Dr. Umang Garg is an academician, presently working as Associate Professor and Cluster Lead Cyber Security & Intelligence at IILM University, Gurugram. He has a rich and diverse experience spanning over 17 years across research, industry, and academia. His primary research area includes IoT Security, IoT Botnet, Artificial Intelligence, and Malware Analysis. As a researcher & author, he has published extensively, contributing to various prestigious journals listed in Scopus & WoS; edited & authored multiple books that address IoT security, and serve as vital resources for students and academicians. 

Educational Qualification 

• Ph.D. CSE, Graphic Era Deemed to be University, Dehradun, India (2023). 
  – A Security Framework for detection, mitigation, and prevention of IoT botnet.
• M.Tech CSE, AKTU, Lucknow, India (2012)
  – CSE (1st Division)
• B.Tech CSE, AKTU, Lucknow, India (2008)
  – CSE (1st Division)

Research and Scholarly Publication

BOOKS

• U. Garg et. al., “Internet of Things Security Attacks, Tools, Techniques and Challenges” in Elsevier publisher, 2025, CRC Press. Available at: https://shop.elsevier.com/books/internet-of-things-security/mishra/978-0-443-33759-8.
• U. Garg et. al., “Anatomy of IoT Botnet and Detection Methods”, authored book in Taylor & Francis Series, 2025. Available at: https://www.routledge.com/Anatomy-of-IoT-Botnets-and-Detection-Methods/Garg-Gupta-Singh-Gehlot-Dumka/p/book/9781041051350.

SCOPUS PUBLICATION

• U. Garg, P. Mishra, N. Gupta, and E. S. Pilli, “IoT botnets Unveiled: architectural analysis, threat vectors, and cutting-edge detection techniques,” Cluster Computing, vol. 28, no. 15, Oct. 2025, doi: 10.1007/s10586-025-05633-1.
• U. Garg et. al., “A research and enhancement strategy for detecting counterfeit medications utilizing blockchain technology,” IET Blockchain, vol. 5, no. 1. Institution of Engineering and Technology (IET), Jan. 2025. doi: 10.1049/blc2.70003.
• U. Garg et al., “An optimized deep learning-based intrusion detection system for IoT botnets using hybrid feature selection”, in Recent Advances in Computational Methods in Science and Technology, CRC Press, 2026. doi: 10.1201/9781003662839.
• U. Garg et. al., “Developing an Intelligent System for Efficient Botnet Detection in IoT Environment,” International Journal of Mathematical, Engineering and Management Sciences, vol. 10, no. 2. Ram Arti Publishers, pp. 537–553, Apr. 01, 2025. doi: 10.33889/ijmems.2025.10.2.027.
• U. Garg et. al., “Prediction and Segmentation of Heart Disease Boosting-Based Machine Learning Algorithms”. Journal of Neonatal Surgery, 14 (5s), 324-334, 2025.
• U. Garg, S. Kumar, and M. Kumar, “INFRDET: IoT network flow regulariser-based detection and classification of IoT botnet,” International Journal of Grid and Utility Computing, vol. 14, no. 6. Inder science Publishers, pp. 606–616, 2023. doi: 10.1504/ijguc.2023.135344.
• U. Garg, S. Kumar, and A. Mahanti, “IMTIBOT: An Intelligent Mitigation Technique for IoT Botnets,” Future Internet, vol. 16, no. 6. MDPI AG, p. 212, Jun. 17, 2024. doi: 10.3390/fi16060212.
• U. Garg, S. Kumar, and M. Kumar, “IHBOT: An Intelligent and Hybrid Model for Investigation and Classification of IoT Botnet,” International Journal of Computer Network and Information Security, vol. 16, no. 5. MECS Publisher, pp. 98–112, Oct. 08, 2024. doi: 10.5815/ijcnis.2024.05.08. 
• Kumar, S., Mehra, R., Sivaraman, H., Garg, U.: A Research and Enhancement Strategy for detecting counterfeit medications utilizing blockchain technology. IET Blockchain 5, e70003(2025). https://doi.org/10.1049/blc2.70003.
• U. Garg, R. S. Pundir, M. Manchanda, N. Gupta, and R. B. Singh, “Sentiments and opinions shared on social media during the COVID-19 pandemic using machine learning techniques,” Hybrid Information Systems. De Gruyter, pp. 71–90, Jul. 08, 2024. doi: 10.1515/9783111331133-005.
• S. Maurya, S. Kumar, U. Garg, and M. Kumar, “An Efficient Framework for Detection and Classification of IoT Botnet Traffic,” ECS Sensors Plus, vol. 1, no. 2. The Electrochemical Society, p. 026401, Jun. 01, 2022. doi: 10.1149/2754-2726/ac7abc.
• N. Gupta, P. K. Juneja, S. Sharma, and U. Garg, “An intelligent technique for network resource management and analysis of 5G-IoT smart healthcare application,” Journal of Autonomous Intelligence, vol. 7, no. 1. Frontier Scientific Publishing Pte Ltd, Oct. 09, 2023. doi: 10.32629/jai.v7i1.694.
• U. Garg, V K Singh, “MHID: Malware Detection Using Hybrid Honeypot and Intrusion Detection System,” Communications on Applied Nonlinear Analysis, vol. 31, no. 2s. Science Research Society, pp. 145–162, May 30, 2024. doi: 10.52783/cana.v31.617.
• U. Garg, N. Gupta, M. Manchanda, and K. Purohit, “Classification and Prediction of Employee Attrition Rate using Machine Learning Classifiers,” 2024 International Conference on Inventive Computation Technologies (ICICT). IEEE, Apr. 24, 2024. doi: 10.1109/icict60155.2024.10544966.
• U. Garg, N. Sharma, S. Appukutti, J. Mukherjee, and S. Mishra, “Analysis of Student’s Academic Performance based on their Time Spent on Extra-Curricular Activities using Machine Learning Techniques,” International Journal of Modern Education and Computer Science, vol. 15, no. 1. MECS Publisher, pp. 46–57, Feb. 08, 2023. doi: 10.5815/ijmecs.2023.01.04.
• U. Garg, S. Kumar, and M. Kumar, “A Hybrid Approach for the Detection and Classification of MQTT-based IoT-Malware,” 2023 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS). IEEE, Mar. 23, 2023. doi: 10.1109/icscds56580.2023.10104820. 
• N. Sharma, M. Sharma, and U. Garg, “Predicting Academic Performance of Students Using Machine Learning Models,” 2023 International Conference on Artificial Intelligence and Smart Communication (AISC). IEEE, Jan. 27, 2023. doi: 10.1109/aisc56616.2023.10085214.
• U. Garg, S. Dhyani, S. Nautiyal, A. Chand, and N. Gupta, “Medical Assistance for Detecting Cataract, Jaundice and Strabismus using Deep Learning,” 2023 IEEE Pune Section International Conference (PuneCon). IEEE, Dec. 14, 2023. doi: 10.1109/punecon58714.2023.10449988.
• U. Garg, V. Kukreti, R. S. Pundir, M. Manchanda, and N. Gupta, “Prediction of Turkey Forest Fire using Random Forest Regressor,” 2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA). IEEE, Mar. 14, 2023. doi: 10.1109/icidca56705.2023.10099565.
• N. Gupta, P. K. Juneja, S. Sharma, and U. Garg, “Future Aspect of 5G-IoT Architecture in Smart Healthcare System,” 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, May 06, 2021. doi: 10.1109/iciccs51141.2021.9432082.
• U. Garg, S. Kumar, and M. Ghanshala, “Analysis and Categorization of Emotet IoT Botnet Malware,” 2023 International Conference on Artificial Intelligence and Smart Communication (AISC). IEEE, Jan. 27, 2023. doi: 10.1109/aisc56616.2023.10085302.
• U. Garg, and V. Kukreja, “Advances in Skin Disease Recognition: Hybrid Deep Learning and Ensemble Models for Accurate Classification,” 2023 4th IEEE Global Conference for Advancement in Technology (GCAT). IEEE, Oct. 06, 2023. doi: 10.1109/gcat59970.2023.10353466.
• U. Garg, S. Dutta, A. Gupta, S. S. Rawat, A. Gupta, and N. Gupta, “An Efficient and Resilient Technique for Malware Detection,” 2023 International Conference on the Confluence of Advancements in Robotics, Vision and Interdisciplinary Technology Management (IC-RVITM). IEEE, Nov. 28, 2023. doi: 10.1109/ic-rvitm60032.2023.10435092.
• A. Gandhi, S. Singh, N. Verma, U. Garg, and A. Garg, “An Efficient Virtual Decentralized Cloud Load Balancing (VDCLB),” 2023 Annual International Conference on Emerging Research Areas: International Conference on Intelligent Systems (AICERA/ICIS). IEEE, Nov. 16, 2023. doi: 10.1109/aicera/icis59538.2023.10420318.
• U. Garg, M. Kaur, M. Kaushik, and N. Gupta, “Detection of DDoS Attacks using Semi-Supervised based Machine Learning Approaches,” 2021 2nd International Conference on Computational Methods in Science & Technology (ICCMST). IEEE, Dec. 2021. doi: 10.1109/iccmst54943.2021.00033.   
• U. Garg, P. Mishra, R.C. Joshi, “A Layered Internet of Things (IoT) Security Framework: Attacks, Counter Measures and Challenges”, Cloud Network Management, pp 23, 2020, Taylor and Francis. 
• U. Garg, Urmila, R. S. Pundir, M. Manchanda, and N. Gupta, “Identification and Prediction of Hepatitis B and NAFLD using Machine Learning,” 2023 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS). IEEE, Mar. 23, 2023. doi: 10.1109/icscds56580.2023.10104875.
• H. Sivaraman, U. Garg, A. Gupta, N. Sharma, and A. Sharma, “Performance Evaluation and Analysis of IoT Network using KNN and SVM,” 2023 International Conference on Device Intelligence, Computing and Communication Technologies, (DICCT). IEEE, Mar. 17, 2023. doi: 10.1109/dicct56244.2023.10110194.
• U. Garg, V. Kaushik, A. Panwar, and N. Gupta, “Analysis of Machine Learning Algorithms for IoT Botnet,” 2021 2nd International Conference for Emerging Technology (INCET). IEEE, May 21, 2021. doi: 10.1109/incet51464.2021.9456246.
• A. K. Mishra, N. Kumar Pandey, V. Kumar, U. Garg, and M. Singh, “Detection of Ships in The Ocean Using Deep Learning Algorithm,” 2022 2nd International Conference on Innovative Sustainable Computational Technologies (CISCT). IEEE, Dec. 23, 2022. doi: 10.1109/cisct55310.2022.10046587.
• A. Sinha, S. Kumar, P. Mishra, U. Garg, and A. Agwarwal, “A Review and Case Study on Attacking and Security Tools at Application-Layer of IoT,” Advances in Intelligent Systems and Computing. Springer International Publishing, pp. 51–63, 2021. doi: 10.1007/978-3-030-76736-5_6.
•  U. Garg, S. Kumar, and M. Kumar, “A Hybrid Approach for the Detection and Classification of MQTT-based IoT-Malware,” 2023 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS). IEEE, Mar. 23, 2023. doi: 10.1109/icscds56580.2023.10104820.
• N. Sharma, M. Sharma, and U. Garg, “Predicting Academic Performance of Students Using Machine Learning Models,” 2023 International Conference on Artificial Intelligence and Smart Communication (AISC). IEEE, Jan. 27, 2023. doi: 10.1109/aisc56616.2023.10085214.
• N. Gupta, S. Sharma, P. Juneja, and U. Garg, “A Network Data Analytic Technique in a 5G-IoT-Based Smart Healthcare System Using Machine Learning,” Advances in Computer and Electrical Engineering. IGI Global, pp. 81–93, Jun. 03, 2022. doi: 10.4018/978-1-6684-3855-8.ch003.
• S. Rana, U. Garg, and N. Gupta, “Intelligent Traffic Monitoring System Based on Internet of Things,” 2021 International Conference on Computational Performance Evaluation (ComPE). IEEE, Dec. 01, 2021. doi: 10.1109/compe53109.2021.9752045.
• U. Garg, H. Sivaraman, A. Bamola, and P. Kumari, “To Evaluate and Analyze the Performance of Anomaly Detection in Cloud of Things,” 2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, Oct. 03, 2022. doi: 10.1109/icccnt54827.2022.9984316.
• N. Gupta, S. Sharma, P. K. Juneja, and U. Garg, “SDNFV 5G-IoT: A Framework for the Next Generation 5G enabled IoT,” 2020 International Conference on Advances in Computing, Communication & Materials (ICACCM). IEEE, pp. 289–294, Aug. 21, 2020. doi: 10.1109/icaccm50413.2020.9213047.
• Paper published in UCOST conference on “A review based on Environmental and Agricultural application of UAV” in March 2018.
• U. Garg, K. K. Ghanshala, R. C. Joshi, and R. Chauhan, “Design and Implementation of Smart Wheelchair for Quadriplegia patients using IOT,” 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC). IEEE, Dec. 2018. doi: 10.1109/icsccc.2018.8703354. 
•  “MAC AND LOGICAL ADDRESSING (A REVIEW STUDY) in IJERA, ISSN: 2248-9622, Vol. 2 ISSUE 3, May-JUNE 2012, PP. 474-480.
• “Simulation of AODV & AOMDV using SCMAC & proposed solution to improve throughput in MANET” in IJSER, ISSN: 2229-5518, Vol. 4 Issue 6 June-2013, PP. 2065-2071.
• A study on Graphical password authentication techniques, Umang Garg, National Conference on Emerging trends in Engineering and Technology, Nov 7-8, 2014.
• U. Garg, P. Mishra, R. C. Joshi, “A Layered Internet of Things (IoT) Security Framework: Attacks, Counter Measures and Challenges,” Taylor & Francis CRC Press, ISBN- 978-0-367-25605-0, pp. 1–22 2020.
• N. Gupta, S. Sharma, P. Juneja, and U. Garg, “A Network Data Analytic Technique in a 5G-IoT-Based Smart Healthcare System Using Machine Learning,” Advances in Computer and Electrical Engineering. IGI Global, pp. 81–93, Jun. 03, 2022. doi: 10.4018/978-1-6684-3855-8.ch003.