, no. 1, pp. 25–45, 2013.
9. M. Sikorski and A. Honig, Practical Malware Analysis: The Hands-On Guide to Dissecting Malicious Software. San Francisco, CA,
USA: No Starch Press, 2012.
10. B. Carrier, File System Forensic Analysis. Upper Saddle River, NJ, USA: Addison-Wesley, 2005.
11. A. Moser, C. Kruegel, and E. Kirda, "Limits of static analysis for malware detection," in Proc. 23rd Annual Computer Security
Applications Conference (ACSAC), Miami Beach, FL, USA, Dec. 2007, pp. 421–430.
12. G. E. Dahl, J. W. Stokes, L. Deng, and D. Yu, "Large-scale malware classification using random projections and neural networks,"
in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver, Canada, May 2013, pp.
3422–3426.
13. I. Kirat, G. Vigna, and C. Kruegel, "BareCloud: Bare-metal analysis-based evasive malware detection," in Proc. 23rd USENIX
Security Symposium, San Diego, CA, USA, Aug. 2014, pp. 287–301.
14. R. Sommer and V. Paxson, "Outside the closed world: On using machine learning for network intrusion detection," in Proc. IEEE
Symposium on Security and Privacy, Oakland, CA, USA, May 2010, pp. 305–316.
15. C. Shannon, "A mathematical theory of communication," The Bell System Technical Journal, vol. 27, no. 3, pp. 379–423, Jul. 1948.
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