Distribution and tracking current live location of recognised criminal face at decentralised blockchain through image
by Sana Zeba; Mohammad Amjad
International Journal of Internet Protocol Technology (IJIPT), Vol. 16, No. 3, 2023

Abstract: In the current era, the Internet of Things (IoT), Blockchain Technology and Face recognition are the most emergent technologies to make more advanced and smart cities. In our day-to-day life, security and recognition play a significant position, and managing those securities and recognition is vital for the service providers. Major parts of security depend on passwords, encryption, recognition, secure storage, etc. To prevent any criminal of IoT applications or for preventing any unethical activities of IoT applications, there is a need for a strong secure network. Here, we have designed an algorithm to store with time stamping and signature as well as a live location tracking algorithm to enhance the security of the IoT recognition system through decentralised blockchain storage. In the Blockchain server, we have proposed a decentralised solution to find the live location of the recognised criminal face through which we can prevent any wrong activities furthermore. We have stored the recognised information on blockchain storage and used the time stamping, signature, and transaction of blockchain to ensure the security and track the current location of the criminal face with the blockchain. Hence, through storage at the decentralised server criminal information is in the immutable form on the server and ensures the guarantee of data security at an extended level. In the result, the accuracy, real-time criminal location, and the execution time of the output were all assessed using the ORL datasets and self-created datasets. The current live location tracking rate was approximately 99%, while the average accuracy was around 98%. At various sizes and DPI combinations, the elapsed time and execution times were also assessed.

Online publication date: Fri, 25-Aug-2023

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