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非承诺加密机制是语义安全的,不能抵抗选择密文攻击.在non-erase模型的安全假设下,基于非承诺加密机制的不经意传输协议不能实现自适应攻击者UC(Universally Composable)安全的定义.利用可否认加密体制和可验证平滑投影哈希函数,提出了一个新的不经意传输协议,可否认加密体制通过陷门承诺的双陷门解密技术实现,新协议方案是可证明UC安全的,基于公共参考串模型,安全性可以归约为确定性复合剩余假设.新协议参与方能够处理指数空间的消息,计算效率得到改善,通过两次协议交互可以实现string-OT协议,与bit-OT协议相比单轮通信效率提高O(n)倍. 相似文献
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在一个1—out—n的不经意传输模型中。发送者提供n条消息给另一方接收者。但是接收者只能选择获取其中的1条消患,并且发送者不知道接收者获取的是哪一条消息。文章提出了一个基于门限思想并且可复用的1—out-n不经意传输协议。它在效率方面优于以往的Naor-Pinkas协议和Tzeng协议。 相似文献
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基于VSPH的UC不经意传输协议 总被引:2,自引:0,他引:2
基于UC(universally composable)安全模型框架,提出了一个新的不经意传输协议方案(UC-OT)。利用可验证平滑投影散列函数(VSPH),在公共参考串模型中,该协议方案实现了抗自适应攻击的通用可组合安全。UC-OT利用基于确定性组合剩余假设构造的非承诺加密体制提高了协议的计算效率,实现了string-OT,与bit-OT协议相比单轮通信效率提高O(n)倍。在non-erase模型假设下,与Canetti所提的方案相比,单轮交互次数减少1次;与Fischlin方案相比,单轮交互次数减少2次,并且本方案不需要辅助第3方,因而更符合实际情况。 相似文献
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不经意传输(OT, oblivious transfer)协议是密码学中的一个基本协议。基于物理不可克隆函数(PUF, physical unclonable function)给出物理不可克隆函数系统(PUFS, physical unclonable function system)的概念,并在此基础上提出一个新的不经意传输协议(POT, PUFS based OT),最后在通用可组合(UC, universal composition)框架内给出POT协议抵抗静态敌手的安全性证明。相比于传统基于公钥加密的OT方案,POT协议不使用任何可计算的假设,而是基于PUFS的安全属性实现,因此在很大程度上减小了计算和通信开销。 相似文献
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提出两个抗选择密文攻击的门限密码系统.第一个方案的密文由应用Canetti-Halevi-Kazt的方法到Boneh-Boyen的基于身份加密而得到.第二个方案中的密文与Waters的基于身份加密的密文基本相同,唯一的区别是这里的"身份"是密文的前两部分的hash值.由于服务器在提供解密碎片之前可以公开验证密文的合法性,而合成者又可以公开验证解密碎片的合法性,使我们的两个方案都具有非交互性.二者的安全性都在标准的决定性双线性Diffie-Hellman假设下被证明. 相似文献
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The mobile agent is a fundamental building block of the mobile computing paradigm. In mobile agent security, oblivious transfer
(OT) from a trusted party can be used to protect the agent’s privacy and the hosts’ privacy. In this paper, we introduce a
new cryptographic primitive called Verifiable Distributed Oblivious Transfer (VDOT), which allows us to replace a single trusted party with a group of threshold trusted servers. The design of VDOT uses a novel
technique called consistency verification of encrypted secret shares. VDOT protects the privacy of both the sender and the receiver against malicious attacks of the servers. We also show the
design of a system to apply VDOT to protect the privacy of mobile agents. Our design partitions an agent into the general
portion and the security-sensitive portion. We also implement the key components of our system. As far as we know, this is
the first effort to implement a system that protects the privacy of mobile agents. Our preliminary evaluation shows that protecting
mobile agents not only is possible, but also can be implemented efficiently.
This work was supported in part by the DoD University Research Initiative (URI) program administered by the Office of Naval
Research under grant N00014-01-1-0795. Sheng Zhong was supported by ONR grant N00014-01-1-0795 and NSF grants ANI-0207399
and CCR-TC-0208972. Yang Richard Yang was supported in part by NSF grant ANI-0207399. A preliminary version of this paper
was presented at the DialM-POMC Joint Workshop on Foundations of Mobile Computing in 2003.
Sheng Zhong received his Ph.D. in computer science from Yale University in the year of 2004. He holds an assistant professor position
at SUNY Buffalo and is currently on leave for postdoctoral research at the Center for Discrete Mathematics and Theoretical
Computer Science (DIMACS). His research interests, on the practical side, are security and incentives in data mining, databases,
and wireless networks. On the theoretical side, he is interested in cryptography and game theory.
Yang Richard Yang is an Assistant Professor of Computer Science at Yale University. His research interests include computer networks, mobile
computing, wireless networking, sensor networks, and network security. He leads the LAboratory of Networked Systems (LANS)
at Yale. His recent awards include a Schlumberger Fellowship and a CAREER Award from the National Science Foundation. He received
his B.E. degree from Tsinghua University (1993), and his M.S. and Ph.D. degrees from the University of Texas at Austin (1998
and 2001). 相似文献
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基于邻域的社会化推荐需要同时依赖用户的历史行为数据和完善的社交网络拓扑图,但通常这些数据分别属于不同平台,如推荐系统服务提供商和社交网络服务提供商。出于维护自身数据价值及保护用户隐私的考虑,他们并不愿意将数据信息提供给其他方。针对这一现象,提出了2种数据隐私保护的社会化推荐协议,可以在保护推荐系统服务提供商和社交网络服务提供商的数据隐私的同时,为用户提供精准的推荐服务。其中,基于不经意传输的社会化推荐,计算代价较小,适用于对推荐效率要求较高的应用;基于同态加密的社会化推荐,安全程度更高,适用于对数据隐私要求较高的应用。在4组真实数据集上的实验表明,提出的2种方案切实可行,用户可以根据自身需求选择合适的方案。 相似文献
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We present an alternative to the controversial ``key-escrow' techniques for enabling law enforcement and national security
access to encrypted communications. Our proposal allows such access with probability p for each message, for a parameter p between 0 and 1 to be chosen (say, by Congress) to provide an appropriate balance between concerns for individual privacy, on the one hand,
and the need for such access by law enforcement and national security, on the other. (For example, with p=0.4 , a law-enforcement agency conducting an authorized wiretap which records 100 encrypted conversations would expect to be
able to decrypt (approximately) 40 of these conversations; the agency would not be able to decrypt the remaining 60 conversations
at all.) Our scheme is remarkably simple to implement, as it requires no prior escrowing of keys.
We implement translucent cryptography based on noninteractive oblivious transfer. Extending the schemes of Bellare and Micali
[2], who showed how to transfer a message with probability ?, we provide schemes for noninteractive fractional oblivious transfer,
which allow a message to be transmitted with any given probability p . Our protocol is based on the Diffie—Hellman assumption and uses just one El Gamal encryption (two exponentiations), regardless
of the value of the transfer probability p . This makes the implementation of translucent cryptography competitive, in efficiency of encryption, with current suggestions
for software key escrow.
Received 19 September 1996 and revised 1 November 1997 相似文献