An Improvised Framework for Privacy Preservation in IoT

Data privacy is now-a-days a special issue in era of Internet of Things because of the big data stored and transmitted by the public/private devices. Different types and levels of privacy can be provided at different layers of IoT architecture, also different mechanisms operate at different layers of IoT architecture. This article presents the work being done towards the design of a generic framework to integrate these privacy preserving mechanisms at different layers of IoT architecture and can ensure privacy preservation in a heterogeneous IoT environment. The data is classified into different levels of secrecy and appropriate rules and mechanisms are applied to ensure this privacy. The proposed framework is implemented and evaluated for its performance with security and execution time or primary parameters. Various scenarios are also evaluated, and a comparison is done with an existing mechanism ABE (Attribute Based Encryption). It has been found that the proposed work takes less time and is more secure due to short key length and randomness of the parameters used in encryption algorithm.