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- Vol. 6 Issue 2
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The Digital Iliad: A Comparative Analysis of Trojan War Strategy and AI-Driven Malware Detection Frameworks
Authors
Assistant Professor, Department of English, Sri Krishna Adithya College of Arts and Science, Coimbatore, Tamilnadu, India.
Article Information
- Published In
- Volume 6, Issue 2 (2026)
- Published Online
- March-April 2026
- Pages
- 38-41
- Article Type
- Original Article
References
1. Ab Razak, Mohd Faizal, et al. "Trojan Horse Detection Using Machine Learning Algorithms." Journal of Cybersecurity and Privacy, vol.
2, no. 1, 2022, pp. 12-28.
2. Abualhaj, Mohammad M., et al. "Memory-Based Trojan Detection Using Decision Tree Classifiers." Computers & Security, vol. 138,
2024, pp. 103-115.
3. Ahuja, Ravinder, and Swapnil Salunke. "Hybrid Machine Learning and Blockchain Framework for Enhanced Threat Detection."
International Journal of Information Security, vol. 24, no. 2, 2025, pp. 45-62.
4. Azeem, Muhammad, et al. "Comparative Analysis of Machine Learning Classifiers for Malware Classification." IEEE Access, vol. 12,
2024, pp. 14210-25.
5. Chen, Xiao, et al. "The Evolution of Zero-Day Attacks and the Inadequacy of Signature-Based Detection." Journal of Network Security,
vol. 15, no. 3, 2019, pp. 210-25.
6. Homer. The Iliad. Translated by Robert Fagles, Penguin Books, 1990.
7. ---. The Odyssey. Translated by Robert Fagles, Penguin Books, 1996.
8. Kamboj, Sandeep, et al. "Multi-Malware Detection Using File-Based Feature Extraction and Machine Learning." Cybersecurity and
Intelligence, vol. 6, no. 1, 2023, pp. 88-104.
9. Kumar, Pawan, et al. "Ensemble Learning for Malware Detection: A Study on Random Forest and XGBoost." Advanced Computing
Reports, vol. 9, no. 4, 2024, pp. 56-72.
10. Öztürk, Mustafa, and Serkan Hızal. "Evaluation of Machine Learning Models on the CIC-MalMem-2022 Dataset for Obfuscated Malware
Detection." Data Science and Cybersecurity Review, vol. 11, no. 2, 2024, pp. 34-49.
11. Singh, Abhishek, et al. "Advanced Evasion Techniques in Modern Malware: A Survey." Security and Communication Networks, vol.
2019, 2019, pp. 1-18.
12. Singh, Rahul, et al. "Bypassing AI-Based Malware Detectors through API-Call Manipulation." Journal of Forensic Informatics, vol. 13,
no. 1, 2025, pp. 12-29.
13. Song, Jianguo, et al. "Deep Learning for Malware Detection: A 72-Study Systematic Literature Review." Journal of Big Data, vol. 12, no.
1, 2025, pp. 45-70.
14. Talukder, Md. Alamin, and Sharmin Talukder. "Exploratory Data Analysis and Machine Learning for Dynamic Trojan Detection."
International Journal of Computer Science & Engineering, vol. 14, no. 3, 2025, pp. 201-15.
15. Tanikonda, Sumanth, et al. "The Shift toward AI-Driven (AID) Malware: Autonomously Bypassing Security Paradigms." Cyber
Resilience Quarterly, vol. 7, no. 2, 2025, pp. 101-18.
16. Virgil. The Aeneid. Translated by Robert Fitzgerald, Vintage Classics, 1990.
17. Wang, Haoyu, et al. "Taxonomies of Malware and Their Propagation Vectors in Modern Networks." Computing Surveys, vol. 53, no. 4,
2020, pp. 1-35.
2, no. 1, 2022, pp. 12-28.
2. Abualhaj, Mohammad M., et al. "Memory-Based Trojan Detection Using Decision Tree Classifiers." Computers & Security, vol. 138,
2024, pp. 103-115.
3. Ahuja, Ravinder, and Swapnil Salunke. "Hybrid Machine Learning and Blockchain Framework for Enhanced Threat Detection."
International Journal of Information Security, vol. 24, no. 2, 2025, pp. 45-62.
4. Azeem, Muhammad, et al. "Comparative Analysis of Machine Learning Classifiers for Malware Classification." IEEE Access, vol. 12,
2024, pp. 14210-25.
5. Chen, Xiao, et al. "The Evolution of Zero-Day Attacks and the Inadequacy of Signature-Based Detection." Journal of Network Security,
vol. 15, no. 3, 2019, pp. 210-25.
6. Homer. The Iliad. Translated by Robert Fagles, Penguin Books, 1990.
7. ---. The Odyssey. Translated by Robert Fagles, Penguin Books, 1996.
8. Kamboj, Sandeep, et al. "Multi-Malware Detection Using File-Based Feature Extraction and Machine Learning." Cybersecurity and
Intelligence, vol. 6, no. 1, 2023, pp. 88-104.
9. Kumar, Pawan, et al. "Ensemble Learning for Malware Detection: A Study on Random Forest and XGBoost." Advanced Computing
Reports, vol. 9, no. 4, 2024, pp. 56-72.
10. Öztürk, Mustafa, and Serkan Hızal. "Evaluation of Machine Learning Models on the CIC-MalMem-2022 Dataset for Obfuscated Malware
Detection." Data Science and Cybersecurity Review, vol. 11, no. 2, 2024, pp. 34-49.
11. Singh, Abhishek, et al. "Advanced Evasion Techniques in Modern Malware: A Survey." Security and Communication Networks, vol.
2019, 2019, pp. 1-18.
12. Singh, Rahul, et al. "Bypassing AI-Based Malware Detectors through API-Call Manipulation." Journal of Forensic Informatics, vol. 13,
no. 1, 2025, pp. 12-29.
13. Song, Jianguo, et al. "Deep Learning for Malware Detection: A 72-Study Systematic Literature Review." Journal of Big Data, vol. 12, no.
1, 2025, pp. 45-70.
14. Talukder, Md. Alamin, and Sharmin Talukder. "Exploratory Data Analysis and Machine Learning for Dynamic Trojan Detection."
International Journal of Computer Science & Engineering, vol. 14, no. 3, 2025, pp. 201-15.
15. Tanikonda, Sumanth, et al. "The Shift toward AI-Driven (AID) Malware: Autonomously Bypassing Security Paradigms." Cyber
Resilience Quarterly, vol. 7, no. 2, 2025, pp. 101-18.
16. Virgil. The Aeneid. Translated by Robert Fitzgerald, Vintage Classics, 1990.
17. Wang, Haoyu, et al. "Taxonomies of Malware and Their Propagation Vectors in Modern Networks." Computing Surveys, vol. 53, no. 4,
2020, pp. 1-35.
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