Basharat Ali | Cybersecurity Data Analysis | Best Researcher Award

Published on by Research Data Analysis

Dr. Basharat Ali | Cybersecurity Data Analysis | Best Researcher Award

Nanjing University | China

Dr. Basharat Ali is a dedicated researcher and PhD scholar in Computer Science at Nanjing University, China, with a strong academic foundation in Software Engineering from Northeastern University, China, and the University of Swat, Pakistan. His professional journey includes roles as a Software Developer at Neusoft (China) and RaidIT Solution (Pakistan), where he gained hands-on expertise in programming, system architecture, and cross-border e-commerce platforms. His research focuses on network security, blockchain development, IoT infrastructure protection, and the integration of deep learning techniques for cyber defense. Dr. Ali has published influential works such as “An Efficient E-Voting Algorithm and DApp Using Blockchain Technology” and “Towards a Secure Infrastructure for the IoT’s Using Deep Learning.” His scholarly contributions have achieved an h-index of 4, with 79 citations and 2 indexed documents, reflecting the growing impact of his work in secure digital ecosystems. He has also been recognized for his innovation and technical creativity in decentralized systems and smart contract applications. Combining academic research with practical software engineering and design expertise, Dr. Ali aims to advance global cybersecurity through intelligent, transparent, and scalable blockchain-based systems that shape the next generation of secure digital environments.

Profiles : Orcid | Google Scholar

Featured Publications

Ali, B., & Chen, G. (2025). Next-generation AI for advanced threat detection and security enhancement in DNS over HTTPS. Journal of Network and Computer Applications.

Ali, B. (2022). An Efficient E-Voting Algorithm and DApp Using Blockchain Technology.

Ali, B. (2021). Towards a Secure Infrastructure for the IoT’s Using Deep Learning. Multidisciplinary International Journal of Research and Development.

Mohammad Zahid | Cybersecurity Data Analysis | Young Scientist Award

Published on by Research Data Analysis

Mr. Mohammad Zahid | Cybersecurity Data Analysis | Young Scientist Award

Jamia Millia Islamia | India

Author Profile

Google Scholar

Mr. Mohammad Zahid

Junior Research Fellow | Ph.D. Scholar in Computer Science | Cybersecurity & AI Researcher

Summary

Mohammad Zahid is a motivated and research-focused computer science professional currently pursuing a Ph.D. in Computer Science at Jamia Millia Islamia, New Delhi. He is working as a Junior Research Fellow (JRF) with a specialization in IoT security, machine learning, deep learning, and federated learning. With strong analytical and technical skills, he is actively engaged in AI-driven cybersecurity research, aiming to develop intelligent systems for threat detection. Zahid is passionate about contributing to innovative and interdisciplinary projects in both academia and the tech industry.

Education

Mr. Zahid is currently enrolled in a Ph.D. program at Jamia Millia Islamia (Central University), New Delhi, with a research focus in computer science and AI. He holds a Master of Computer Applications (MCA) from Maulana Azad National Urdu University (MANUU), Hyderabad, where he graduated with an excellent academic record (87.6%). He also completed a Bachelor of Science (Hons) in Chemistry, Mathematics, and Physics from Aligarh Muslim University (AMU), Aligarh.

Professional Experience

As a Junior Research Fellow, Mr. Zahid is engaged in cutting-edge research related to cybersecurity and artificial intelligence. During his postgraduate studies, he developed a web-based fraud detection system that utilized machine learning algorithms to identify and visualize suspicious banking transactions. His hands-on experience includes technologies such as Java, MySQL, JavaScript, and HTML/CSS, with a strong foundation in data preprocessing and anomaly detection.

Research Interests

Mr. Zahid’s research interests span across IoT security, federated learning, machine learning, and deep learning. His current Ph.D. research is centered on AI-based cybersecurity frameworks, especially for detecting and mitigating threats in decentralized and IoT-based environments. He is particularly interested in applying federated learning models to preserve data privacy while improving detection efficiency in real-world systems.

Honors and Awards

Mr. Zahid was awarded the UGC Junior Research Fellowship (JRF) in Computer Science by the National Testing Agency (NTA) in March 2022, recognizing him among the top national-level researchers eligible for academic and research roles across Indian universities. He also received the Merit-cum-Means Scholarship for Professional Courses from the Ministry of Minority Affairs, Government of India, during his MCA studies (2018–2021), in acknowledgment of his academic performance and financial need.

Publications

 Empowering IoT Networks

Author: M Zahid, TS Bharati

Journal: Artificial Intelligence for Blockchain and Cybersecurity Powered IoT
Year: 2025

Enhancing Cybersecurity in IoT Systems: A Hybrid Deep Learning Approach for Real-Time Attack Detection

Author: M Zahid, TS Bharati
Journal: Discover Internet of Things, Volume 5(1), Page 73
Year: 2025

 Comprehensive Review of IoT Attack Detection Using Machine Learning and Deep Learning Techniques

Author: M Zahid, TS Bharati
Journal: 2024 Second International Conference on Advanced Computing & Communication
Year: 2024

Empowering IoT Networks: A Study on Machine Learning and Deep Learning for DDoS Attack

Author: M Zahid, TS Bharati
Journal: Artificial Intelligence for Blockchain and Cybersecurity Powered IoT
Year: 2025