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Annual review of advances of full homomorphic encryption technology
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Science & Technology Review | 2024, 42(1) : 286 - 295
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Science & Technology Review | 2024, 42(1): 286-295
Exclusive: Science and Technology Review in 2023
Annual review of advances of full homomorphic encryption technology
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FAN Ruiqi1, CHEN Mingzhi1, NIU Xinli2, DONG Wenkuo1, LI Xiaolin1, LIU Shuo1, LIU Jing1, ZHAO Ming3, CAI Jiayue2, YAN Wei1, ZHU Shuyong1, ZHENG Kewei2, XU Peng4, HAO Qinfen1, SUN Ninghui1
Affiliations
    1. Institute of Computing Technology, Chinese Academy of Science, Beijing 100086, China;
    2. Wuxi Xingguangtongtai LTD., Wuxi 214104, China;
    3. Wuxi Institute of Integrate Chip and Interconnect Technology, Wuxi 214104, China;
    4. School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Published: 2024-01-13 doi: 10.3981/j.issn.1000-7857.2024.01.018
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In the era of big data and artificial intelligence, homomorphic encryption methods are widely recognized as an ideal technology to solve data security and privacy leakage problems. However, there are currently issues such as poor computational efficiency and ciphertext inflation, which seriously affect application and promotion of this technology. On the basis of summarizing the current research status, this paper reviews and analyzes the relevant research progress in 2023 from two aspects:hardware acceleration for homomorphic encryption algorithms and optimization of homomorphic encryption algorithms. Significant acceleration effects are attributed to the dedicated integrated circuit technology route; substantial progress has been made in optimization from the algorithm perspective. It can be predicted that in the next few years homomorphic encryption will be combined with artificial intelligence to deliver more value in cross-industry and industry division data collaboration and utilization.
fully homomorphic encryption  /  data security  /  privacy leakage protection  /  computer architecture  /  cryptography
FAN Ruiqi, CHEN Mingzhi, NIU Xinli, DONG Wenkuo, LI Xiaolin, LIU Shuo, LIU Jing, ZHAO Ming, CAI Jiayue, YAN Wei, ZHU Shuyong, ZHENG Kewei, XU Peng, HAO Qinfen, SUN Ninghui. Annual review of advances of full homomorphic encryption technology[J]. Science & Technology Review, 2024 , 42 (1) : 286 -295 . DOI: 10.3981/j.issn.1000-7857.2024.01.018
Year 2024 volume 42 Issue 1
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doi: 10.3981/j.issn.1000-7857.2024.01.018
  • Receive Date:2023-12-31
  • Online Date:2024-04-09
  • Published:2024-01-13
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  • Received:2023-12-31
  • Revised:2024-01-08
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https://castjournals.cast.org.cn/joweb/kjdb/EN/10.3981/j.issn.1000-7857.2024.01.018
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表12种不同金属材料的力学参数

Family
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Number of
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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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