Akashdeep Bhardwaj | Cybersecurity | Editorial Board Member

Published on by Global Scholar Awards

Dr.  Akashdeep Bhardwaj | Cybersecurity | Editorial Board Member

University of Petroleum and Energy Studies | India

Akashdeep Bhardwaj is a distinguished researcher affiliated with the University of Petroleum and Energy Studies, Dehradun, India, with expertise spanning cybersecurity, intrusion detection, cyber-physical systems security, IoT protection frameworks, and machine-learning-based threat analysis. His research contributions include the development of robust intrusion detection models using statistical feature-selection techniques, elasticsearch-based threat-hunting mechanisms, and advanced security architectures for cyber-physical robotic systems. He has published extensively in high-impact international journals such as Scientific Reports, Eurasip Journal on Information Security, Computers & Security, Egyptian Informatics Journal,Measurement Sensors, and the Journal of Database Management. His interdisciplinary work also includes deep learning applications in medical imaging, particularly diabetic-retinopathy detection using residual networks. In addition to journal publications, he has authored key academic books, including Mastering Cybersecurity: A Practical Guide to Cyber Tools and Techniques (Volume 2) and A Practical Approach to Open Source Intelligence (OSINT) – Volume 1, highlighting his commitment to knowledge dissemination and professional capacity building. With collaborations involving over 100 co-authors worldwide, his work significantly contributes to enhancing digital security, strengthening smart-infrastructure resilience, and advancing next-generation threat-mitigation strategies. His academic influence and research productivity are reflected in his metrics 1,208 citations by 1,097 documents, 110 documents, and an h-index of 21.

Profiles: Google Scholar | Scopus | ORCID | LinkedIn

Featured Publications

1. Security Algorithms for Cloud Computing Bhardwaj, A., Subrahmanyam, G. V. B., Avasthi, V., & Sastry, H. (2016). Security algorithms for cloud computing. Procedia Computer Science, 85, 535–542. Citations: 162

2. Smart IoT and Machine Learning-Based Framework for Water Quality Assessment and Device Component Monitoring Bhardwaj, A., Dagar, V., Khan, M. O., Aggarwal, A., Alvarado, R., Kumar, M., … (2022). Smart IoT and machine learning-based framework for water quality assessment and device component monitoring. Environmental Science and Pollution Research, 29(30), 46018–46036. Citations: 121

3. Penetration Testing Framework for Smart Contract Blockchain Bhardwaj, A., Shah, S. B. H., Shankar, A., Alazab, M., Kumar, M., & Gadekallu, T. R. (2021). Penetration testing framework for smart contract blockchain. Peer-to-Peer Networking and Applications, 14(5), 2635–2650. Citations: 121

4. Machine Learning-Based Regression Framework to Predict Health Insurance Premiums Kaushik, K., Bhardwaj, A., Dwivedi, A. D., & Singh, R. (2022). Machine learning-based regression framework to predict health insurance premiums. International Journal of Environmental Research and Public Health. Citations: 118

5. Ransomware Digital Extortion: A Rising New Age Threat Bhardwaj, A., Avasthi, V., Sastry, H., & Subrahmanyam, G. V. B. (2016). Ransomware digital extortion: A rising new age threat. Indian Journal of Science and Technology, 9(14), 1–5. Citations: 92

Ashfaq Ahmad Najar | Cybersecurity | Best Researcher Award

Published on by Global Scholar Awards

Mr. Ashfaq Ahmad Najar | Cybersecurity | Best Researcher Award

Assistant Professor VIT Bhopal University, Madhya Pradesh India

👨‍💻 Ashfaq Ahmad Najar is an accomplished IT professional and academic, currently serving as an IT Manager and Faculty at VIT Bhopal University, Madhya Pradesh. With a rich background in cyber security, machine learning, and deep learning, he has made significant contributions to the field through his research and publications. Ashfaq is dedicated to advancing knowledge in cybersecurity and has presented his work at various national and international platforms.

 

Profile

Google Scholar

Education

🎓 Ashfaq Ahmad Najar is nearing the completion of his Ph.D. in Computer Science from the Central University of Kerala, having submitted his thesis. He holds a Master’s degree in Information Technology from the Central University of Kashmir and a Bachelor’s degree in Information Technology from the University of Kashmir. His early education was completed at the J&K State Board of School Education.

Experience

💼 Ashfaq has a robust professional background, currently holding the position of IT Manager and Faculty at VIT Bhopal University. He has previously worked as an IT Manager Head and Tutor at KCCSBA Bijbehera, Anantnag, and as a Guest Faculty at Govt Boys Degree College Anantnag. His experience is complemented by his active participation in various workshops, seminars, and hackathons.

Research Interest

🔍 Ashfaq’s research interests are focused on Cyber Security, specifically Distributed Denial of Service (DDoS) attacks, as well as Machine Learning and Deep Learning. His work aims to develop robust systems to detect and mitigate cyber threats, leveraging advanced neural network architectures and machine learning algorithms.

Awards

🏆 Ashfaq has received several accolades, including the UGC-NET 2023 qualification, the GATE 2018 qualification, and the CUK University Fellowship for his Ph.D. research. He was also honored with the Young Researcher Award for his work on DDoS attack detection using MLP and random forest algorithms, and recognized as the best all-rounder in a cricket tournament organized by the Central University of Kerala.

Publications Top Notes

📝 Ashfaq Ahmad Najar has published numerous research articles in prestigious journals. Some of his notable works include:

A novel CNN-based approach for detection and classification of DDoS attacks. Concurrency Computat Pract Exper, 2024, Wiley. Cited by 4 articles

A robust DDoS intrusion detection system using convolutional neural network. Computers and Electrical Engineering, 2024, Elsevier. Cited by 8 articles

Cyber-secure SDN: A CNN-based approach for efficient detection and mitigation of DDoS attacks. Computers & Security, 2024, Elsevier. Cited by 6 articles

DDoS attack detection and mitigation using deep neural network in SDN environment. Computers & Security, 2024, Elsevier. Cited by 3 articles

DDoS attack detection using MLP and random forest algorithms. International Journal of Information Technology, 2022, Springer. Cited by 5 articles