An Improvised Framework for Privacy Preservation in IoT

Abstract

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.

Security and Privacy in IoT-Cloud-Based e-Health Systems—A Comprehensive Review

“…Data privacy has been defined several different ways, reflecting divergent perspectives. For example some researchers [15][16][17]23,25,43,45,51,52,54,[58][59][60][61][62]65,68,[70][71][72][73][74][75][76][77][78][79][80][81][82] have focused on data privacy in terms confidential data protection and provided a legal framework with built-in privacy standards, including PbD. Semantha et al [23] analyzed the contemporary PbD frameworks in the health systems to identify the key limitations.…”

“…The integration of PbD can be incorporated into the General Data Protection Regulation (GDPR), which is supported by the European Parliament and Council of the European Union (EU) to unify data protection laws for all data citizens. Moreover, PbD can be used to create a new framework, as shown in References [23,72,75,80]. Data privacy is a foundational concept that is concerned with protecting user data.…”

“…Many researchers have acknowledged the importance of the GDPR. Kubo et al [80], created a system of engineering standards that incorporated elements of GDPR and PbD. This system was widely adopted in both the private and public sectors.…”

“…• Access Control: the ability to access a computer system can be controlled at a hardware level by using a special access device such as a USB thumb drive with a built-in security/authentication key. Access control can also be addressed at the operating system level [6,18,26,33,50,61,65,71,79,80]. • Secure Communications: encryption that utilizes robust algorithms is required to secure system communications.…”

“…Multifunction, multilevel and high- Robust security and privacy measures are essential for the future expansion and sustainability of the cloud computing industry. The most effective security and privacy measure for cloud computing is strict access control as used in Kaliya and Hussain [79,80] presented framework for privacy preservation in IoT through classification and access control mechanism. They indicated security and privacy of user data is a serious issue in IoT that classifies data into a structural format based on its and user and access control lists are created.…”