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AES Datapath Optimization Strategies for Low-Power Low-Energy Multisecurity-Level Internet-of-Things Applications

Abstract : Connected devices are getting attention because of the lack of security mechanisms in current Internet-of-Thing (IoT) products. The security can be enhanced by using standardized and proven-secure block ciphers as advanced encryption standard (AES) for data encryption and authentication. However, these security functions take a large amount of processing power and power/energy consumption. In this paper, we present our hardware optimization strategies for AES for high-speed ultralow-power ultralow-energy IoT applications with multiple levels of security. Our design supports multiple security levels through different key sizes, power and energy optimization for both datapath and key expansion. The estimated power results show that our implementation may achieve an energy per bit comparable with the lightweight standardized algorithm PRESENT of less than 1 pJ/b at 10 MHz at 0.6 V with throughput of 28 Mb/s in ST FDSOI 28-nm technology. In terms of security evaluation, our proposed datapath, 32-b key out of 128 b cannot be revealed by correlation power analysis attack using less than 20 000 traces.
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Duy-Hieu Bui, Diego Puschini, Simone Bacles-Min, Edith Beigné, X.-T. Tran. AES Datapath Optimization Strategies for Low-Power Low-Energy Multisecurity-Level Internet-of-Things Applications. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, IEEE, 2017, 25 (12), pp.3281-3290. ⟨10.1109/TVLSI.2017.2716386⟩. ⟨cea-02193684⟩

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