This paper presents a new type of anonymous fingerprinting scheme, which is based on homomorphic public key cryptosystems.

An Anonymous Fingerprinting Scheme Based on Homomorphic Public Key Cryptosystems

一种基于同态公钥加密体制的匿名数字指纹方案

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Compared with the general encryption algorithm, homomorphic encryption can implement not only the basic cryptographic operations, but also specific types of computations on ciphertexts, which means the results of calculating before decrypting is same as decrypting before calculating.

与一般加密算法相比，同态加密除了能实现基本的加密操作之外，还能实现密文间的多种计算功能，即先计算后解密可等价于先解密后计算。

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The second system ( i.e., the strengthened version of the first one) achieved more efficient security reduction by incorporating the straight-line extraction paradigm and removed random oracles by using the non-interactive zero-knowledge argument from homomorphic encryption.

第二个系统（即前一个系统的增强版本）利用直线提取技术实现了更为高效的安全性归约过程，并借助基于同态加密的非交互零知识论证避免了对随机预言机的使用。

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In this paper, the main work of the homomorphic encryption as follows: First of all, introduce several typical homomorphic encryption schemes, including partially homomorphic encryption schemes and fully homomorphic encryption schemes.

本文在同态加密领域的主要工作如下：首先，介绍分析了几种典型的同态加密方案，包括半同态和全同态方案。

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With the strict analysis of the characteristics of homomorphic encryption, we realize that the reasonable using of this technology can reduce the computational complexity and communication complexity of multi-party computation.

通过对同态加密技术特点的深入分析，得知合理利用此技术可降低多方计算协议的计算复杂度与通信复杂度。

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But the defects of homomorphic encryption system still limit the scope of its application. Therefore, research on the theory and applications of homomorphic encryption is of great significance.

但目前同态加密体制的自身缺陷也限制了其应用的范围，所以从理论和应用两个方面研究同态加密具有重要的价值。

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Based on these work, we summarize the existing problems of homomorphic encryption cryptosystems, and propose further ideas. Next, introduce the "many-to-one" homomorphic encryption scheme.

在此基础上，总结同态加密体制存在的问题，并提出进一步研究设想。其次，提出并设计了多对一的同态加密方案。

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The present homomorphic encryption schemes are mostly in the form of" one-to-one", means one party encrypts and the other decrypts in public key cryptosystem.

已有同态加密方案大多是公钥密码体制下的一方加密，一方解密的一对一的密码形式。

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It puts forward a novel approach to discover privacy-preserving sequential patterns based on secure multi-party computation by using commutative encryption and homomorphic encryption technology.

利用可交换加密技术和同态加密技术，提出一个新颖的基于安全多方计算的私密保持序贯模式挖掘算法。

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Finally, this paper presents a new secure tree-based data aggregation protocol which includes homomorphic encryption algorithm and the new result-checking algorithm.

最后，基于同态加密和新的结果验证算法，提出一种新的树形数据融合协议。

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Therefore, in order to balance security and service demand in cloud computing, we introduce the concept of the homomorphism encryption.

因此，为了平衡安全性和服务于云计算的需求，我们引入了同态加密这一概念。

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Wireless Group Key Distribution Protocol Based on Homomorphic Encryption Scheme Detecting Dynamic Complexity of Rat Population in Ecological Systems

基于同态加密机制的无线群组密钥分配协议生态系统中鼠群密度动态复杂性研究

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Secondly, this paper protects data by homomorphic encryption algorithm based on elliptic curve.

其次，本文提出基于椭圆曲线的同态加密算法，对传感器数据进行加密。

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Homomorphic Encryption Scheme in the Range of the Real

实数范围上的同态加密机制

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On the other hand, using homomorphic encryption technology, we.

另一方面，本文通过同态加密技术，提出一种基于同态加密的数据隔离操作机制。

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Research on Techniques Securing Mobile Code Based on Homomorphic Encryption

基于同态加密的移动代码安全技术研究

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Making use of the Sander and Tschudin defined homomorphic encryption scheme in the integer ring, we design a new protocol, the homomorphism key agreement.

利用Sander和Tschudin提出的整数环上的同态加密机制，提出了一种新的密钥协定&同态密钥协定。

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The neural network-based fuzzy logic system, combined with neural network and fuzzy logic, has the advantages Of self-organizing, sample-learning, auto-structuring and fuzzy rule developing and member function optimizing.

将神经网络和模糊逻辑有机结合起来的神经网络模糊逻辑系统，具有自组织和监督学习样本、自动构造和发展模糊规则、发现和优化输入输出隶属函数等优点，从而使系统具有较快的收敛速度。

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The convergence of Learning Subspace Methods ( LSM) for pattern recognition is studied.

本文研究了神经网络无导师自监督学习子空间模式识别方法的收敛性问题，证明了学习子空间法的变换矩阵收敛于模式的自相关矩阵估计；

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The transformed matrices of learning subspaces are proved to converge to the estimation of pattern autocorrelation matrix, thus the convergence of Kohonen's self-supervised LSMs is proved.

证明了一类Kohonen自监督学习子空间方法的收敛性；

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