Date of Publication : 29th June 2024

Abstract:Today, information is collected for no specific reason; every machine or individual action is recorded, and thedata can be analyses if required in the future. However, as databecomes more reliable, the issue of trust will surface in periods for inspection by several parties. The data could include confidential or sensitive data the organizations that participate in the process of analysis could misuse. As a result, it makes sense to address data privacy challenges now. Data privacy involves with how to restrict the usage of data according to its importance. For example, someone will tell strangers his or hername but will not reveal his or her mobile phone contact through the outsider seems at comfortable. In up-to-date digital age, data pertaining to privacy is usually applied to essential personal information. Data privacy extends beyond the crucial data of employees and customers from a business standpoint. Because ML utilizes massive data sets to train and evaluate, there is widespread recognition that Intelligence and Machine Learning-powered technology are impeded by concerns about data security. Can this barrier block, however, be transformed into an entry stone Yes, it is conceivable.Consider the scenario that follows: no one can be believed; in this case, Blockchain enter the picture. Blockchain makes useof data, however it does it securely. So, in this work, we're presenting a way for ensuring data security through combiningthe block chain and Machine Learning.

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