Secure and privacy preserving keyword searching for cloud storage services

Cloud storage services enable users to remotely access data in a cloud anytime and anywhere, using any device, in a pay-as-you-go manner. Moving data into a cloud offers great convenience to users since they do not have to care about the large capital investment in both the deployment and management of the hardware infrastructures. However, allowing a cloud service provider (CSP), whose purpose is mainly for making a profit, to take the custody of sensitive data, raises underlying security and privacy issues. To keep user data confidential against an untrusted CSP, a natural way is to apply cryptographic approaches, by disclosing the data decryption key only to authorized users. However, when a user wants to retrieve files containing certain keywords using a thin client, the adopted encryption system should not only support keyword searching over encrypted data, but also provide high performance. In this paper, we investigate the characteristics of cloud storage services and propose a secure and privacy preserving keyword searching (SPKS) scheme, which allows the CSP to participate in the decipherment, and to return only files containing certain keywords specified by the users, so as to reduce both the computational and communication overhead in decryption for users, on the condition of preserving user data privacy and user querying privacy. Performance analysis shows that the SPKS scheme is applicable to a cloud environment.     

基于云存储的多用户可搜索加密方案

云存储服务允许用户外包数据并以此来降低资源开销。针对云服务器不被完全信任的现状,文章研究如何在云环境下对数据进行安全存储和加密搜索。多用户的可搜索加密方案为用户提供了一种保密机制,使用户可以在不受信任的云存储环境下安全地共享信息。在现有的可搜索加密方案的基础上,文章提出了一种安全有效的带关键字搜索的加密方案,以及更加灵活的密钥管理机制,降低了云端数据处理的开销。     

区块链上基于云辅助的属性基可搜索加密方案

可搜索加密技术在不解密的情况下搜索加密数据.针对现有的可搜索加密技术没有考虑数据用户细粒度搜索权限的问题,以及现有的可搜索加密方案中因云存储的集中化对数据安全和隐私保护带来的问题,提出了区块链上基于云辅助的属性基可搜索加密方案.该方案利用可搜索加密技术实现加密数据在区块链上的安全搜索,利用基于属性的加密技术实现数据的细...     

云环境下基于属性策略隐藏的可搜索加密方案

基于属性的可搜索加密技术可以实现对数据的细粒度访问控制,但现有的可搜索加密方案,关键字的搜索、访问控制、文件加密基本上是分别执行的,导致攻击者可能跳过访问策略直接进行关键字索引匹配或文件解密;其次,现有方案中数据拥有者需将加密文件的密钥以安全通道传给用户,增加了数据拥有者的开销;此外,大多基于树型的访问控制策略是公开的,容易造成隐私泄露。因此,基于线性秘密分享（LSSS,linear secret sharing schemes）访问结构,提出了一种云环境下基于属性策略隐藏的可搜索加密方案。通过将策略秘密值嵌入关键字加密与文件存储加密,实现访问控制、关键字搜索与文件加密的有机结合;通过聚合密钥技术实现用户无须与数据拥有者交互,即可对文件进行解密的功能,减轻了密钥管理的负担,存储空间提高约30%。实验结果及安全性分析表明,所提方案具有数据存储的安全性、访问策略的隐私性、陷门的不可连接性等功能,具有较高的密文检索效率,与已有主流方案相比,检索效率提高至20%以上。     

可验证的多用户云加密关键字搜索方案

针对云环境下多用户访问和大数据量存储的特点,提出了一种云环境下加密关键字搜索方案。与已有的大多数方案相比,该方案使用签名绑定关键字索引和其关联加密文件,实现了查询结果完备性和完整性的验证,使用重加密技术实现了多用户隐查询,并动态更新用户查询权限。此外,该方案在查询过程中使用哈希查询优化索引结构,实现了对云数据的快速访问。安全性分析表明,该方案是安全的;性能分析及仿真实验结果表明该方案和已有的一些算法相比有了较大的性能提升。     

基于CP-ABE和XACML多权限安全云存储访问控制方案

为了保护云存储系统中用户数据的机密性和用户隐私,提出了一种基于属性加密结合XACML框架的多权限安全云存储访问控制方案。通过CP-ABE加密来保证用户数据的机密性,通过XACML框架实现基于属性细粒度访问控制。云存储系统中的用户数据通过对称加密机制进行加密,对称密钥采用CP-ABE加密。仿真实验表明,该方案是高效灵活并且安全的。安全性分析表明,该方案能够抵抗共谋攻击,具有数据机密性以及后向前向保密性。     

基于离线密钥分发的加密数据重复删除方法

重复数据删除技术受到工业界和学术界的广泛关注.研究者致力于将云服务器中的冗余数据安全的删除,明文数据的重复删除方法较为简单.而用户为了保护隐私,会使用各自的密钥将数据加密后上传至云服务器,形成不同的加密数据.在保证安全性的前提下,加密数据的重复删除较难实现.目前已有的方案较多依赖在线的可信第三方.提出一种基于离线密钥分发的加密数据重复删除方案,通过构造双线性映射,在不泄露数据隐私的前提下,验证加密数据是否源自同一明文.利用广播加密技术实现加密密钥的安全存储与传递.任意数据的初始上传者能够借助云服务器,以离线方式验证后继上传者的合法性并传递数据加密密钥.无需可信第三方在线参与,实现云服务器对加密数据的重复删除.分析并证明了方案的安全性.仿真实验验证了方案的可行性与高效性.     

Privacy-preserving conjunctive keyword search on encrypted data with enhanced fine-grained access control

Cloud storage over the internet gives opportunities for easy data sharing. To preserve the privacy of sharing data, the outsourced data is usually encrypted. The searchable encryption technique provides a solution to find the target data in the encrypted form. And the public-key encryption with keyword search is regarded as a major approach for the searchable encryption technique. However, there are still several privacy leakage challenges for the further adoption of these major schemes. One is how to resist the keyword guessing attack which still leaks data user’s keywords privacy. Another is how to construct the access control policy to prevent illegal access of outsourced data sharing since illegal access always leak the privacy of user’s attribute. In our paper, we firstly try to design a novel secure keyword index to resist the keyword guessing attack from access pattern and search pattern. Second, we propose an attribute-based encryption scheme which supports an enhanced fine-grained access control search. This allows the authenticated users to access different data although their searching request contains the same queried keywords, and meanwhile unauthenticated users cannot get any attribute privacy information. Third, we give security proofs to show that the construction of keyword index is against keyword guessing attack from the access pattern and search pattern, and our scheme is proved to be IND-CPA secure (the indistinguishability under chosen plaintext attack) under the standard model. Finally, theoretical analyses and a series of experiments are conducted to demonstrate the efficiency of our scheme.

     

VMKDO: Verifiable multi-keyword search over encrypted cloud data for dynamic data-owner

The advantages of cloud computing encourage individuals and enterprises to outsource their local data storage and computation to cloud server, however, data security and privacy concerns seriously hinder the practicability of cloud storage. Although searchable encryption (SE) technique enables cloud server to provide fundamental encrypted data retrieval services for data-owners, equipping with a result verification mechanism is still of prime importance in practice as semi-trusted cloud server may return incorrect search results. Besides, single keyword search inevitably incurs many irrelevant results which result in waste of bandwidth and computation resources. In this paper, we are among the first to tackle the problems of data-owner updating and result verification simultaneously. To this end, we devise an efficient cryptographic primitive called as verifiable multi-keyword search over encrypted cloud data for dynamic data-owner scheme to protect both data confidentiality and integrity. Rigorous security analysis proves that our scheme is secure against keyword guessing attack (KGA) in standard model. As a further contribution, the empirical experiments over real-world dataset show that our scheme is efficient and feasible in practical applications.     

Secure and efficient data collaboration with hierarchical attribute-based encryption in cloud computing

With the increasing trend of outsourcing data to the cloud for efficient data storage, secure data collaboration service including data read and write in cloud computing is urgently required. However, it introduces many new challenges toward data security. The key issue is how to afford secure write operation on ciphertext collaboratively, and the other issues include difficulty in key management and heavy computation overhead on user since cooperative users may read and write data using any device. In this paper, we propose a secure and efficient data collaboration scheme, in which fine-grained access control of ciphertext and secure data writing operation can be afforded based on attribute-based encryption (ABE) and attribute-based signature (ABS) respectively. In order to relieve the attribute authority from heavy key management burden, our scheme employs a full delegation mechanism based on hierarchical attribute-based encryption (HABE). Further, we also propose a partial decryption and signing construction by delegating most of the computation overhead on user to cloud service provider. The security and performance analysis show that our scheme is secure and efficient.     

云存储中支持属性撤销的多关键词可搜索加密方案

云存储的便捷性和管理高效性使得越来越多的用户选择将数据存放在云端。为支持用户对云端加密数据进行检索,提出云存储中基于属性加密支持属性撤销的多关键词搜索方案。采用线性秘密共享矩阵来表示访问控制结构,实现密文细粒度访问控制,在属性撤销过程中不需要更新密钥,应对用户属性变更的情况,在此基础上构造基于多项式方程的搜索算法支持多关键词搜索,从而提高搜索精度。理论分析和实验结果表明,该方案具有陷门不可伪造性和关键词隐私性,能够保证用户数据的隐私和安全,相比CP-ABE方案,具有较高的存储性能和计算效率,功能性更强。     

一种属性可撤销的安全云存储模型

针对云存储服务中数据用户权限撤销粒度较粗及现有方案密钥分发计算量大等问题,基于双系统加密的思想,在合数阶双线性群上提出了一种新的细粒度权限撤销的安全云存储模型。数据拥有者同时也作为属性分发机构,保证了对自身数据的绝对控制,确保了在云服务商不可信情况下开放环境中的云端存储数据的安全。从模型架构和属性密钥分发两个方面对模型进行了研究,并用严格的数学方法证明了本方案是适应性安全的。云存储模型的数据访问策略根据实际需要可灵活设置,适用于云存储等开放式环境。     

单断言的密文区间检索方案的安全分析

为保护用户数据隐私,用户通常将敏感数据加密后外包存储在半可信的服务器上。为防止泄露用户隐私信息,蔡克等(蔡克,张敏,冯登国.基于单断言的安全的密文区间检索［J］.计算机学报, 2011, 34(11):2093-2103)首次提出单断言密文区间检索方案,而之前在密文数据上的区间检索都通过多次断言实现。使用三角函数关系和矩阵理论,通过密文区间索引直接产生敏感数据的排列信息,证明该单断言密文检索方案不是唯密文安全的。为避免这种安全缺陷,通过引入随机元素构造了安全的单断言密文检索改进方案,并分析了改进方案的复杂性。     

不经意随机访问机研究综述

随着云计算与大数据技术的发展,隐私保护越来越受到人们的关注.加密是一种常见的保护数据隐私的方法,但是单纯地利用加密手段并不能抵抗所有类型的攻击.攻击者可以通过观察用户对数据的访问模式来推断隐私信息,其中包括数据的重要程度、数据的关联性,甚至是加密数据的内容等.不经意随机访问机是一种重要的保护访问模式的手段,它通过混淆每一次访问过程,使其与随机访问不可区分,从而保护真实访问中的访问操作、访问位置等信息.不经意随机访问机在安全云存储系统以及安全计算领域有着非常重要的作用.利用不经意随机访问机可以降低攻击者通过访问模式推测隐私信息的可能性,减小系统受到的攻击面,从而提供更安全更完整的服务.对不经意随机访问机的研究与应用进行综述,主要介绍了不经意随机访问机的相关概念以及设计方法,重点分析并总结了目前学术界研究的性能优化的常见策略及其优劣性,主要包括针对客户端与服务器的平均带宽与最坏情况带宽优化、存储开销优化以及交互轮数优化等方面.同时讨论了将不经意随机访问机应用于安全存储系统的一般性问题,如数据完整性保护以及支持多用户并发访问等,也讨论了将其应用于安全计算领域的问题,如安全计算协议设计以及不经意数据结构的设计等;最后,对不经意随机访问机未来的研究方向进行了展望.     

Privacy-aware searching with oblivious term matching for cloud storage

Encryption ensures confidentiality of the data outsourced to cloud storage services. Searching the encrypted data enables subscribers of a cloud storage service to access only relevant data, by defining trapdoors or evaluating search queries on locally stored indexes. However, these approaches do not consider access privileges while executing search queries. Furthermore, these approaches restrict the searching capability of a subscriber to a limited number of trapdoors defined during data encryption. To address the issue of privacy-aware data search, we propose Oblivious Term Matching (OTM). Unlike existing systems, OTM enables authorized subscribers to define their own search queries comprising of arbitrary number of selection criterion. OTM ensures that cloud service provider obliviously evaluates encrypted search queries without learning any information about the outsourced data. Our performance analysis has demonstrated that search queries comprising of 2 to 14 distinct search criteria cost only 0.03 to 1.09 $ per 1000 requests.     

基于关键词的加密云数据模糊搜索策略研究

随着个人和企业用户产生的数据量越来越多,云存储的价格便宜、存储空间使用灵活等优势也越来越明显。随着大量的数据外包到云服务器端,用户一般采用加密方法实现对敏感数据的保护和使用限制,这使得传统的基于明文的搜索方案不再适用。如何在保护隐私的基础上实现高效的数据文件搜索是首要考虑的问题。在已有的加密数据搜索方案的基础上,分析中文所特有的模糊音和多义的特点,利用中文和英文实现关键词的同义词构建,并建立关键词的模糊音词和同义词集合,提出了基于关键词的加密云数据模糊搜索方案,实现了对中文模糊音和同义关键词的搜索并利用伪随机函数对私钥进行保护。最后通过安全性分析和系统实验验证了该方案具有较高的安全性、良好的实用性和较高的搜索成功率。     

An efficient PHR service system supporting fuzzy keyword search and fine-grained access control

Outsourcing of personal health record (PHR) has attracted considerable interest recently. It can not only bring much convenience to patients, it also allows efficient sharing of medical information among researchers. As the medical data in PHR is sensitive, it has to be encrypted before outsourcing. To achieve fine-grained access control over the encrypted PHR data becomes a challenging problem. In this paper, we provide an affirmative solution to this problem. We propose a novel PHR service system which supports efficient searching and fine-grained access control for PHR data in a hybrid cloud environment, where a private cloud is used to assist the user to interact with the public cloud for processing PHR data. In our proposed solution, we make use of attribute-based encryption (ABE) technique to obtain fine-grained access control for PHR data. In order to protect the privacy of PHR owners, our ABE is anonymous. That is, it can hide the access policy information in ciphertexts. Meanwhile, our solution can also allow efficient fuzzy search over PHR data, which can greatly improve the system usability. We also provide security analysis to show that the proposed solution is secure and privacy-preserving. The experimental results demonstrate the efficiency of the proposed scheme.     

Efective Error-Tolerant Keyword Search for Secure Cloud Computing简

The existing solutions to keyword search in the cloud can be divided into two categories： searching on exact keywords and searching on error-tolerant keywords. An error-tolerant keyword search scheme permits to make searches on encrypted data with only an approximation of some keyword. The scheme is suitable to the case where users＇ searching input might not exactly match those pre-set keywords. In this paper, we first present a general framework for searching on error-tolerant keywords. Then we propose a concrete scheme, based on a fuzzy extractor, which is proved secure against an adaptive adversary under well-defined security definition. The scheme is suitable for all similarity metrics including Hamming distance, edit distance, and set difference. It does not require the user to construct or store anything in advance, other than the key used to calculate the trapdoor of keywords and the key to encrypt data documents. Thus, our scheme tremendously eases the users＇ burden. What is more, our scheme is able to transform the servers＇ searching for error-tolerant keywords on ciphertexts to the searching for exact keywords on plaintexts. The server can use any existing approaches of exact keywords search to search plaintexts on an index table.     

一种无安全信道的模糊关键字搜索加密方案

在互联网技术高度发达的今天,人们越来越习惯把个人数据上传到云端进行存储。传统可搜索公钥加密方案仅支持对精确的关键字进行搜索,用户需要精确地输入搜索关键字,且需要使用安全信道来传输陷门,降低了系统的可用性。针对安全信道,本文结合公钥加密技术提出一种无安全信道的模糊关键字搜索加密方案。该方案在不使用安全信道的情况下也能保证信息的隐私性,使用通配符技术来降低关键字集的空间大小,并且给出安全性验证。     

云计算中基于属性的可搜索加密电子病历系统

电子病历是医学报告在云计算技术迅速发展下的一个重要产物,它的出现方便了医院和患者对病历的管理。然而, 患者的相关隐私数据存储在云上,就必然面临着隐私泄露、非法访问等隐患。为保护存储在云端的电子病历数据的私密性,提出了一个基于属性的可搜索加密方案,并给出了它在电子病历系统中的重要应用。与传统的可搜索加密方案相比,本方案降低了多用户环境下密钥管理的难度,且方案中的陷门可以在非安全信道上传输。此外,该方案可隐藏访问结构,具有细粒度访问控制,可根据数据拥有者的请求增加或撤销用户的访问权限。安全性分析表明,该方案保护了关键词的隐私性,可抵抗关键词猜测攻击,能有效防止隐私数据的泄露。关键词陷门匹配算法仅需一次双线性对运算,大大提高了搜索效率。