安全多方计算技术专栏序言(中英文)

徐秋亮,唐春明

1.山东大学 软件学院,济南 250101

2.广州大学 数学与信息科学学院,广州 510006

安全多方计算研究两个或多个持有私有输入的参与者,联合计算某些功能函数,各自得到他们预定的输出,并达到正确性、隐私性、公平性等安全特性.近年来,随着云计算、大数据、人工智能、区块链等技术的出现和发展,数据安全与隐私保护问题面临的挑战日益突出,安全多方计算被寄予厚望,公认是解决这类问题的重要手段,因而得到空前重视.

为了进一步促进我国安全多方计算领域的理论和应用研究,本刊通过广泛征稿和约稿,组织了本期“安全多方计算技术” 专栏,希望能对该领域的发展起到积极促进作用.经过同行评审,本期共收录6 篇论文.

综述性论文1 篇.赵川等人的论文《实用安全两方计算及其在基因组序列比对中的应用》,总结分析了安全两方计算近年来在实用性方面的主要研究成果,并重点介绍了实用安全两方计算在基因组序列比对中的研究进展.作者从安全两方计算的两个主要构造方法(同态加密和混乱电路)出发,分别给出了较为清晰的发展脉络.此外,该文指出了现阶段基于安全两方计算的基因组序列比对研究中存在的几点不足,并分析了未来可能的研究方向.

特定安全多方计算协议论文3 篇.杜润萌等人的论文《矩阵与增广矩阵秩相等问题的保密计算及应用》,在半诚实敌手模型下,设计了矩阵与增广矩阵秩相等判定问题的安全多方计算协议,并将该协议用于解决保密判断多项式整除、保密判定直线与直线的位置关系等问题.李占利等人的论文《云环境下多方保密计算最大值、最小值及其统计学应用》首先使用0-1 编码方法,使得保密数据隐藏于所编码的0-1 数组中,然后利用云环境下多密钥NTRU 全同态加密算法,在半诚实敌手模型下,设计了在云计算环境下解决最大值、最小值计算的安全多方计算协议.葛雪等人的论文《直方图与饼形图的保密生成协议》,利用加同态加密算法,设计了数据求和的安全多方计算协议,并进一步转化为直方图与饼形图,该协议也是在半诚实敌手模型下证明安全的.

安全多方计算应用协议2 篇.朱岩等人的论文《基于安全多方计算的区块链智能合约执行系统》,提出了基于安全多方计算的智能合约框架、面向线性秘密共享的公平安全多方计算算法设计、以及非阻塞信息传递接口等三方面技术,保证了智能合约执行中的输入隐私性和计算正确性,从而增强了区块链中智能合约执行安全.王启正等人的论文《一种处理隐私保护数据的神经网络》,利用基于同态加密的安全多方计算技术,设计了神经网络计算外包协议,在保障数据隐私性的前提下保留了数据的可计算性.

安全多方计算是密码学的一个重要研究领域,它随着公钥密码技术的出现而产生,经过了长时间的发展.近年来,随着安全多方计算协议本身效率的提升,以及各种分布式应用场景对安全和隐私保护的迫切要求,安全多方计算协议的研究成为密码学方向最有活力的研究领域之一.通过本期专栏,希望读者能够管中窥豹,见安全多方计算技术最新研究动向之一斑.

In the secure multi-party computation(SMPC),two or more participants who have private inputs,want to jointly calculate some functionalities,get their outputs,and achieve some secure properties such as correctness,privacy,fairness,and so on.In recent years,with the development of cloud computing,big data,artificial intelligence,block chains,and other technologies,the challenges of data security and privacy protection have become increasingly prominent.Secure multi-party computing has been highly expected,and is recognized as an important technique to solve such problems,which has attracted unprecedented attention.

In order to promote the theoretical and applied research of SMPC in China,Journal of Cryptologic Research organized the special column on ”Secure Multi-party Computing Technology” by calling and inviting for papers widely,hoping to promote the development of this field.6 papers are selected into this special column after the peer review process.

One review is included in this special column.“Advances in Practical Secure Two-party Computation and Its Application in Genomic Sequence Comparison”by Zhao Chuan et al.reviews the advances in practical secure two-party computation in recent years,and focuses on the major research results in the field of genomic sequence comparison based on secure two-party computation.The authors start with introducing two major construction techniques(i.e.,homomorphic encryption and garbled circuit),and give a clear development trend,respectively.In addition,the existing deficiencies in this research area and some possible research directions are pointed out.

Three papers on specific secure multi-party computation protocol are included in this special column.The paper entitled“Privately Determining Equality of Ranks of Matrix and Its Augmented Ones and Applications”by Du Run-Meng et al.designs an SMPC protocol in semi-honest adversaries model to determine whether the rank of a matrix is equal to its augmented ones,and applies this protocol in privately determining the relationship between two lines,determining whether a polynomial divides another one.The paper entitled “Secure Multiparty Computation of the Maximum and the Minimum in Cloud Environment and Its Statistics Application”by Li Zhan-Li et al.adapts 0-1 encoding method to encode a private number into an array,and then using the multikey NTRU fully homomorphic encryption algorithm in cloud environment,designs the SMPC protocol in semi-honest adversaries model to compute the maximum and the minimum value.The paper entitled “Histogram and Pie Chart of Confidentiality Generation Agreement” by Ge Xue et al.uses homomorphic encryption algorithm to design an SMPC protocol to compute the summation,and further convert it to generate the histogram and pie chart.The protocol is also proved in semi-honest adversaries model.

Two papers on secure multi-party computation application protocol are included in this special column.The paper entitled “Smart Contract Execution System over Blockchain Based on Secure Multi-party Computation”by Zhu Yan et al.proposes three technologies:a smart contract framework based on secure multi-party computation(SMPC),a fair SMPC algorithm built on linear secret sharing,and a non-blocking message passing interface,to ensure the privacy of inputs and the correctness of computing result during smart contract execution.Thus,the execution security of smart contract can be enhanced by the proposed technologies in the Blockchain.The paper entitled “Neural Network for Processing Privacy-protected Data” by Wang Qi-Zheng et al.uses the homomorphic encryption based SMPC to design a neural network computation outsourcing protocol.It keeps the computability of data under the premise of ensuring data privacy.

SMPC is an important research field in cryptography.It has been developed for a long time with the emergence of public key cryptography.In recent years,with the improvement of the efficiency of secure multi-party computing protocols and the urgent requirement of security and privacy protection in various distributed application scenarios,the research of SMPC protocols has become one of the most liven research fields in cryptography.Through this special column,we hope that readers can get a glimpse of the research trends in SMPC technology.