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| 1 | Modified Multi-Key Fully Homomorphic Encryption Based on NTRU Cryptosystem without Key-Switching显示文摘The Multi-Key Fully Homomorphic Encryption (MKFHE) based on the NTRU cryptosystem is an important alternative to the post-quantum cryptography due to its simple scheme form,high efficiency,and fewer ciphertexts and keys.In 2012,Lopez-Alt et al.proposed the first NTRU-type MKFHE scheme,the LTV12 scheme,using the key-switching and modulus-reduction techniques,whose security relies on two assumptions:the Ring Learning With Error (RLWE) assumption and the Decisional Small Polynomial Ratio (DSPR) assumption.However,the LTV12and subsequent NTRU-type schemes are restricted to the family of power-of-2 cyclotomic rings,which may affect the security in the case of subfield attacks.Moreover,the key-switching technique of the LTV12 scheme requires a circular application of evaluation keys,which causes rapid growth of the error and thus affects the circuit depth.In this paper,an NTRU-type MKFHE scheme over prime cyclotomic rings without key-switching is proposed,which has the potential to resist the subfield attack and decrease the error exponentially during the homomorphic evaluating process.First,based on the RLWE and DSPR assumptions over the prime cyclotomic rings,a detailed analysis of the factors affecting the error during the homomorphic evaluations in the LTV12 scheme is provided.Next,a Low Bit Discarded&Dimension Expansion of Ciphertexts (LBD&DEC) technique is proposed,and the inherent homomorphic multiplication decryption structure of the NTRU is proposed,which can eliminate the key-switching operation in the LTV12 scheme.Finally,a leveled NTRU-type MKFHE scheme is developed using the LBD&DEC and modulus-reduction techniques.The analysis shows that the proposed scheme compared to the LTV12 scheme can decrease the magnitude of the error exponentially and minimize the dimension of ciphertexts. | Xiaoliang Che Tanping Zhou Ningbo Li Haonan Zhou Zhenhua Chen Xiaoyuan Yang | 2020 | Tsinghua Science and Technology2020，25，5： | 6 |
| 2 | SFSDA:Secure and Flexible Subset Data Aggregation with Fault Tolerance for Smart Grid显示文摘Smart grid(SG)brings convenience to users while facing great chal-lenges in protecting personal private data.Data aggregation plays a key role in protecting personal privacy by aggregating all personal data into a single value,preventing the leakage of personal data while ensuring its availability.Recently,a flexible subset data aggregation(FSDA)scheme based on the Pail-lier homomorphic encryption was first proposed by Zhang et al.Their scheme can dynamically adjust the size of each subset and obtain the aggregated data in the corresponding subset.In this paper,firstly,an efficient attack with both theorems proving and experimentative verification is launched.We find that in a specific scenario where the encrypted data constructed by a smart meter(SM)exceeds the size of one Paillier ciphertext,the malicious fog node(FN)may use the received ciphertext to obtain the reading of the SM.Secondly,to avoid the possibility of privacy disclosure under certain circumstances,additional hash functions are added to the individual encryption process.In addition,fault tolerance is very important to aggregation schemes in practical scenarios.In most of the current schemes,once some SMs failed,then they will not work.As far as we know,there is no multi-subset aggregation scheme both supports flexible subset data aggregation and fault tolerance.Finally,we construct the first secure flexible subset data aggregation(SFSDA)scheme with fault tolerance by combining the fault tolerance method with the flexible multi-subset aggregation,where FN enables the control server(CS)to finally decrypt the aggregated ciphertext by recovering equivalent ciphertexts when some SMs fail to submit their ciphertexts.Experiments show that our SFSDA scheme keeps the efficiency in implementing a flexible multi-subset aggregation function,and only has a small delay in implementing fault-tolerant data aggregation. | Dong Chen Tanping Zhou Xu An Wang Zichao Song Yujie Ding Xiaoyuan Yang | 2023 | Intelligent Automation & Soft Computing2023，37，8： | 0 |
| 3 | Properties of GSW and Their Applications显示文摘In CRYPTO' 13,Gentry et al.proposed a fully homomorphic encryption scheme,called GSW.We find that the scheme has three special properties,which are not sufficiently recognized and applied in current literatures.Property 1:Noise grows asymmetrically in multiplication.Property 2:Small noise in MultConst(C,α).Property 3:Fixed noise bound when a is a power of 2 in MultConst(C,α).We made use of property 1 to the Yi's private searching on streaming data protocol,called YBVX.Compared with YBVX,the four mainly aspects of efficiency in our protocol had been improved,the computation complexity of the sever decreased from O(ml^2 +μ)multi.+O(ml^2 +μ)add.+O(μd) enc.+O(μ)ADD.to O(m+μ)multi.+O(m+μ)add.+O(μd)enc.+O(μ) ADD;the space complexity decreased from O(ml^2+μd) to O(m+μd);the communication complexity decreased from O(ml)+O(d|D|k) to O(m)+O(d|D|k);the computation complexity of the client decreased from O(ml)dec.+O(d|D|) enc to O(m)dec.+O(d|D|)enc.what's more,the above three properties can have a variety of applications,ranging from improving the property of cryptographic prototypes to protocol building. | YANG Xiaoyuan ZHOU Tanping ZHANG Wei TAN Zhenlin | 2015 | China Communications2015，12，11： | 0 |
| 4 | Optimized Relinearization Algorithm of the Multikey Homomorphic Encryption Scheme显示文摘Multikey homomorphic encryption(MKHE) supports arbitrary homomorphic evaluation on the ciphertext of different users and thus can be applied to scenarios involving multiusers(e.g., cloud computing and artificial intelligence) to protect user privacy. CDKS19 is the current most efficient MKHE scheme, and its relinearization process consumes most of the time of homomorphic evaluation. In this study, an optimized relinearization algorithm of CDKS19 is proposed. This algorithm reorganizes the evaluation key during the key generation process, decreases the complexity of relinearization, and reduces the error growth rate during homomorphic evaluation. First, we reduce the scale of the evaluation key by increasing its modulus instead of using a gadget vector to decompose the user’s public key and extend the ciphertext of homomorphic multiplication. Second, we use rescaling technology to optimize the relinearization algorithm;thus, the error bound of the ciphertext is reduced, and the homomorphic operation efficiency is improved. Lastly, the average-case error estimation on the variances of polynomial coefficients and the upper bound of the canonical embedding map are provided. Results show that our scheme reduces the scale of the evaluation key, the error variance, and the computational cost of the relinearization process. Our scheme can effectively perform the homomorphic multiplication of ciphertexts. | Xiaoyuan Yang Shangwen Zheng Tanping Zhou Yao Liu Xiaoliang Che | 2022 | Tsinghua Science and Technology2022，27，3： | 0 |
| 5 | Artificial intelligence-based medical image segmentation for 3D printing and naked eye 3D visualization显示文摘Image segmentation for 3D printing and 3D visualization has become an essential component in many fields of medical research,teaching,and clinical practice.Medical image segmentation requires sophisticated computerized quantifications and visualization tools.Recently,with the development of artificial intelligence(AI)technology,tumors or organs can be quickly and accurately detected and automatically contoured from medical images.This paper introduces a platform-independent,multi-modality image registration,segmentation,and 3D visualization program,named artificial intelligence-based medical image segmentation for 3D printing and naked eye 3D visualization(AIMIS3D).YOLOV3 algorithm was used to recognize prostate organ from T2-weighted MRI images with proper training.Prostate cancer and bladder cancer were segmented based on U-net from MRI images.CT images of osteosarcoma were loaded into the platform for the segmentation of lumbar spine,osteosarcoma,vessels,and local nerves for 3D printing.Breast displacement during each radiation therapy was quantitatively evaluated by automatically identifying the position of the 3D printed plastic breast bra.Brain vessel from multimodality MRI images was segmented by using model-based transfer learning for 3D printing and naked eye 3D visualization in AIMIS3D platform. | Guang Jia Xunan Huang Sen Tao Xianghuai Zhang Yue Zhao Hongcai Wang Jie He Jiaxue Hao Bo Liu Jiejing Zhou Tanping Li Xiaoling Zhang Jinglong Gao | 2022 | Intelligent Medicine2022，2，1： | 0 |
| 6 | Secure Scheme for Locating Disease-Causing Genes Based on Multi-Key Homomorphic Encryption显示文摘Genes have great significance for the prevention and treatment of some diseases.A vital consideration is the need to find a way to locate pathogenic genes by analyzing the genetic data obtained from different medical institutions while protecting the privacy of patients’genetic data.In this paper,we present a secure scheme for locating disease-causing genes based on Multi-Key Homomorphic Encryption(MKHE),which reduces the risk of leaking genetic data.First,we combine MKHE with a frequency-based pathogenic gene location function.The medical institutions use MKHE to encrypt their genetic data.The cloud then homomorphically evaluates specific gene-locating circuits on the encrypted genetic data.Second,whereas most location circuits are designed only for locating monogenic diseases,we propose two location circuits(TH-intersection and Top-q)that can locate the disease-causing genes of polygenic diseases.Third,we construct a directed decryption protocol in which the users involved in the homomorphic evaluation can appoint a target user who can obtain the final decryption result.Our experimental results show that compared to the JWB+17 scheme published in the journal Science,our scheme can be used to diagnose polygenic diseases,and the participants only need to upload their encrypted genetic data once,which reduces the communication traffic by a few hundred-fold. | Tanping Zhou Wenchao Liu Ningbo Li Xiaoyuan Yang Yiliang Han Shangwen Zheng | 2022 | Tsinghua Science and Technology2022，27，2： | 0 |
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