Rahul Gupta

Dr. Rahul Gupta is a faculty member in the Department of Information Technology at Delhi Technological University( Formerly known as Delhi College of Engineering). He earned a Doctorate degree in the Design and Development of Malware Analysis Techniques for Android-Based Smart Devices from the Department of Information Technology, Delhi Technological University. He has completed his M.Tech in Computer Engineering from the National Institute of Technology in 2013.   He has also completed his B.Tech in Computer Engineering from Kurukshetra University in 2011.

His research centers on mobile security, malware analysis (particularly Android), and cybersecurity — with significant overlap into artificial intelligence, machine learning, and social media mining. He explores how to use data-driven methods to detect malicious software on mobile devices and secure mobile platforms against evolving threats, applying AI/ML techniques to improve the detection of malware and vulnerabilities.  Additionally, his interest in semantic web and social media mining  address security and privacy concerns in online/social data environments, combining security research with data-mining and intelligence methods

• Department of Information Technology, Delhi Technological University, New Delhi, India  December 2020- Present as Assistant Professor
• Deaprtment of Computer Science Engineering, Delhi Technological University, New Delhi, India  July 2014-  November 2020 as  Assistant Professor
• Lovely Professional University, July 2013 - May 2014 as Assistant Professor.

• Angorithm Design Analysis
• Theory of Computation / Principles of Computing
• Secure Coding
• C Programming
• Ethical Hacking
• Artificial Intelligence
• Information and Network Security
• Operating Systems

Life Time CSI membership

• Gupta, R., Sharma, K., & Garg, R. K. (2024, December). Technique Based on Process Memory Dump Files. In Proceedings of Fifth International Conference on Computing, Communications, and Cyber-Security: IC4S'05 Volume 2 (Vol. 1128, p. 195). Springer Nature.
• Sahu, M. K., & Gupta, R. (2024, August). Android Malware Detection Using Graphical Technique. In 2024 IEEE 5th India Council International Subsections Conference (INDISCON) (pp. 1-6). IEEE.
• Shukla, A., & Gupta, R. (2024, August). Important Feature Filtering in IoT Network Traffic to Enhance ML-based Classification. In 2024 IEEE 5th India Council International Subsections Conference (INDISCON) (pp. 1-6). IEEE.
• Ritu, Bharmjeet, Das, A., Gupta, R., & Chandra, P. (2024). Nanoscience in controlled drug release in the gastrointestinal tract. In Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases (pp. 3-1). Bristol, UK: IOP Publishing.
• Gupta, R., Sharma, K., & Garg, R. K. (2024). Covalent Bond Based Android Malware Detection Using Permission and System Call Pairs. Computers, Materials & Continua, 78(3).
• Gupta, R., Sharma, K., & Garg, R. K. (2024). Innovative approach to android malware detection: prioritizing critical features using rough set theory. Electronics, 13(3), 482.
• Gupta, R., Sharma, K., & Garg, R. K. (2023, December). Android Malware Detection based on Feature-pair Bonding: A Hybrid Detection Model. In 2023 5th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) (pp. 1377-1380). IEEE.
• Gupta, R., Sharma, K., & Garg, R. K. (2023, December). A Visual Android Malware Detection Technique Based on Process Memory Dump Files. In International Conference on Cognitive Computing and Cyber Physical Systems (pp. 195-203). Singapore: Springer Nature Singapore.
• Sehrawat, N., Shandilya, P., Kumar, P., & Gupta, R. (2022). Malware Family Classification Using Music Information Retrieval Techniques. In ICT with Intelligent Applications: Proceedings of ICTIS 2022, Volume 1 (pp. 221-230). Singapore: Springer Nature Singapore.
• Sehrawat, N., Shandilya, P., Kumar, P., & Gupta, R. (2022). Malware Family Classification Using Music Information Retrieval Techniques. In ICT with Intelligent Applications: Proceedings of ICTIS 2022, Volume 1 (pp. 221-230). Singapore: Springer Nature Singapore.
• Chandok, A., Verma, A., & Gupta, R. (2022, May). Dro-Mal Detector: A Novel Method of Android Malware Detection. In 2022 3rd International Conference for Emerging Technology (INCET) (pp. 1-9). IEEE.
• Aggarwal, N., Aggarwal, P., & Gupta, R. (2022, March). Static malware analysis using pe header files api. In 2022 6th International Conference on Computing Methodologies and Communication (ICCMC) (pp. 159-162). IEEE.
• Gupta, R., Agarwal, A., Dua, D., & Yadav, A. (2021). Android Malware Detection Using Extreme Learning Machine Optimized with Swarm Intelligence. In Cyber Security and Digital Forensics: Proceedings of ICCSDF 2021 (pp. 31-43). Singapore: Springer Singapore.
• Chauhan, D., Singh, H., Hooda, H., & Gupta, R. (2021, August). Classification of malware using visualization techniques. In International Conference on Innovative Computing and Communications: Proceedings of ICICC 2021, Volume 3 (pp. 739-750). Singapore: Springer Singapore.
• Gupta, R., Dabas, G., Yadav, H., & Hasnain, N. (2021, May). QnA System on Educational Textbooks: Digital Library Doubt Support System. In 2021 2nd International Conference for Emerging Technology (INCET) (pp. 1-4). IEEE.
• Gupta, R., Yadav, J., & Kapoor, C. (2021, January). Music information retrieval and intelligent genre classification. In Proceedings of International Conference on Intelligent Computing, Information and Control Systems: ICICCS 2020 (pp. 207-224). Singapore: Springer Singapore.
• Gupta, R., Koli, N., Mahor, N., & Tejashri, N. (2020, June). Performance analysis of machine learning classifier for predicting chronic kidney disease. In 2020 International Conference for Emerging Technology (INCET) (pp. 1-4). IEEE.
• Gupta, R., Kapoor, C., & Yadav, J. (2020, June). Acceptance towards digital payments and improvements in cashless payment ecosystem. In 2020 International Conference for Emerging Technology (INCET) (pp. 1-9). IEEE.
• Gupta, R., Hooda, P., & Chikkara, N. K. (2020, May). Natural Language Processing based Visual Question Answering Efficient: an EfficientDet Approach. In 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS) (pp. 900-904). IEEE.
• Gupta, R., Kumar, J., & Agrawal, H. (2020, May). A statistical approach for sarcasm detection using Twitter data. In 2020 4th international conference on intelligent computing and control systems (ICICCS) (pp. 633-638). IEEE.
• Gupta, R., Yadav, N., Sharma, N., & Garg, R. (2020, May). Analyzing Fuzzy Phrases for Emotion Detection Using Distance Based Approach. In International Conference on Information, Communication and Computing Technology (pp. 172-180). Singapore: Springer Singapore.
• Gupta, R. (2018). Cross-Layered Design in WSN to Enhance Transmission Reliability.
• Gupta, R., & Kumar, A. (2017, August). An intelligent information retrieval system for finding contextual information on twitter. In 2017 International Conference on Innovations in Control, Communication and Information Systems (ICICCI) (pp. 1-5). IEEE.
• Gupta, R., & Ranga, V. K. (2013). Cross-layering in WSN: A Survey. International Journal of Science, Engineering and Computer Technology, 3(1), 48.

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