Work place: Department of Computing Technologies, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu District 603203, Tamil Nadu, India
E-mail: mailtoragug2022@gmail.com
Website:
Research Interests:
Biography
Mr. G. Ragu is a research scholar in the Department of Computing Technologies at SRM Institute of Science and Technology, Kattankulathur Campus, with 13 years of academic and research experience. He holds an M.Tech in Computer Science and Engineering from SRM University, an M.B.A in Banking Technology from Pondicherry University, and a B.Tech in Information Technology from Pondicherry Engineering College. Currently pursuing a Ph.D. in Cloud Security, he has organized and participated in numerous guest lectures, faculty development programs, and conferences. Mr. Ragu holds three patents and is a life member of ISTE, contributing to the NAAC accreditation process and publishing papers in reputed Scopus and Web of Science journals.
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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