Idemix based anonymization for home automation systems

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Demir, Simge (2021) Idemix based anonymization for home automation systems. [Thesis]

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Abstract

Lately, the Internet of Things has been a popular research area within academia as well as in the industry. IoT technology has been widely adopted to industry with a variety of applications. Home automation systems (HAS) which helps homeowners to manage their devices remotely is one of these applications. However, smart homes are vulnerable to various network based attacks. Another important threat in HAS is that it is possible to leak private information of homeowners. In this thesis, we propose a privacy-aware anonymous identification and authentication model for HAS. In the proposed scheme, an innovative gateway is presented to build a secure intercommunication platform between IoT devices and the outside users. Besides, the proposed system is privacy-aware with the introduction of fake proofs which aims to protect users’ private information. Anonymity is provided by the Idemix based anonymous credential system where the real identities of the users are hidden. We give implementation details and the results of conducted experiments with downstream and upstream traffic scenarios. Our results suggest that the proposed model is efficient and scalable for home automation systems.
Item Type: Thesis
Uncontrolled Keywords: Internet of Things. -- Home Automation Systems. -- Mutual Authentication. -- Privacy-awareness. -- Anonymous Identification. -- Nesnelerin Interneti. -- Ev Otomasyon Sistemleri. -- Çift Yönlü Dogrulama. -- Gizlilige Duyarlılık. -- Anonim Tanımlama.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics > TK7885-7895 Computer engineering. Computer hardware
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng.
Faculty of Engineering and Natural Sciences
Depositing User: IC-Cataloging
Date Deposited: 18 Oct 2021 15:46
Last Modified: 26 Apr 2022 10:38
URI: https://research.sabanciuniv.edu/id/eprint/42491

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