Randhir Kumar

(Dr. Randhir Kumar) received his Ph.D. in the department of Information Technology from NIT Raipur, India. He completed his Postdoctoral from department of Electrical Engineering, IIT Hyderabad. He is currently working as an Assistant Professor, Department of Computer Science and Engineering, SRM University, AP. He is having 7 years of teaching and 4 years of research experience. He has published his research articles in leading journal and conferences from IEEE, Elsevier, Springer, and John Wiley. His paper has been published in some of the high impact factor journals such as – IEEE Internet of Things, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Network Science and Engineering, IEEE Transactions on Green Communications and Networking, IEEE Transactions on Industrial Informatics, IEEE Intelligent Systems, IEEE Consumer Electronics Magazine, IEEE COMSNETs, IEEE ICC, MobiCom, GlobeCom, Computer Networks, JPDC, and Transactions on Emerging Telecommunications Technologies (ETT Wiley). His paper was recognized as most cited paper of year 2020-2021 in one of the reputed journal i.e., Transactions on Emerging Telecommunications Technologies. He received best paper presentation award in one of the reputed conference i.e., GLOBECOM in the year 2022. He has qualified UGC-NET in the year of 2018. He has been awarded as Best Engineer Trainee by Honeywell Technology, India in the year 2009. He is active reviewer of many of the reputed journals like IEEE TDSC, IEEE TGCN, IEEE TNSM, IEEE TII, IEEE Access, Journal of Super Computing, Journal of Ambient Intelligent and Humanized Computing, and International Journal of Information Security and Privacy, IGI global. His research interest includes Cryptographic Techniques, Information Security, Blockchain Technology, Digital Twin and Services, Machine Learning, and Web Mining. He is also a member of IEEE, IAENG.

Currently, I am investigating Parallel Execution of smart contracts and interoperability challenges in blockchain-enabled frameworks and services.

Recent Updates

Kumar, R., & Tripathi, R. (2019, January). Traceability of counterfeit medicine supply chain through Blockchain. In 2019 11th International Conference on Communication Systems & Networks (COMSNETS) (pp. 568-570). IEEE.
Kumar, R., Marchang, N., & Tripathi, R. (2020, January). Distributed off-chain storage of patient diagnostic reports in healthcare system using IPFS and blockchain. In 2020 International Conference on COMmunication Systems & NETworkS (COMSNETS) (pp. 1-5). IEEE.
Kumar, R., Kumar, P., Tripathi, R., Gupta, G. P., & Kumar, N. (2021). P2SF-IoV: A Privacy-Preservation-Based Secured Framework for Internet of Vehicles. IEEE Transactions on Intelligent Transportation Systems.
Kumar, R., Kumar, P., Tripathi, R., Gupta, G. P., Kumar, N., & Hassan, M. M. (2021). A Privacy-Preserving-Based Secure Framework Using Blockchain-Enabled Deep-Learning in Cooperative Intelligent Transport System. IEEE Transactions on Intelligent Transportation Systems.
Kumar, R., Kumar, P., Tripathi, R., Gupta, G. P., Sahil, G., Mehedi M. H., BDTwin: An Integrated Framework for Enhancing Security and Privacy in Cybertwin-driven Automotive Industrial Internet of Things. IEEE Internet of Things Journal.
Kumar, R., Kumar, P., Kumar, A., Antony, A.,& Zolfaei, A.,. (2022, May). Blockchain and Deep Learning for Cyber Threat-Hunting in Software-Defined Industrial IoT. In IEEE International Conference on Communications 2022 (ICC 2022) IEEE.
Kumar, P., Kumar, R., Kumar, A., Antony, A.,& Zolfaei, A.,. (2022, May). Blockchain and Deep Learning Empowered Secure Data Sharing Framework for Softwarized UAVs. In IEEE International Conference on Communications 2022 (ICC 2022) IEEE.

Notable Contribution

Kumar, R., Kumar, P., Tripathi, R., Gupta, G. P., Islam, N. (2022), Permissioned Blockchain and Deep-Learning for Secure and Efficient Data Sharing in Industrial Healthcare Systems. IEEE Transactions on Industrial Informatics.
Kumar, P., Kumar, R., Gupta, G. P., Tripathi, R., & Srivastava, G. (2022). P2TIF: A Blockchain and Deep Learning Framework for Privacy-preserved Threat Intelligence in Industrial IoT. IEEE Transactions on Industrial Informatics.
Kumar, P., Kumar, R., Kumar, A., Franklin, A. A., Garg, S., & Singh, S. (2022). Blockchain and Deep Learning for Secure Communication in Digital Twin Empowered Industrial IoT Network. IEEE Transactions on Network Science and Engineering.
Kumar, P., Kumar, R., Gupta, G. P., Tripathi, R (2022), BDEdge: Blockchain and Deep-Learning for Secure Edge-Envisioned Green CAVs. IEEE Transactions on Green Communications and Networking. (Rank- Q1, SCIE, IEEE-TGCN)
Kumar, R., Kumar, P., Tripathi, R., Gupta, G. P., Kumar, N., & Hassan, M. M. (2021). A Privacy-Preserving-Based Secure Framework Using Blockchain-Enabled Deep-Learning in Cooperative Intelligent Transport System. IEEE Transactions on Intelligent Transportation Systems.
Kumar, R., Kumar, P., Tripathi, R., Gupta, G. P., & Kumar, N. (2021). P2SF-IoV: A Privacy-Preservation-Based Secured Framework for Internet of Vehicles. IEEE Transactions on Intelligent Transportation Systems.
Kumar, P., Kumar, R., Srivastava, G., Gupta, G. P., Tripathi, R., Gadekallu, T. R., & Xiong, N. (2021). PPSF: A Privacy-Preserving and Secure Framework using Blockchain-based Machine-Learning for IoT-driven Smart Cities. IEEE Transactions on Network Science and Engineering.
Kumar, R., Kumar, P., Tripathi, R., Gupta, G. P., Sahil, G., Mehedi M. H., BDTwin: An Integrated Framework for Enhancing Security and Privacy in Cybertwin-driven Automotive Industrial Internet of Things. IEEE Internet of Things Journal.
Kumar, R., & Tripathi, R. (2021). DBTP2SF: A deep blockchain‐based trustworthy privacy‐preserving secured framework in industrial internet of things systems. Transactions on Emerging Telecommunications Technologies, 32(4), e4222.
Kumar, P., Kumar, R., Gupta, G. P., & Tripathi, R. (2021). A Distributed framework for detecting DDoS attacks in smart contract‐based Blockchain‐IoT Systems by leveraging Fog computing. Transactions on Emerging Telecommunications Technologies, 32(6), e4112.