云存储服务中数据完整性审计方案综述

云存储是由云计算提供的一个重要服务,允许数据拥有者将数据远程存储到云服务器上,同时又能够从云服务器上便捷、高效地获取这些数据,没有本地存储和维护数据的负担。然而,这种新的数据存储模式也引发了众多安全问题,一个重要的问题就是如何确保云服务器中数据拥有者数据的完整性。因此,数据拥有者以及云存储服务提供商亟需一个稳定、安全、可信的完整性审计方案,用于审核云服务器中数据的完整性和可用性。不仅如此,一个好的数据完整性审计方案还需满足如下功能需求：支持数据的动态操作,包括插入、删除、修改;支持多用户、多云服务器的批量审计;确保用户数据的隐私性;注重方案的执行效率,尽量减少数据拥有者和云服务器的计算开销与通信开销。为了促进云存储服务的广泛应用与推广,文章重点对云数据完整性审计方案的研究现状进行综述,描述云存储以及数据完整性审计的相关概念、特点,提出云计算环境下数据完整性审计模型和安全需求,阐述云存储数据完整性审计的研究现状,并重点分析部分经典方案,通过方案对比,指出当前方案存在的优点及缺陷。同时,文章还指出了本领域未来的研究方向。     

Cryptanalysis and improvement of Panda - public auditing for shared data in cloud and internet of things

Cloud computing and internet of things have gained remarkable popularity by a wide spectrum of users recently. Despite of the convenience of cloud storage, security challenges have risen upon the fact that users do not physically possess their data any more. Thus, some auditing schemes are introduced to ensure integrity of the outsourced data. And among them Panda is a public auditing scheme for shared data with efficient and secure user revocation proposed by Wang et al. It argued that it could verify the integrity of shared data with storage correctness and public auditing. In this paper, we analyze this scheme and find some security drawbacks. Firstly, Panda cannot preserve shared data privacy in cloud storage. Furthermore, our analysis shows that Panda is vulnerable to integrity forgery attack, which can be performed by malicious cloud servers to forge a valid auditing proof against any auditing challenge even without correct data storage. Then we pinpoint that the primary cause of the insecurity is the linear combinations of sampled data blocks without random masking properly. Finally, we propose an improvement of Panda together with data privacy preserving and sound public auditing while incurring optimal communication and computation overhead.     

Privacy-preserving public auditing for educational multimedia data in cloud computing

Nowadays, as distance learning is being widly used, multimedia data becomes an effective way for delivering educational contents in online educational systems. To handle the educational multimedia data efficiently, many distance learning systems adopt a cloud storage service. Cloud computing and storage services provide a secure and reliable access to the outsourced educational multimedia contents for users. However, it brings challenging security issues in terms of data confidentiality and integrity. The straightforward way for the integrity check is to make the user download the entire data for verifying them. But, it is inefficient due to the large size of educational multimedia data in the cloud. Recently many integrity auditing protocols have been proposed, but most of them do not consider the data privacy for the cloud service provider. Additionally, the previous schemes suffer from dynamic management of outsourced data. In this paper, we propose a public auditing protocol for educational multimedia data outsourced in the cloud storage. By using random values and a homomorphic hash function, our proposed protocol ensures data privacy for the cloud and the third party auditor (TPA). Also, it is secure against lose attack and temper attack. Moreover, our protocol is able to support fully dynamic auditing. Security and performance analysis results show that the proposed scheme is secure while guaranteeing minimum extra computation costs.     

云计算下的数据存储安全可证明性综述

云计算的数据服务外包可以减少数据所有者本地的存储和维护压力,然而用户会因此失去对数据可靠性和安全的物理控制。于是如何确保云中数据的安全就成为了非常有挑战性的任务和难题。在全面研究云计算数据存储安全现有成果的基础上,介绍了云计算数据存储的基本架构,并从可检索证明和可证明数据拥有两个角度分析了相关研究方案的发展,从公共认证、同态认证、数据动态化、隐私保护、批审计和多服务器环境得方面讨论了协议的功能设计,并且列表进行了功能和开销对比,在此基础上提出了一个比较完备的云计算环境下的协议框架。最后总结并阐述了后续工作。     

云计算中数据隐私的安全保护机制

在云计算中,用户所拥有的数据信息通常被存放在遥远的云端,而其它用户常常能够访问这些数据且这些数据通常不由数据拥有者自己控制和管理.在此状况下,如何在云计算中保护用户的数据隐私安全则是一个十分具有挑战性的问题.为了解决这个问题,本文提出了一种数据隐私的安全保护机制.在此安全保护机制中,针对用户数据上载和访问的过程,首先提出了一种数据隐私保护的安全流程.在此基础上,提出了用户数据安全存储算法和云端数据安全访问算法.为了证明这种保护机制的有效性,本文对其安全性能进行了一系列的分析.分析结果表明：在云计算中使用这种机制能够确保数据隐私的安全性.     

Efficient integrity verification of replicated data in cloud using homomorphic encryption

The cloud computing is an emerging model in which computing infrastructure resources are provided as a service over the internet. Data owners can outsource their data by remotely storing them in the cloud and enjoy on-demand high quality services from a shared pool of configurable computing resources. However, since data owners and the cloud servers are not in the same trusted domain, the outsourced data may be at risk as the cloud server may no longer be fully trusted. Therefore, data confidentiality, availability and integrity is of critical importance in such a scenario. The data owner encrypts data before storing it on the cloud to ensure data confidentiality. Cloud should let the owners or a trusted third party to check for the integrity of their data storage without demanding a local copy of the data. Owners often replicate their data on the cloud servers across multiple data centers to provide a higher level of scalability, availability, and durability. When the data owners ask the cloud service provider (CSP) to replicate data, they are charged a higher storage fee by the CSP. Therefore, the data owners need to be strongly convinced that the CSP is storing data copies agreed on in the service level contract, and data-updates have been correctly executed on all the remotely stored copies. To deal with such problems, previous multi copy verification schemes either focused on static files or incurred huge update costs in a dynamic file scenario. In this paper, we propose a dynamic multi-replica provable data possession scheme (DMR-PDP) that while maintaining data confidentiality prevents the CSP from cheating, by maintaining fewer copies than paid for and/or tampering data. In addition, we also extend the scheme to support a basic file versioning system where only the difference between the original file and the updated file is propagated rather than the propagation of operations for privacy reasons. DMR-PDP also supports efficient dynamic operations like block modification, insertion and deletion on replicas over the cloud servers. Through security analysis and experimental results, we demonstrate that the proposed scheme is secure and performs better than some other related ideas published recently.     

Security analysis of a publicly verifiable data possession scheme for remote storage

As an essential technology of cloud computing, the cloud storage can exactly satisfy the demand of users with the service of scalability, ubiquitous access and low maintenance cost. However, moving data to the cloud servers will bring some significant security challenges due to the loss of the physical data possession. In order to verify the data integrity, many verifiable data possession schemes have been proposed in last several years. Very recently, Tang and Zhang proposed a new publicly verifiable data possession (PVDP) scheme for remote storage. They claimed that their scheme was suitable for checking the storage correctness and secure against various types of attacks. In this paper, we analyze the security of Tang and Zhang’s PVDP scheme and prove that it is vulnerable to the data recovery attack. We also demonstrate that PVDP scheme works incorrectly with a concrete instance. Our analysis shows that their scheme is not suitable for practical applications. Our work can help cryptographers and engineers design and implement more secure and efficient public auditing schemes for the cloud storage data.     

Efficient data integrity auditing for storage security in mobile health cloud

Cloud storage services can enable data owners to eliminate the need for the initial investment of expensive infrastructure setup and also minimize development and maintenance costs. Outsourcing the health data to e-health cloud storage server is very beneficial. Nonetheless, storing the health data on cloud servers also brings serious security challenges. In this paper, we propose a highly efficient data integrity auditing scheme for cloud storage for mobile health applications. The authentication tag for each data block generated by biosensor nodes is minimal in our scheme due to the use of hash operation. Moreover, in data integrity checking phase, message-locked encryption scheme is utilized to encrypt and transport the auditing information of the checked data blocks, which significantly reduces the required amount of calculation and communication resources. Compared with the conventional third party auditing schemes, the presented scheme speeds up the tag generation and tag checking process by more than one thousand times.     

云存储系统中数据完整性验证协议

在云存储网络环境中,数据的安全性和完整性是用户最关心的问题之一。综合考虑云存储网络环境中的安全需求,设计了云存储数据完整性验证(CS-DIV)协议。客户端把数据文件和校验标签上传到云存储服务器后随机抽查,服务器返回验证证据并由客户端判断文件的完整性。协议可以有效地验证云存储数据的完整性,并抵抗恶意服务器欺骗和恶意客户端攻击,从而提高整个云存储系统的可靠性和稳定性。仿真实验数据表明,所提协议以较低的存储、通信及时间开销实现了数据的完整性保护。     

A method for trust management in cloud computing: Data coloring by cloud watermarking

With the development of Internet technology and human computing, the computing environment has changed dramatically over the last three decades. Cloud computing emerges as a paradigm of Internet computing in which dynamical, scalable and often virtualized resources are provided as services. With virtualization technology, cloud computing offers diverse services (such as virtual computing, virtual storage, virtual bandwidth, etc.) for the public by means of multi-tenancy mode. Although users are enjoying the capabilities of super-computing and mass storage supplied by cloud computing, cloud security still remains as a hot spot problem, which is in essence the trust management between data owners and storage service providers. In this paper, we propose a data coloring method based on cloud watermarking to recognize and ensure mutual reputations. The experimental results show that the robustness of reverse cloud generator can guarantee users embedded social reputation identifications. Hence, our work provides a reference solution to the critical problem of cloud security.     

On the security of auditing mechanisms for secure cloud storage

Cloud computing is a novel computing model that enables convenient and on-demand access to a shared pool of configurable computing resources. Auditing services are highly essential to make sure that the data is correctly hosted in the cloud. In this paper, we investigate the active adversary attacks in three auditing mechanisms for shared data in the cloud, including two identity privacy-preserving auditing mechanisms called Oruta and Knox, and a distributed storage integrity auditing mechanism. We show that these schemes become insecure when active adversaries are involved in the cloud storage. Specifically, an active adversary can arbitrarily alter the cloud data without being detected by the auditor in the verification phase. We also propose a solution to remedy the weakness without sacrificing any desirable features of these mechanisms.     

Policing as a Service in the Cloud

ABSTRACT

Security and privacy are fundamental concerns in cloud computing both in terms of legal complications and user trust. Cloud computing is a new computing paradigm, aiming to provide reliable, customized, and guaranteed computing dynamic environment for end users. However, the existing security and privacy issues in the cloud still present a strong barrier for users to adopt cloud computing solutions. This paper investigates the security and privacy challenges in cloud computing in order to explore methods that improve the users’ trust in the adaptation of the cloud. Policing as a Service can be offered by the cloud providers with the intention of empowering users to monitor and guard their assets in the cloud. This service is beneficial both to the cloud providers and the users. However, at first, the cloud providers may only be able to offer basic auditing services due to undeveloped tools and applications. Similar to other services delivered in the cloud, users can purchase this service to gain some control over their data. The subservices of the proposed service can be Privacy as a Service and Forensics as a Service. These services give users a sense of transparency and control over their data in the cloud while better security and privacy safeguards are sought.     

全生命周期的云外包数据安全审计协议

海量数据的产生给用户带来了极大的存储和计算负担,云服务器的出现很好地解决了这一问题,但数据外包给用户带来便利的同时,也引起了一些的安全问题。针对数据在外包过程中的安全性问题,结合经典的字符串相等检测协议和基于等级的默克尔哈希树（RMHT）算法,设计并实现了一种理论更简化、效率更高的全生命周期的云外包数据安全审计协议。该协议不仅可以保证外包存储数据的完整性,用户可以定期对数据的完整性进行审计;而且可以保证数据的安全迁移;此外,还可以防止恶意的云服务器保留迁移数据的副本,更好地保护用户的隐私。安全性分析和效率分析显示,该协议足够安全并较为高效,外包数据在整个生命周期的安全性将得到较好的保护。     

利用可信计算技术改善云计算的安全性

云计算影响了互联网上世界上任何地方远程服务器处理、数据存储和共享的方式。这种共享多种分布式资源方式,使得安全问题更加复杂化。本文分析了云计算环境下的安全服务,通过整合可信计算环境来建立云计算系统。可信计算平台模式可以提高云计算的安全性。可信计算模式重要的安全服务包括加密,认证,完整性和保密性等都可以用在云计算系统中。     

Secure and efficient privacy-preserving public auditing scheme for cloud storage

Cloud computing poses many challenges on integrity and privacy of users’ data though it brings an easy, cost-effective and reliable way of data management. Hence, secure and efficient methods are needed to ensure integrity and privacy of data stored at the cloud. Wang et al. proposed a privacy-preserving public auditing protocol in 2010 but it is seriously insecure. Their scheme is vulnerable to attacks from malicious cloud server and outside attackers regarding to storage correctness. So they proposed a scheme in 2011 with an improved security guarantee but it is not efficient. Thus, in this paper, we proposed a scheme which is secure and with better efficiency. It is a public auditing scheme with third party auditor (TPA), who performs data auditing on behalf of user(s). With detail security analysis, our scheme is proved secure in the random oracle model and our performance analysis shows the scheme is efficient.     

Secure multi-server-aided data deduplication in cloud computing

Cloud computing enables on-demand and ubiquitous access to a centralized pool of configurable resources such as networks, applications, and services. This makes that huge of enterprises and individual users outsource their data into the cloud server. As a result, the data volume in the cloud server is growing extremely fast. How to efficiently manage the ever-increasing datum is a new security challenge in cloud computing. Recently, secure deduplication techniques have attracted considerable interests in the both academic and industrial communities. It can not only provide the optimal usage of the storage and network bandwidth resources of cloud storage providers, but also reduce the storage cost of users. Although convergent encryption has been extensively adopted for secure deduplication, it inevitably suffers from the off-line brute-force dictionary attacks since the message usually can be predictable in practice. In order to address the above weakness, the notion of DupLESS was proposed in which the user can generate the convergent key with the help of a key server. We argue that the DupLESS does not work when the key server is corrupted by the cloud server. In this paper, we propose a new multi-server-aided deduplication scheme based on the threshold blind signature, which can effectively resist the collusion attack between the cloud server and multiple key servers. Furthermore, we prove that our construction can achieve the desired security properties.     

云存储及其安全性研究

云存储是在云计算概念上延伸和发展出来的一个新的概念,旨在对外提供数据存储和业务访问服务。在分析云存储基本概念、结构和特点的基础上,对云存储的安全性进行了研究和分析。云存储的安全性问题是制约云存储发展的首要问题,针对非法访问、数据泄漏、数据存取故障等安全问题提出了挑战-应答式的云存储身份认证、基于用户与密钥关联的加密存储、数据恢复等多项安全解决方案,能够避免传统身份认证口令被攻击的风险,使用户可以选择加密算法使用密钥进行数据加密,以及透明地为用户提供快速且与存取并行的数据恢复。     

Efficient multi-keyword ranked query over encrypted data in cloud computing

Cloud computing infrastructure is a promising new technology and greatly accelerates the development of large scale data storage, processing and distribution. However, security and privacy become major concerns when data owners outsource their private data onto public cloud servers that are not within their trusted management domains. To avoid information leakage, sensitive data have to be encrypted before uploading onto the cloud servers, which makes it a big challenge to support efficient keyword-based queries and rank the matching results on the encrypted data. Most current works only consider single keyword queries without appropriate ranking schemes. In the current multi-keyword ranked search approach, the keyword dictionary is static and cannot be extended easily when the number of keywords increases. Furthermore, it does not take the user behavior and keyword access frequency into account. For the query matching result which contains a large number of documents, the out-of-order ranking problem may occur. This makes it hard for the data consumer to find the subset that is most likely satisfying its requirements. In this paper, we propose a flexible multi-keyword query scheme, called MKQE to address the aforementioned drawbacks. MKQE greatly reduces the maintenance overhead during the keyword dictionary expansion. It takes keyword weights and user access history into consideration when generating the query result. Therefore, the documents that have higher access frequencies and that match closer to the users’ access history get higher rankings in the matching result set. Our experiments show that MKQE presents superior performance over the current solutions.     

User Centric Block-Level Attribute Based Encryption in Cloud Using Blockchains

Cloud computing is a collection of distributed storage Network which can provide various services and store the data in the efficient manner. The advantages of cloud computing is its remote access where data can accessed in real time using Remote Method Innovation (RMI). The problem of data security in cloud environment is a major concern since the data can be accessed by any time by any user. Due to the lack of providing the efficient security the cloud computing they fail to achieve higher performance in providing the efficient service. To improve the performance in data security, the block chains are used for securing the data in the cloud environment. However, the traditional block chain technique are not suitable to provide efficient security to the cloud data stored in the cloud. In this paper, an efficient user centric block level Attribute Based Encryption (UCBL-ABE) scheme is presented to provide the efficient security of cloud data in cloud environment. The proposed approach performs data transaction by employing the block chain. The proposed system provides efficient privacy with access control to the user access according to the behavior of cloud user using Data Level Access Trust (DLAT). Based on DLAT, the user access has been restricted in the cloud environment. The proposed protocol is implemented in real time using Java programming language and uses IBM cloud. The implementation results justifies that the proposed system can able to provide efficient security to the data present in and cloud and also enhances the cloud performance.     

云计算中基于密文策略属性基加密的数据访问控制协议

云计算提供一种新兴的数据交互模式,实现了用户数据的远程存储、共享和计算。由于云计算的系统复杂性、网络开放性、资源集中性以及数据敏感性等特点,使得用户与云服务器的交互过程面临着严峻的安全威胁,成为云计算安全领域亟待解决的关键问题。文章首先介绍了云计算系统的系统组件、信任模型和攻击模型,针对云计算系统中的数据安全访问问题,提出了基于密文策略属性基加密的访问控制协议。该协议利用切比雪夫映射的半群特性实现了用户身份的合法性认证,并设计轻量级的属性加密算法实现用户数据的可靠性授权。同时,该协议主要引入身份认证、访问控制和前向安全性机制,实现用户身份真实性认证和数据可靠性访问。通过协议存储需求分析,表明该协议在数据属性集和密钥存储方面具有固定的存储空间需求,避免海量数据交互中用户存储空间的线性增长。通过分析,表明该协议具有较强的可靠性、灵活性和扩展性,适应于云环境中大规模数据交互的应用场景。