Fast and Energy-Efficient Block Ciphers Implementations in ARM Processors and Mali GPU

Citation

Lee, Wai Kong and Phan, Raphael Chung Wei and Goi, Bok Min (2020) Fast and Energy-Efficient Block Ciphers Implementations in ARM Processors and Mali GPU. IETE Journal of Research. pp. 1-8. ISSN 0377-2063

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Abstract

With the proliferation of the internet of things (IoT) and device-to-device (D2D) communications enabled by the boom of mobile computing technology, secure high-speed communication has now become indispensable in our daily life. This is especially true when potentially private data are being continually sensed by and communicated among mobile devices as they exist in a world of interconnected inanimate objects, which is also one of the main themes of the upcoming 5G revolution. As the amount of data to be secured for high-speed communications is vast, there is a need to ensure that the block ciphers used for encryption are deployed without incurring significant computational cost. In this paper, we present fast implementations of recent industry standard block ciphers in typical embedded platforms, consisting of multi-core CPU (ARM A15 and A7) and GPU (Mali T628). We implemented the conventional block cipher (AES) and lightweight block ciphers (CLEFIA, SIMON, SPECK and PRESENT) optimized for fast computation. We also analyze the energy efficiency of these block ciphers computation in CPU and GPU, as low power consumption is crucial for the embedded system. Our experimental results show that the embedded GPU is not only able to compute block ciphers faster than conventional CPU but also consumes significantly less power.

Item Type: Article
Uncontrolled Keywords: Computer networks—Security measures, ARM, Block cipher, Energy efficiency, GPU,
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 08 Dec 2020 16:47
Last Modified: 08 Dec 2020 16:47
URII: http://shdl.mmu.edu.my/id/eprint/7798

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