A PRIVACY-PRESERVING MACHINE LEARNING FRAMEWORK FOR RELIABLE INDUSTRIAL IOT APPLICATIONS

The Industrial Internet of Things (IIoT) is revolutionizing many vital industries, including electricity, transportation, energy, construction, and agriculture. Machine learning techniques are used to gain understanding of procedures within an IT architecture. In many cases, IoT network unit centers gain an unusual advantage by decreasing their vulnerability to illegal access by hackers. IIoT models must incorporate a wide range of practical scenarios. One factor to examine is the adoption of security measures and their practical importance. The solution uses PriModChain, a combination of differential protection, the Ethereum blockchain, and uniform machine learning, to assure the safety and security of IIoT data. As a result, safety will be jeopardized. To solve the situation, we employ the PriMod chain, which ensures that everyone is safe and follows the rules. Python and connection programming are used in the design of this system on crucial personal computers.