Abstract
There is a definite upward trend in the number of cellular communication nodes that, together with high rate of digital content transactions, led to continuous progress on generational technologies (3G, 4G, 5G, and more recently 6G). To facilitate smooth deployments on multi-generation environments, communication systems have to be flexible, i.e., being able to support more than one security mechanisms. In this article, two multimode architectures are introduced, realizing both SNOW 3G and SNOW-V stream ciphers. The first SNOW-3G/V multimode architecture targets area efficiency. Thus, extensive and sophisticated resource sharing is performed, without degrading the overall performance. The second one, going one step further, aims at increasing the performance of underlying SNOW 3G mechanism through parallelism, without compromising the overall area efficiency. The introduced architectures are captured in SystemVerilog and implemented in FPGA (AMD Xilinx Virtex 7 - xc7v585tffg1761–3) and ASIC (22nm FD-SOI) technologies. Frequency, Area, and Throughput metrics are concerned and comparisons with existing implementations of individual SNOW 3G and SNOW-V mechanisms are made. Regarding the area, comparisons with the sum of the area of individual designs are also made. Experimental results showed that: (a) there is limited degradation of achieved performance of multimode architectures, (b) remarkable resource sharing is achieved in both multimode architectures, and (c) the overall performance of the proposed multimode architectures is great, comparable with almost all existing individual cipher designs. Finally, it has to be stressed that it is the first time that multimode designs are proposed that include SNOW 3G and SNOW-V mechanisms.
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Konstantopoulou, E., Athanasiou, G.S., Sklavos, N. (2023). Towards Secure and Efficient Multi-generation Cellular Communications: Multi-mode SNOW-3G/V ASIC and FPGA Implementations. In: Palumbo, F., Keramidas, G., Voros, N., Diniz, P.C. (eds) Applied Reconfigurable Computing. Architectures, Tools, and Applications. ARC 2023. Lecture Notes in Computer Science, vol 14251. Springer, Cham. https://doi.org/10.1007/978-3-031-42921-7_11
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