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Post-Quantum Public-Key Cryptography Scheme for Secure Internet of Things-Based Edge Consumer Electronics Device

Mohd FazilCollege of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi ArabiaDivya NimmaArkansas Tech University, Russellville, AR, USANadeem SarwarDepartment of Computer Science, Bahria University, Lahore Campus, Lahore, PakistanYelisela RajeshDepartment of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, IndiaShakir KhanCollege of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi ArabiaNavruzbek ShavkatovDepartment of Corporate Finance and Securities, Tashkent State University of Economics, Tashkent, UzbekistanMohamed Abbas IbrahimCollege of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi ArabiaGufran Ahmad AnsariCollege of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi ArabiaNeeraj KumarDepartment of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, India
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In the basic operations of the GGH-based post-quantum public-key cryptography scheme, polynomial multiplication consumes a large amount of time in edge-based consumer electronics devices (ECED). To improve the actual computational performance, this paper aims to design a fast and efficient polynomial multiplication architecture for lattice-based cryptography in IoT applications. Specifically, the objective is to develop a number-theoretic transform algorithm optimized for CRYSTALS-Kyber that reduces modular operations, supports high parallelism, and eliminates memory conflicts. To this end, we propose a 2n-th root pre-processing fast number-theoretic transform algorithm tailored for IoT-based edge devices. This architecture utilizes parallel processing of small-digit NTT operations and low-complexity calculation forms to reduce computation time. After combining the characteristics of the algorithm, the overall computational architecture determines a design model with 32 parallel channels. Based on this, a unified computational unit matching this architecture and storage units with non-conflicting data read/write and optimal address allocation were designed. Experimental results show that under the 65 nm complementary metal-oxide-semiconductor (CMOS) technology, polynomial multiplication operations with 256 terms and a modulus of 3,329 can be completed in 97 ns, consuming 108 cycles. The highest operating frequency can reach 1.1 GHz, with an area-time product of 20.7 (kGE × μs).

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