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Embed. Comput. Syst."],"published-print":{"date-parts":[[2024,11,30]]},"abstract":"<jats:p>As the core operation of lattice cipher, large-scale polynomial multiplication is the biggest computational bottleneck in its realization process. How to quickly calculate polynomial multiplication under resource constraints has become an urgent problem to be solved in the hardware implementation of lattice ciphers. Therefore, an analog in-memory circuit for fast polynomial multiplication calculation is proposed. First, an in-memory computing circuit for Discrete Fourier Transform and Inverse Discrete Fourier Transform based on memristor array is designed. On this basis, a fully analog circuit that can realize polynomial multiplication in one step is designed. Compared with traditional hardware implementation, the in-memory calculation method used in this article decreases the calculation time of polynomial multiplication to the microsecond level, which greatly improves the speed of lattice cipher encryption and decryption. For the specific examples in this article, PSPICE simulation shows that the average accuracy of the calculation result is above 99.90%.<\/jats:p>","DOI":"10.1145\/3605891","type":"journal-article","created":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T12:04:11Z","timestamp":1687781051000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Analog In-memory Circuit Design of Polynomial Multiplication for Lattice Cipher Acceleration Application"],"prefix":"10.1145","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4718-8042","authenticated-orcid":false,"given":"Sichun","family":"Du","sequence":"first","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1802-6132","authenticated-orcid":false,"given":"Jun","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3929-9930","authenticated-orcid":false,"given":"Chen","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4134-8551","authenticated-orcid":false,"given":"Pingdan","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Physics and Electronics, Hunan University, Changsha, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6210-6033","authenticated-orcid":false,"given":"Qinghui","family":"Hong","sequence":"additional","affiliation":[{"name":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China, Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0149-4001","authenticated-orcid":false,"given":"Jiliang","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Semiconductors (College of Integrated Circuits), Hunan University, Changsha, China"}]}],"member":"320","published-online":{"date-parts":[[2024,9,11]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2022.3200751"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3267778"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3274116"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2023.3242858"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11071-021-06476-2"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/CCIOT.2014.7062497"},{"key":"e_1_3_1_8_2","first-page":"327C343","volume-title":"Proceedings of the 25th USENIX Conference on Security Symposium","author":"Alkim Erdem","year":"2016","unstructured":"Erdem Alkim, L\u00e9o Ducas, Thomas P\u00f6ppelmann, and Peter Schwabe. 2016. 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