Privacy Protection and Con Dentiality in Medical IoT

Autor: Anjana George, Poornasree R. Mohan, Gopika G. Nair, Fasila K. A, Anu S. Alunkal
Rok vydání: 2020
Předmět:
Zdroj: Second International Conference on Computer Networks and Communication Technologies ISBN: 9783030370503
DOI: 10.1007/978-3-030-37051-0_3
Popis: The central issue of any IoT device is its security in sharing the sensitive data. Different methods have been proposed for sharing of data from any IoT device. The ranges of security in these methods are different in various IoT architectures. This paper is a comparative study of these security schemes to determine which scheme allows the fastest and most accurate output. Our findings indicate that the attribute matching functions decreases the usage of keys and leads to an efficient key management technique. It helps in the easy addition and searching of the attributes and solves the trouble of complete re-initialization of attributes during updation. Attribute matching functions also reduces the need of large number of keys and is based on hashing of attributes towards a specified position that enhances the security. The authenticated people whose attributes matches with the specified condition can upload and retrieve medical files whereas non-matching attribute holders may be able to request and they cannot download the medical files nor have access to its contents. Since medical world is booming and the associated technology is advancing formerly and protection of the data from tampering and its sharing to various terminals need security enhancing methods and procedures which adds on the relevance of this work.
Databáze: OpenAIRE