Mitra Alidoosti | Network Security and Privacy | Editorial Member

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Dr. Mitra Alidoosti | Network Security and Privacy | Editorial Member 

Dr. Mitra Alidoosti | IUST | Iran

Dr. Mitra Alidoosti is a computer engineering researcher specializing in web application security, network security, and business-layer vulnerability analysis, contributing extensively to the advancement of dynamic security testing methods. Her work focuses on detecting complex logical vulnerabilities such as race conditions, session puzzling, and business-layer DoS attacks through innovative black-box and dynamic analysis approaches. She has authored multiple ISI and ISC-indexed publications in reputable journals, addressing web resiliency, semantic security testing, and SIP vulnerability assessment, along with several conference papers on secure protocol design, web penetration testing, and multi-step vulnerability detection. Her expertise spans penetration testing, secure architectural design, and process mining for web applications, supported by deep experience in security frameworks, protocol analysis, and automated testing tools. With 97 citations, an h-index of 5, and an i10-index of 2, she continues to contribute significant research in strengthening the security and reliability of complex web and communication systems.

Profiles: Google Scholar

Featured Publications: 

Mirjalili, M., Nowroozi, A., & Alidoosti, M. (2014). A survey on web penetration test. Advances in Computer Science: An International Journal, 3(6), 107–121.

Alidoosti, M., Nowroozi, A., & Nickabadi, A. (2020). Evaluating the web-application resiliency to business-layer DoS attacks. ETRI Journal, 42(3), 433–445.

Alidoosti, M., & Nowroozi, A. (2020). BLProM: A black-box approach for detecting business-layer processes in the web applications. Journal of Computing and Security (JCS), 6(2), 65–80.

Alidoosti, M., Asgharian, H., & Akbari, A. (2013). Security framework for designing SIP scanner. In 2013 21st Iranian Conference on Electrical Engineering (ICEE) (pp. 1–5).

Alidoosti, M., Nowroozi, A., & Nickabadi, A. (2022). Semantic web Racer: Dynamic security testing of the web application against race condition in the business layer. Expert Systems with Applications, 195, 116569.

Sathiyandrakumar Srinivasan | Network Security | Editorial Board Member

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Mr. Sathiyandrakumar Srinivasan | Network Security | Editorial Board Member

Mr. Sathiyandrakumar Srinivasan | V2 Technologies Inc | United States

Mr. Sathiyandrakumar Srinivasan is an active researcher associated with the Kalasalingam Academy of Research and Education. His scholarly contributions span  research publications, supported by 140 Scopus citations from 19 citing documents, reflecting measurable impact within his research domain. His work demonstrates consistent engagement with emerging scientific problems and collaborative scholarship,  With an h-index of 7, his research outputs show developing influence and continued citation growth, indicating early yet meaningful contributions to the field. His publications, documented within Scopus, highlight his involvement in contemporary academic investigations and his ability to contribute to multi-author, interdisciplinary studies. Overall, his research trajectory positions him as a steadily growing scholar whose work continues to gain recognition through increasing citations and academic reach.

Profile: Scopus | Google Scholar 

Featured Publications : 

Raman, R., Kantari, H., Gokhale, A. A., Elangovan, K., Meenakshi, B., … (2024). Agriculture yield estimation using machine learning algorithms. 2024 International Conference on Automation and Computation (AUTOCOM), 187-191.

Srinivasan, S., Deepalakshmi, P. (2023). Enhancing the security in cyber-world by detecting the botnets using ensemble classification based machine learning. Measurement: Sensors, 25, 100624.

Srinivasan, S., Saravanan, T. R., Ithayan, J. V., Ganesh, E. N., Devi, A. S. (2023). Unleashing the potential of IoT in tackling ocean pollution: A data-driven approach for marine ecosystem conservation. 2023 Second International Conference on Smart Technologies for Smart Nation, 31.

Lakshmi, V. V., Giriprasad, S., Vimal, S. P., Kantari, H., Meenakshi, B., … (2024). Wind power forecasting with support vector machines using sparrow search algorithm. 2024 2nd International Conference on Computer, Communication and Control, 29.

Srinivasan, S., Raman, R., Thacker, C. B., Shrivastava, A. (2023). Smart crosswalk management with vehicle-to-pedestrian communication. 2023 International Conference on Sustainable Communication Networks and Applications, 25.

Zhijie Fan | Network Security Situation Awareness | Best Researcher Award

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Prof. Zhijie Fan | Network Security Situation Awareness | Best Researcher Award

Professor at The Third Research Institute of the Ministry of Public Security | China

Prof. Zhijie Fan is a distinguished cybersecurity scholar and professor at The Third Research Institute of the Ministry of Public Security in Shanghai, China. With over a decade of dedicated research in cyberspace and information security, his work spans IoT security, SDN network security, cyber threat intelligence, and security mechanism design for large-scale data systems. Recognized for his outstanding contributions, he has received multiple national and provincial honors, including the Second Prize of the Ministry of Public Security Scientific and Technological Progress Award and the Shanghai Science and Technology Progress Award.

Professional Profile:

Education: 

Prof. Fan earned his Ph.D. in Cyberspace Security from Tongji University, Shanghai, following a Master’s degree in Computer Science and Technology from Zhejiang University, Hangzhou, and a Bachelor’s degree in Electronics and Information Engineering from Xi’an University of Architecture and Technology. He also completed a part-time Postdoctoral Fellowship in IoT Security at Fudan University, Shanghai and a visiting researcher program in SDN Network Security at the University of Ottawa, Canada.

Experience:

Prof. Fan has served as a Professor at The Third Research Institute of the Ministry of Public Security, focusing on information and cyber security. He has led and contributed to numerous national and provincial research projects, including the National Key R&D Programs of China, the Shanghai Talent Development Fund, and major Ministry of Public Security technology initiatives. His leadership extends beyond research into mentoring young scholars and contributing to security standards and policies at both the regional and national levels.

His distinguished career is marked by prestigious honors, including being named Special Expert by the Shanghai Science and Technology Commission, Academic Leader of Xuhui District, Shanghai, and Special Researcher at the People’s Public Security University of China.

Research Interest:

Prof. Zhijie Fan’s research is deeply rooted in advancing the field of cyber and information security, with a strong emphasis on developing innovative and scalable solutions to address modern security challenges. His core expertise spans IoT security and smart device protection, ensuring the resilience and privacy of interconnected systems, and Software Defined Networking (SDN) security, where he focuses on strengthening the integrity and defense of network infrastructures. He has made significant contributions to cybersecurity situation awareness, leveraging advanced models such as ResMLP and LSTM networks for intelligent threat detection and response. Additionally, Prof. Fan has conducted pioneering work in video surveillance and identity recognition, creating robust methods that integrate static and dynamic identification features for enhanced security applications. His research also addresses large-scale unified log data collection and cross-domain security mechanisms, enabling comprehensive monitoring and coordinated protection across diverse platforms. Central to his work is the integration of AI-driven cyber defense techniques, including graph embedding models, which contribute to the development of next-generation intelligent defense frameworks.

Publications Top Noted:

  • Dynamic Adaptive Mechanism Design and Implementation in VSS for Large-Scale Unified Log Data Collection
    Year: 2024 | Cited: 12

  • Improved Message Mechanism-Based Cross-Domain Security Control Model in Mobile Terminals
    Year: 2024 | Cited: 9

  • Video Surveillance Camera Identity Recognition Method Fused With Multi-Dimensional Static and Dynamic Identification Features
    Year: 2023 | Cited: 21

  • Research on Key Method of Cyber Security Situation Awareness Based on ResMLP and LSTM Network
    Year: 2023 | Cited 18

  • A Bayesian Graph Embedding Model for Link-Based Classification Problems
    Year: 2022 | Cited 45

Conclusion:

Prof. Zhijie Fan’s groundbreaking work in cyber threat intelligence and network security situation awareness positions him as a leading figure in global cybersecurity research. His integration of AI techniques with scalable defense mechanisms addresses urgent modern challenges in IoT, SDN, and large-scale log data security. With an impressive portfolio of national honors and high-impact research contributions, he exemplifies the qualities of a Best Researcher Award recipient. Moving forward, his expertise and leadership will continue to shape the future of intelligent cybersecurity systems at both national and international levels.