An Unbounded Fully Homomorphic Encryption Scheme Based on Ideal Lattices and Chinese Remainder Theorem

We propose an unbounded fully homomorphic encryption scheme, i.e. a scheme that allows one to compute on encrypted data for any desired functions without needing to decrypt the data or knowing the decryption keys. This is a rational solution to an old problem proposed by Rivest, Adleman, and Dertouzos [1] in 1978, and to some new problems that appeared in Peikert [2] as open questions 10 and open questions 11 a few years ago. Our scheme is completely different from the breakthrough work [3] of Gentry in 2009. Gentry’s bootstrapping technique constructs a fully homomorphic encryption (FHE) scheme from a somewhat homomorphic one that is powerful enough to evaluate its own decryption function. To date, it remains the only known way of obtaining unbounded FHE. Our construction of an unbounded FHE scheme is straightforward and can handle unbounded homomorphic computation on any refreshed ciphertexts without bootstrapping transformation technique.

A Fully Homomorphic Encryption Scheme with Better Key Size

Fully homomorphic encryption is faced with two problems now. One is candidate fully homomorphic encryption schemes are few. Another is that the efficiency of fully homomorphic encryption is a big question. In this paper, we propose a fully homomorphic encryption scheme based on LWE, which has better key size. Our main contributions are： （1） According to the binary-LWE recently, we choose secret key from binary set and modify the basic encryption scheme proposed in Linder and Peikert in 2010. We propose a fully homomorphic encryption scheme based on the new basic encryption scheme. We analyze the correctness and give the proof of the security of our scheme. The public key, evaluation keys and tensored ciphertext have better size in our scheme. （2） Estimating parameters for fully homomorphic encryption scheme is an important work. We estimate the concert parameters for our scheme. We compare these parameters between our scheme and Bral2 scheme. Our scheme have public key and private key that smaller by a factor of about logq than in Bral2 scheme. Tensored ciphertext in our scheme is smaller by a factor of about log2q than in Bral2 scheme. Key switching matrix in our scheme is smaller by a factor of about log3q than in Bra12 scheme.

A secure outsourced Turing- equivalent computation scheme against semi-honest workers using fully homomorphic encryption

A scheme that can realize homomorphic Turing- equivalent privacy-preserving computations is proposed, where the encoding of the Turing machine is independent of its inputs and running time. Several extended private information retrieval protocols based on fully homomorphic encryption are designed, so that the reading and writing of the tape of the Turing machine, as well as the evaluation of the transition function of the Turing machine, can be performed by the permitted Boolean circuits of fully homomorphic encryption schemes. This scheme overwhelms the Turing-machine-to- circuit conversion approach, which also implements the Turing-equivalent computation. The encoding of a Turing- machine-to-circuit conversion approach is dependent on both the input data and the worst-case runtime. The proposed scheme efficiently provides the confidentiality of both program and data of the delegator in the delegator-worker model of outsourced computation against semi-honest workers.

Novel Homomorphic Encryption for Mitigating Impersonation Attack in Fog Computing

Fog computing is a rapidly growing technology that aids in pipelining the possibility of mitigating breaches between the cloud and edge servers.It facil-itates the benefits of the network edge with the maximized probability of offering interaction with the cloud.However,the fog computing characteristics are suscep-tible to counteract the challenges of security.The issues present with the Physical Layer Security(PLS)aspect in fog computing which included authentication,integrity,and confidentiality has been considered as a reason for the potential issues leading to the security breaches.In this work,the Octonion Algebra-inspired Non-Commutative Ring-based Fully Homomorphic Encryption Scheme(NCR-FHE)was proposed as a secrecy improvement technique to overcome the impersonation attack in cloud computing.The proposed approach was derived through the benefits of Octonion algebra to facilitate the maximum security for big data-based applications.The major issues in the physical layer security which may potentially lead to the possible security issues were identified.The potential issues causing the impersonation attack in the Fog computing environment were identified.The proposed approach was compared with the existing encryption approaches and claimed as a robust approach to identify the impersonation attack for the fog and edge network.The computation cost of the proposed NCR-FHE is identified to be significantly reduced by 7.18%,8.64%,9.42%,and 10.36%in terms of communication overhead for varying packet sizes,when compared to the benchmarked ECDH-DH,LHPPS,BF-PHE and SHE-PABF schemes.

An Improved Multiple to One Fully Homomorphic Encryption on the Integers

The public key of the integer homomorphic encryption scheme which was proposed by Van Dijk et al. is long, so the scheme is almost impossible to use in practice. By studying the scheme and Coron’s public key compression technique, a scheme which is able to encrypt n bits plaintext once was obtained. The scheme improved the efficiency of the decrypting party and increased the number of encrypting parties, so it meets the needs of cloud computing better. The security of the scheme is based on the approximate GCD problem and the sparse-subset sum problem.

An Efficient Encrypted Speech Retrieval Based on Unsupervised Hashing and B+ Tree Dynamic Index

Existing speech retrieval systems are frequently confronted with expanding volumes of speech data.The dynamic updating strategy applied to construct the index can timely process to add or remove unnecessary speech data to meet users’real-time retrieval requirements.This study proposes an efficient method for retrieving encryption speech,using unsupervised deep hashing and B+ tree dynamic index,which avoid privacy leak-age of speech data and enhance the accuracy and efficiency of retrieval.The cloud’s encryption speech library is constructed by using the multi-threaded Dijk-Gentry-Halevi-Vaikuntanathan(DGHV)Fully Homomorphic Encryption(FHE)technique,which encrypts the original speech.In addition,this research employs Residual Neural Network18-Gated Recurrent Unit(ResNet18-GRU),which is used to learn the compact binary hash codes,store binary hash codes in the designed B+tree index table,and create a mapping relation of one to one between the binary hash codes and the corresponding encrypted speech.External B+tree index technology is applied to achieve dynamic index updating of the B+tree index table,thereby satisfying users’needs for real-time retrieval.The experimental results on THCHS-30 and TIMIT showed that the retrieval accuracy of the proposed method is more than 95.84%compared to the existing unsupervised hashing methods.The retrieval efficiency is greatly improved.Compared to the method of using hash index tables,and the speech data’s security is effectively guaranteed.

基于余数系统的小间隔插值拟合自举方法

针对近似同态加密方案自举耗时过大的问题提出了一种基于余数系统的小区间插值拟合自举方法。通过在多个小区间内对模函数进行插值拟合避免因拟合多项式次数过高产生自举时间过长或计算精度降低的问题,并通过结合余数系统提高计算过程中模乘运算的模逆运算效率。选用拉格朗日插值多项式对小区间内的正弦函数进行插值拟合。通过多个低次多项式复合计算实现比较函数,并提出了一种区间判断算法来识别密文所在区间。最终在24比特精度下,同态计算过程中模运算耗时下降到HEAAN库的8%,在计算槽的数量为65536时,平均每槽的模运算时间为0.028 ms。

新形态对称密码算法研究

安全多方计算、全同态加密和零知识证明是解决数据安全问题的重要密码技术,其快速发展和应用需求驱动,引发了新形态对称密码的设计与安全性分析.本文系统介绍适宜安全多方计算、全同态加密和零知识证明的新形态对称密码算法.首先梳理新形态对称密码算法的应用需求和设计目标;然后归类介绍新形态对称密码算法的设计理念和最新的安全性评估结果;最后总结探讨新形态对称密码算法的设计特点以及面临的问题.

全同态加密软硬件加速研究进展

全同态加密(FHE)是一种重计算、轻交互的多方安全计算协议。在基于全同态加密的计算协议中,尽管计算参与方之间无需多轮交互与大量通信,加密状态下的密态数据处理时间通常是明文计算的10~3~10~6倍,极大地阻碍了这类计算协议的实际落地;而密态数据上的主要处理负担是大规模的并行密码运算和运算所必须的密文及密钥数据搬运需求。该文聚焦软、硬件两个层面上的全同态加密加速这一研究热点,通过系统性地归类及整理当前领域中的文献,讨论全同态加密计算加速的研究现状与展望。

全密态数据库密态计算关键技术综述

随着近些年云服务的流行,越来越多的企业和个人将数据存储在云数据库上.但在享受云服务便利的同时,也带来数据安全的问题.其中一个比较关键的问题是敏感数据的机密性保护,即保护用户的敏感数据不被窥探和泄漏.在这样的背景下,全密态数据库应运而生.相对于传统数据库,全密态数据库能够在数据的传输、存储和计算整个生命周期中对数据进行加密,保护数据的机密性.目前,在对数据加密的同时,支持所有SQL功能并保持高性能等方面还存在很多挑战.全面调研全密态数据库密态计算的关键技术,根据技术类型进行归纳分类,并在功能性、安全性和性能等方面进行对比与总结.首先介绍全密态数据库架构,包括基于加密算法的纯软件架构、基于可信执行环境(TEE)的可信硬件架构和软硬融合式架构.然后,总结归纳各个架构的关键技术.最后,讨论当前研究的挑战和机会,并提供一些未来研究的开放性问题.

基于错误学习的全同态加密技术研究现状与挑战

全同态加密方案是一种具备数据机密性和安全性的加密方案,同时还能够对密文进行计算操作。在云计算时代,全同态加密方案能够满足私有信息检索、多方安全计算等多种应用需求。错误学习与全同态加密的结合,迅速推动了全同态加密方案的发展,并引出了多种技术工具,如密钥交换和模交换等具有理论和实际应用意义的技术。自从2011年基于LWE的全同态加密方案被提出以来,基于LWE类型的方案已成为全同态加密方案的主流方法,并逐步从理论走向实际应用。文章首先介绍全同态加密的基础知识和应用,并对构造方案的数学理论进行详细分析;然后系统梳理了每一代同态加密方案,并给出了每一代方案的典型构造方式;最后探讨了当前基于LWE的全同态加密方案存在的问题以及未来的发展趋势,为后续研究者提供一些参考。

基于Zynq平台的BFV全同态加密算法高效实现

针对BFV全同态加密算法,在Zynq平台上设计了一种高效实现方案。该方案结合负包裹卷积与数论变换(NTT)算法,优化并加速了多项式乘法的过程。同时采用流水线设计思想和并行化硬件电路架构,加速BFV算法的RNS实现。系统采用AXI-DMA传输机制高效地实现了ARM和FPGA之间数据传输。在Zynq Ultra‐Scale+MPSoC ZCU102平台上测试,系统在200 MHz时钟频率下,执行一次同态加法的平均耗时为0.024 ms;执行一次同态乘法的平均耗时为5.779 ms,其中包括0.874 ms的密文传输时间。与SEAL库和OpenFHE库的实现相比,所提方案的同态加法实现了4.63倍和6.79倍的效率提升,同态乘法实现了4.43倍和2.95倍的效率提升,这为全同态加密算法的实际工程实现提供了重要参考。

全同态加密技术的研究现状及发展路线综述

随着物联网、云计算、人工智能的应用与普及,数据安全与隐私保护成为人们关注的焦点。全同态加密,作为隐私安全问题的有效解决办法,允许对加密数据执行任意同态计算,是一种强大的加密工具,具有广泛的潜在应用。该文总结了自2009年以来提出全同态加密方案,并根据方案的核心技术划分成4条技术路线,分析讨论了各类方案的关键构造,算法优化进程和未来发展方向。首先,全面介绍了全同态加密相关的数学原理,涵盖了全同态加密方案的基础假设和安全特性。随后,按照4条全同态加密方案的技术路线,归纳了加密方案的结构通式,总结了自举算法的核心步骤,讨论了最新研究进展,并在此基础上综合分析比较了各类方案的存储效率及运算速度。最后,展示了同态算法库对每条技术路线下加密方案的应用实现情况,分析了在当前时代背景下全同态加密方案的机遇与挑战,并对未来的研究前景做出了展望。

环保大数据在区块链中的隐私计算

近年来,随着我国网络安全、医疗及环保相关政策的先后出台,环境数据的价值与日俱增。但我国对于环境数据的科学管理与安全共享仍处于起步阶段,具有隐私保护需求的环境数据数量急剧增加,但在数据共享上却面临数据孤岛化、泄露风险高等诸多难题。针对环境数据共享场景,为从根本上满足用户数据云存储和云计算的隐私保护需求,文章将区块链和隐私计算相结合,采用国密算法构建了一个基于全同态加密和可搜索加密技术的数据密态管理系统。依托区块链部署和云服务存储、隐私计算支持,系统可实现全同态加密机器学习和可搜索加密两种功能。文章基于全同态加密技术实现了神经网络预测模型,并完成了密态数据的云计算;同时,文章采用对称可搜索加密方案,支持数据在全程密态下的远程托管,能够实现密文检索并保护查询关键词的隐私。在保护隐私安全前提下,该方案有效打通了各方数据流通通道,保证数据可用不可见。

全同态加密应用的编码技术综述

全同态加密允许在不解密的前提下对密文进行任意操作,为数据“可用不可见”的需求提供了绝佳的解决思路.由于效率和安全性原因,全同态加密的明文空间通常被定义在多项式环或者有限域代数结构上.目前实用化的全同态加密方案分为以BGV、BFV和CKKS为代表的第二代和以FHEW、TFHE为代表的第三代全同态加密方案,其中第二代方案的基础计算类型包括代数加法和代数乘法,而第三代方案的核心计算单元是门自举.但是现实应用涉及的数据类型包含整数、浮点数、复数、矩阵、向量等,函数计算类型包括多项式函数和三角、求逆、比较等各种非多项式函数.因此在应用全同态加密时,必须设计高效的消息编码和函数计算编码以适用于实际计算任务,提高整体运行效率.本文系统地总结了目前第二代全同态加密涉及的消息编码,并分析了一些常用函数在不同全同态加密方案下的的同态计算编码策略,最后对卷积神经网络推理和对称加密算法(AES)两个实例给出了具体分析和测试.

云计算环境下基于全同态加密的神经网络分类预测研究

在云计算环境下,数据挖掘应用中的数据共享和服务外包在产生巨大财富的同时,也带来了隐私泄漏的风险,其信息安全问题亟待解决。对云计算环境下神经网络预测分类服务外包中存在的风险以及全同态加密算法的应用进行了分析,使用平方函数作为神经网络中的非线性激活函数,设计并实现了一种密文域的数据分类预测方案,并对该方案运行过程中的5个主要步骤:模型训练、模型加密、数据加密、密文计算和解密结果进行详细描述。设计的测试实验结果验证了该方案的可行性,保证了模型和数据在整个神经网络处理过程中不被泄漏,可有效保障数据和模型的安全与隐私。

多方全同态加密研究进展

全同态加密支持对密文直接进行计算,进而保障了在不可信环境中操作敏感信息的安全性和隐私性.为适应由多个数据持有者提供私有信息的联合计算场景,多参与方下的全同态加密逐渐受到关注.近十年来,大量相关工作展开,主要的技术路线分为门限全同态加密、多密钥全同态加密以及多群全同态加密.同时,多方全同态加密的发展进一步推动了多方安全计算领域的进步.本文从传统的单密钥全同态加密出发,系统全面地对多方全同态加密的前沿进展做出综述性报告,并对其中的代表性构造进行详细介绍.最后,对现有研究工作进行整体分析并总结存在问题.

基于双联盟链的电网分布式异构数据共享研究

电网异构数据分布较为广泛,难以实现有效共享,导致数据共享时延增加、吞吐量变小。为了解决这些问题,提出了基于双联盟链的电网分布式异构数据共享方法。利用双联盟链平台开源代码配置数据共享环境,生成新区块。使用哈希值函数检验区块数据,将同一个属性的异构节点放置在同一通道中。引入全同态加密技术分割明文,获取明文序列,实现单节点跨链数据共享。考虑各个节点隐私情况,采用安全多方计算方式处理相似异构数据,保证异构数据一致性,计算所有节点、局部节点权重,保证数据共享安全性,实现多节点跨链数据共享,从而达到电网分布式异构数据加密共享的目标。实验结果表明,该方法的最大共享时延为10 s,最大吞吐量为460 bit,数据共享效果良好。

基于全同态加密的无线传感网络数据隐私保护方法

为提高无线传感网络数据的隐私性,确保私有数据不被破解,提出基于全同态加密的无线传感网络数据隐私保护方法。该方法通过对多种数据或信息的处理,可以得到更有效的、更符合用户要求的结果,从而达到对无线传感网数据的融合。结合全同态加密,在确保数据安全、完整的情况下,存储无线传感网络数据。结合CPDA算法,分三个阶段实现数据融合隐私保护。对比实验证明,新的数据隐私保护方法的应用可以有效降低无线传感网络数据被破解的概率,促进数据隐私性的提高,为整个无线传感网络环境的安全性提供保障。

基于CKKS全同态加密的用电数据隐私计算

国家电网有限公司提出要提高电网数字化水平,加快数据要素流通,构建能源数字生态圈,支撑各类智慧能源产品和业务创新。然而,数据的安全和隐私问题是数据开放、数据交易的重大障碍,是支撑国家电网的数字化转型战略必须攻克的课题。为此,基于CKKS全同态加密,提出并实现了包含三大参与方(数据提供者、服务提供者、研究者或商业使用者)的用电数据隐私计算分析框架,采用基于模拟的方法证明了上述方案的安全性,分析了基于CKKS隐私计算的时空复杂度,并以负荷曲线聚类作为典型应用场景进行误差分析,以证明所提框架的实用性。