Current - Issue
Year 2026 · Volume 5 · Issue 2
Original Article
SKIM-PDF: A Unified IQR–Chi-Squared Adaptive Selection Pipeline for Structural PDF Malware Detection
Madhava Rao Dommeti1
Dr. Golajapu Venu Madhava Rao2
Dr. Yalakala Dinesh Kumar3
Dr. V. G. Prasuna4
1 PG – M.Tech Student, Department of Computer Science and Engineering, Satya Institute of Technology and Management, Vizianagaram, Andhra Pradesh, India. 2 4 Professor, Department of Computer Science and Engineering, Satya Institute of Technology and Management, Vizianagaram, Andhra Pradesh, India. 3 Associate Professor, Department of Computer Science and Engineering, Satya Institute of Technology and Management, Vizianagaram, Andhra Pradesh, India.
Published Online: May-August 2026
Pages: 920-927
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20260502100
References
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17, 2021, pp. 15137–15145.
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6. M. Ijaz, M. H. Durad, and M. Ismail, “Static and dynamic malware analysis using machine learning,” in Proc. 16th Int. Bhurban Conf. Appl.
Sci. Technol. (IBCAST), Jan. 2019, pp. 687–691.
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2012.
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9. M. Abdelsalam, M. Gupta, and S. Mittal, “Artificial intelligence assisted malware analysis,” in Proc. ACM Workshop Secure Trustworthy
CyberPhys. Syst., Apr. 2021, pp. 75–77.
10. W. Wang et al., “BotMark: Automated botnet detection with hybrid analysis of flow-based and graph-based traffic behaviors,” Inf. Sci., vol.
511, pp. 284–296, Feb. 2020.
11. C. Smutz and A. Stavrou, “Malicious PDF detection using metadata and structural features,” in Proc. 28th Annu. Comput. Secur. Appl.
Conf. (ACSAC), Dec. 2012, pp. 239–248.
12. N. Srndic and P. Laskov, “Practical evasion of a learning-based classifier: A case study,” in Proc. IEEE Symp. Secur. Privacy (S&P), May
2014, pp. 197–211.
13. D. Maiorca, G. Giacinto, and I. Corona, “A pattern recognition system for malicious PDF files detection,” in Proc. 8th Int. Conf. Mach.
Learn. Data Mining (MLDM), Jul. 2012, pp. 510–524.
14. C. Vatamanu, D. Gavrilut, and R. Benchea, “Practical malware detection techniques,” in Proc. 10th Int. Conf. Commun. (COMM), May
2014, pp. 1–4.
15. I. Corona, D. Maiorca, and G. Giacinto, “Lux0R: Detection of malicious PDF-embedded JavaScript code through discriminant analysis of
API references,” in Proc. ACM Workshop Artif. Intell. Secur. (AISec), Nov. 2014, pp. 47–57.
document format files,” Secur. Commun. Netw., vol. 2022, pp. 1–10, Sep. 2022.
2. P. Singh, S. Tapaswi, and S. Gupta, “Malware detection in PDF and office documents: A survey,” Inf. Secur. J., Global Perspective, vol.
29, no. 3, pp. 134–153, May 2020.
3. N. Livathinos et al., “Robust PDF document conversion using recurrent neural networks,” in Proc. AAAI Conf. Artif. Intell., vol. 35, no.
17, 2021, pp. 15137–15145.
4. Q. A. Al-Haija, A. Odeh, and H. Qattous, “PDF malware detection based on optimizable decision trees,” Electronics, vol. 11, no. 19, p.
3142, Sep. 2022.
5. Y. Wiseman, “Efficient embedded images in portable document format,” Int. J., vol. 124, pp. 38–129, Jan. 2019.
6. M. Ijaz, M. H. Durad, and M. Ismail, “Static and dynamic malware analysis using machine learning,” in Proc. 16th Int. Bhurban Conf. Appl.
Sci. Technol. (IBCAST), Jan. 2019, pp. 687–691.
7. Y. Alosefer, “Analysing web-based malware behaviour through client honeypots,” Ph.D. dissertation, Cardiff Univ., Cardiff, Wales, U.K.,
2012.
8. N. Idika and A. P. Mathur, “A survey of malware detection techniques,” Purdue Univ., vol. 48, no. 2, pp. 32–46, 2007.
9. M. Abdelsalam, M. Gupta, and S. Mittal, “Artificial intelligence assisted malware analysis,” in Proc. ACM Workshop Secure Trustworthy
CyberPhys. Syst., Apr. 2021, pp. 75–77.
10. W. Wang et al., “BotMark: Automated botnet detection with hybrid analysis of flow-based and graph-based traffic behaviors,” Inf. Sci., vol.
511, pp. 284–296, Feb. 2020.
11. C. Smutz and A. Stavrou, “Malicious PDF detection using metadata and structural features,” in Proc. 28th Annu. Comput. Secur. Appl.
Conf. (ACSAC), Dec. 2012, pp. 239–248.
12. N. Srndic and P. Laskov, “Practical evasion of a learning-based classifier: A case study,” in Proc. IEEE Symp. Secur. Privacy (S&P), May
2014, pp. 197–211.
13. D. Maiorca, G. Giacinto, and I. Corona, “A pattern recognition system for malicious PDF files detection,” in Proc. 8th Int. Conf. Mach.
Learn. Data Mining (MLDM), Jul. 2012, pp. 510–524.
14. C. Vatamanu, D. Gavrilut, and R. Benchea, “Practical malware detection techniques,” in Proc. 10th Int. Conf. Commun. (COMM), May
2014, pp. 1–4.
15. I. Corona, D. Maiorca, and G. Giacinto, “Lux0R: Detection of malicious PDF-embedded JavaScript code through discriminant analysis of
API references,” in Proc. ACM Workshop Artif. Intell. Secur. (AISec), Nov. 2014, pp. 47–57.
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