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    Securing the IoT ecosystem: ASIC-based hardware realization of Ascon lightweight cipher

    Khan, S ORCID logoORCID: https://orcid.org/0000-0001-8342-6928, Inayat, K, Muslim, FB, Shah, YA, Atif Ur Rehman, M ORCID logoORCID: https://orcid.org/0000-0002-6812-8620, Khalid, A, Imran, M and Abdusalomov, A (2024) Securing the IoT ecosystem: ASIC-based hardware realization of Ascon lightweight cipher. International Journal of Information Security, 23 (6). pp. 3653-3664. ISSN 1615-5262

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    Abstract

    The Internet of Things (IoT) nodes consist of sensors that collect environmental data and then perform data exchange with surrounding nodes and gateways. Cybersecurity attacks pose a threat to the data security that is being transmitted in any IoT network. Cryptographic primitives are widely adopted to address these threats; however, the substantial computation demands limit their applicability in the IoT ecosystem. In addition, each IoT node varies with respect to the area and throughput (TP) requirements, thus demanding flexible implementation for encryption/decryption processes. To solve these issues, this work implements the NIST lightweight cryptography standard, Ascon, on a SAED 32 nm process design kit (PDK) library by employing loop folded, loop unrolled and fully unrolled architectures. The fully unrolled architecture can achieve the highest TP but at the cost of higher area utilisation. Unrolling by a lower factor results in lower area implementations, enabling the exploration of design space to tackle the trade-off between area and TP performance of the design. The implementation results show that, for loop folded architecture, Ascon-128 and Ascon-128a require 36.7k μm2 and 38.5k μm2 chip area, respectively compared to 277.1k μm2 and 306.6k μm2 required by their fully unrolled implementations. The proposed implementation strategies can adjust the number of rounds to accommodate the varied requirements of IoT ecosystems. An implementation with an open-source 45 nm PDK library is also undertaken for enhanced generalization and reproducibility of the results.

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