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.

Pardeep Kumar | Network Security and Privacy | Editorial Member

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Assi. Pro. Dr. Pardeep Kumar | Network Security and Privacy | Editorial Member

Assi. Pro. Dr. Pardeep Kumar | Anurag University | India 

Assi. Pro. Dr. Pardeep Kumar is an active researcher in artificial intelligence, machine learning, cybersecurity, edge computing, and intelligent healthcare systems, with contributions spanning advanced encryption, blockchain-based medical systems, wireless sensor networks, Industry 4.0 security, medical data privacy, and applied data analytics. His work includes notable studies on lightweight privacy-preserving mechanisms using elliptic curve cryptography, AI-driven optimization for edge-computing federations, clinical data analysis, smart agriculture using IoT, adaptive image enhancement, and machine-learning-based fault prediction. He has also contributed patents in medical and pollution-monitoring technologies, along with research on distributed agile software development, cloud resource sharing, and neural-network-driven secure communication systems. With 247 Scopus citations, 13 Scopus-indexed documents, and an h-index of 6, his research demonstrates a consistent impact across interdisciplinary computing domains, particularly in secure intelligent systems and data-driven solutions.

Profiles: Scopus | Orcid 

Featured Publications : 

Behaviour-constrained support vector machines for fMRI data analysis. (2023). AIP Conference Proceedings. DOI: 10.1063/5.0109861.

Certain investigation of clinical nursing analysis and the embedded web medical system. (2022). Journal of Pharmaceutical Negative Results.

A decentralized secured grid integration system using APEBC technique with multi access AI framework. (2022). Sustainable Computing: Informatics and Systems. DOI: 10.1016/j.suscom.2022.100777.

Multi-objective optimization of AI driven mechanism algorithm for dynamic application deployment in federations of edge computing. (2022). NeuroQuantology.

Task allocation in distributed agile software development using machine learning approach. (2021). International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON). DOI: 10.1109/centcon52345.2021.9688114.