Seymen, Beste and Karaoğlan Altop, Duygu and Levi, Albert (2020) Augmented randomness for secure key agreement using physiological signals. In: IEEE Conference on Communications and Network Security (CNS), Avignon, France
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Official URL: https://dx.doi.org/10.1109/CNS48642.2020.9162286
Abstract
With the help of technological advancements in the last decade, it has become much easier to extensively and remotely observe medical conditions of the patients through wearable biosensors that act as connected nodes on Body Area Networks (BANs). Sensitive nature of the critical data captured and communicated via wireless medium makes it extremely important to process it as securely as possible. In this regard, lightweight security mechanisms are needed to overcome the hardware resource restrictions of biosensors. Random and secure cryptographic key generation and agreement among the biosensors take place at the core of these security mechanisms. In this paper, we propose the SKA-PSAR (Augmented Randomness for Secure Key Agreement using Physiological Signals) system to produce highly random cryptographic keys for the biosensors to secure communication in BANs. Similar to its predecessor SKAPS protocol by Karao· g lan Altop et al., SKA-PSAR also employs physiological signals, such as heart rate and blood pressure, as inputs for the keys and utilizes the set reconciliation mechanism as basic building block. Novel quantization and binarization methods of the proposed SKA-PSAR system distinguish it from SKA-PS by increasing the randomness of the generated keys. Additionally, SKA-PSAR generated cryptographic keys have distinctive and time variant characteristics as well as long enough bit sizes that provides resistance against cryptographic attacks. Moreover, correct key generation rate is above 98% with respect to most of the system parameters, and false key generation rate of 0% have been obtained for all system parameters.
Item Type: | Papers in Conference Proceedings |
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Uncontrolled Keywords: | Bio-cryptography; Body Area Networks; Cryptographic Key Generation; Key Agreement; Physiological Signals |
Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng. Foundations Development Faculty of Engineering and Natural Sciences |
Depositing User: | Duygu Karaoğlan Altop |
Date Deposited: | 03 Aug 2023 21:08 |
Last Modified: | 03 Aug 2023 21:08 |
URI: | https://research.sabanciuniv.edu/id/eprint/46844 |