Poorvadevi Ramamoorthy

Work place: SRM Institute of science and Technology, Kattankulathur, Chengalpattu, India

E-mail: poorvadr@srmist.edu.in

Website:

Research Interests:

Biography

Dr. Poorvadevi Ramamoorthy is currently an Assistant Professor at SCSVMV deemed university in Kanchipuram, with over 12 years of teaching and 7 years of research experience in computer science and engineering. He has published more than 70 research papers in high-impact international journals and 87+ papers in conferences including IEEE and Springer. He completed various certifications in cloud computing and obtained funding for a minor research project. He holds two patents related to IoT and has received multiple awards for innovation and teaching excellence. An active member of several research forums, he has delivered over 32 technical and employability.

Author Articles
Innovative Forensics in IoT Clouds by Leveraging Blockchain for Data Integrity and Security

By Ragu Gnanaprakasam Ramamoorthy Sriramulu Poorvadevi Ramamoorthy Mervin Retnadhas

DOI: https://doi.org/10.5815/ijcnis.2026.01.08, Pub. Date: 8 Feb. 2026

The Internet of Things and cloud computing are expanding at a very rapid rate, which has posed a great challenge in maintaining data security and integrity, particularly during forensic investigation. The conventional logging mechanisms are prone to manipulation, unreliable, and difficult to verify the digital evidence. In response to these problems, a blockchain-based system is suggested to facilitate the security and reliability of forensic data stored on cloud-based environments, which is related to IoT devices. The decentralized storage is paired with the smart contract technology to form an immutable version of the cloud communications to make sure that the evidence is unaltered to guarantee its verifiability. It further has a safe off-chain storage system enabling swift records and recalls of massive forensic records. The enormous amount of experimentation has demonstrated that the system minimizes the verification times to about 28 to 39 milliseconds. It is quicker than the methods that are currently in place and has high data integrity. The framework enhances transaction throughput as well as provides scalable solution to preserve forensic evidence. It has offered a feasible and reliable platform to enhance the security, visibility and reliability of forensic data within intricate IoT and cloud environments. These characteristics aid law enforcement groups and forensic investigators in having effective and credible investigations.

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