• Journal of Platform Technology
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• v.12 no.1
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• pp.77-84
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• 2024

With the recent increase in the use of artificial intelligence, AI TRiSM data management within organizations has become important, and thus securing data reliability has emerged as an essential requirement for data-based decision-making. Digital content is transmitted through the unreliable Internet to the cloud where the digital content storage is located, then used in various applications. When detecting anomaly of data, it is difficult to provide a function to check content modification due to its damage in digital content systems. In this paper, we design a technique to guarantee the reliability of video data by expanding the function of data annotation. The designed annotation technique constitutes a prototype based on gRPC to handle a request and a response in a webUI that generates classification label and Merkle tree of given video data.