Efficient and secure identity-based encryption scheme with equality test in cloud computing

Efficient searching on encrypted data outsourced to the cloud remains a research challenge. Identity-based encryption with equality test (IBEET) scheme has recently been identified as a viable solution, in which users can delegate a trapdoor to the server and the server then searches on user outsourced encrypted data to determine whether two different ciphertexts are encryptions of the same plaintext. Such schemes are, unfortunately, inefficient particularly for deployment on mobile devices (with limited power/battery life and computing capacity). In this paper, we propose an efficient IBEET scheme with bilinear pairing, which reduces the need for time-consuming HashToPoint function. We then prove the security of our scheme for one-way secure against chosen identity and chosen ciphertext attacks (OW–ID–CCA) in the random oracle model (ROM). The performance evaluation of our scheme demonstrates that in comparison to the scheme of Ma (2016), our scheme achieves a reduction of 36.7% and 39.24% in computation cost during the encryption phase and test phase, respectively, and that our scheme is suitable for (mobile) cloud deployment.     

移动网络中心云计算存储数据访问安全自动监测系统设计

为了提高移动网络中心云计算存储数据访问和安全监测能力,提出一种基于深度学习和交叉编译控制的移动网络中心云计算存储数据访问安全自动监测系统设计方法。采用混合属性数据模糊加权聚类方法进行移动网络中心云计算存储数据的优化访问控制模型设计,根据云计算存储数据之间的属性相似度进行离散化数值属性分解,提取移动网络中心云计算存储数据的混合属性特征量,根据最小化云存储数据访问成本为代价进行移动网络中心云计算存储数据访问的安全监测。结合深度学习方法进行数据访问的自适应控制,在交叉编译环境下实现云计算存储数据访问安全自动监测系统开发设计。测试结果表明,采用该方法进行移动网络中心云计算存储数据访问的安全性较好,自动化控制能力较强。     

Comment on “Privacy-preserving public auditing for non-manager group shared data”

Using cloud storage, users can remotely store their data without the burden on complicated local storage management and maintenance. However, users will no longer physically possess the storage of their data after they upload the data to the cloud. It is very natural for users to suspect whether their data stored in the cloud is intact. To help users efficiently check the integrity of the outsourced data, many public auditing schemes have been proposed. Recently, Huang et al. have proposed a privacy-preserving public auditing scheme for non-manager group shared data. In this paper, we find a security flaw in their auditing scheme. Even if the cloud has deleted or polluted the whole outsourced data, it still can pass the verification of the verifier. And then, we overcome this shortcoming by improving their scheme, which prevents the cloud forging a valid proof to pass the integrity auditing. Last, we perform the concrete implementation of our improved scheme and Huang et al. ’s scheme.

     

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.     

云计算中改进概率公钥加密的移动设备数据隐私保护方法

基于云计算的服务具有许多优势,但外包数据隐私保护一直以来都有待优化解决。针对云计算中资源受限的移动设备外包数据安全问题,提出一种基于改进概率公钥加密的隐私保护方法。使用概率公钥加密算法加密数据;在云中数据通过搜索其空间关键词进行文件检索;在确保数据准确性和隐私安全性的前提下,实现云计算中移动设备外包数据安全有效加密后的隐私保护。仿真实验结果表明,该方案不仅可以确保数据隐私和计算速度,同时能够减少通信开销。相比于双轮可搜索加密(TRSE)方案、可排序多关键词检索加密(MRSE)方案和实时循环移位加密(RRSE)等方案,该方案在可行性和计算效率方面都有所提升。     

TraceChain: A blockchain-based scheme to protect data confidentiality and traceability

The risk of sharing data in cloud computing has gathered increasing attention. After the owner of some confidential data outsources the data to cloud storage services and shares it with others, the data owner lost the control to the data to a large extent. To achieve data sharing while keeping data confidentiality, attribute-based encryption (ABE) can be employed by cloud storage services. However, ABE can only guarantee that outsourced data on the cloud is decrypted by attribute-satisfying users but cannot restrict data from being accessed by dishonest users whose attributes also satisfy the access-control policy. It is impossible for the data owner to control the shared data after it has been decrypted by dishonest users, especially when a set of attribute-satisfying dishonest users may collude. To address this concern, we propose a traceable data sharing scheme called TraceChain. In TraceChain, data is encrypted over a new CP-ABE scheme called E-CP-ABE. Furthermore, the system parameters for generating the private key in E-CP-ABE are uploaded to the private blockchain and transactions are performed on the chain. The data owner can obtain the identity of users by monitoring system parameters simultaneously and control data sharing on the blockchain. To prove the security of our scheme, the security analysis is given in this paper. Meanwhile, experimental results also show that our system is viable and efficient.     

Oblivious access control policies for cloud based data sharing systems

Conventional procedures to ensure authorized data access by using access control policies are not suitable for cloud storage systems as these procedures can reveal valid access parameters to a cloud service provider. In this paper, we have proposed oblivious access control policy evaluation (O-ACE); a data sharing system, which obliviously evaluates access control policy on a cloud server and provisions access to the outsourced data. O-ACE reveals no useful information about the access control policy neither to the cloud service provider nor to the unauthorized users. Through the security analysis of O-ACE it has been observed that computational complexity to compromise privacy of the outsourced data is same as reverting asymmetric encryption without valid key pair. We have realized O-ACE for Google Cloud. Our evaluation results show the fact that O-ACE CPU utilization cost is 0.01–0.30 dollar per 1,000 requests.     

Improved security of a dynamic remote data possession checking protocol for cloud storage

Cloud storage offers the users with high quality and on-demand data storage services and frees them from the burden of maintenance. However, the cloud servers are not fully trusted. Whether the data stored on cloud are intact or not becomes a major concern of the users. Recently, Chen et al. proposed a remote data possession checking protocol to address this issue. One distinctive feature of their protocol support data dynamics, meaning that users are allowed to modify, insert and delete their outsourced data without the need to re-run the whole protocol. Unfortunately, in this paper, we find that this protocol fails to achieve its purpose since it is vulnerable to forgery attack and replace attack launched by a malicious server. Specifically, we show how a malicious cloud server can deceive the user to believe that the entire file is well-maintained by using the meta-data related to the file alone, or with only part of the file and its meta-data. Then, we propose an improved protocol to fix the security flaws and formally proved that our proposal is secure under a well-known security model. In addition, our improvement keeps all the desirable features of the original protocol.     

Cloud data integrity checking with an identity-based auditing mechanism from RSA

Cloud data auditing is extremely essential for securing cloud storage since it enables cloud users to verify the integrity of their outsourced data efficiently. The computation overheads on both the cloud server and the verifier can be significantly reduced by making use of data auditing because there is no necessity to retrieve the entire file but rather just use a spot checking technique. A number of cloud data auditing schemes have been proposed recently, but a majority of the proposals are based on Public Key Infrastructure (PKI). There are some drawbacks in these protocols: (1) It is mandatory to verify the validity of public key certificates before using any public key, which makes the verifier incur expensive computation cost. (2) Complex certificate management makes the whole protocol inefficient. To address the key management issues in cloud data auditing, in this paper, we propose ID-CDIC, an identity-based cloud data integrity checking protocol which can eliminate the complex certificate management in traditional cloud data integrity checking protocols. The proposed concrete construction from RSA signature can support variable-sized file blocks and public auditing. In addition, we provide a formal security model for ID-CDIC and prove the security of our construction under the RSA assumption with large public exponents in the random oracle model. We demonstrate the performance of our proposal by developing a prototype of the protocol. Implementation results show that the proposed ID-CDIC protocol is very practical and adoptable in real life.     

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.     

Security and Control in the Cloud

ABSTRACT

Cloud computing is a new IT delivery paradigm that offers computing resources as on-demand services over the Internet. Like all forms of outsourcing, cloud computing raises serious concerns about the security of the data assets that are outsourced to providers of cloud services. To address these security concerns, we show how today's generation of information security management systems (ISMSs), as specified in the ISO/IEC 27001:2005, must be extended to address the transfer of security controls into cloud environments. The resulting virtual ISMS is a standards-compliant management approach for developing a sound control environment while supporting the various modalities of cloud computing.

This article addresses chief security and/or information officers of cloud client and cloud provider organizations. Cloud clients will benefit from our exposition of how to manage risk when corporate assets are outsourced to cloud providers. Providers of cloud services will learn what processes and controls they can offer in order to provide superior security that differentiates their offerings in the market.     

Ownership-hidden group-oriented proofs of storage from pre-homomorphic signatures

In this paper, we study the problem of secure cloud storage in a multi-user setting such that the ownership of outsourced files can be hidden against the cloud server. There is a group manager for initiating the system, who is also responsible for issuing private keys for the involved group members. All authorized members are able to outsource files to the group’s storage account at some cloud server. Although the ownership of outsourced file is preserved against the cloud server, the group manager could trace the true identity of any suspicious file for liability investigation. To address this issue, we introduce and formalize a notion of ownership-hidden group-oriented proofs of storage (OPoS). We present a generic OPoS construction from pre-homomorphic signatures, and propose an OPoS instantiation by employing the Boneh–Boyen short signature. We show that the OPoS instantiation can be optimized using a polynomial commitment technique, so that the integrity auditing protocol would only take constant-size communication overheads by the cloud server. Theoretical and experimental analyses show that our OPoS instantiations are efficient and practical for enterprise-oriented cloud storage applications. Also, we show that the OPoS instantiations can be enhanced to safeguard against a dynamic set of corrupted members, as well as support batch integrity auditing mechanism.     

Secured Data Storage Using Deduplication in Cloud Computing Based on Elliptic Curve Cryptography

The tremendous development of cloud computing with related technologies is an unexpected one. However, centralized cloud storage faces few challenges such as latency, storage, and packet drop in the network. Cloud storage gets more attention due to its huge data storage and ensures the security of secret information. Most of the developments in cloud storage have been positive except better cost model and effectiveness, but still data leakage in security are billion-dollar questions to consumers. Traditional data security techniques are usually based on cryptographic methods, but these approaches may not be able to withstand an attack from the cloud server's interior. So, we suggest a model called multi-layer storage (MLS) based on security using elliptical curve cryptography (ECC). The suggested model focuses on the significance of cloud storage along with data protection and removing duplicates at the initial level. Based on divide and combine methodologies, the data are divided into three parts. Here, the first two portions of data are stored in the local system and fog nodes to secure the data using the encoding and decoding technique. The other part of the encrypted data is saved in the cloud. The viability of our model has been tested by research in terms of safety measures and test evaluation, and it is truly a powerful complement to existing methods in cloud storage.     

Towards Public Integrity Audition for Cloud-IoT Data Based on Blockchain

With the rapidly developing of Internet of Things (IoT), the volume of data generated by IoT systems is increasing quickly. To release the pressure of data management and storage, more and more enterprises and individuals prefer to integrate cloud service with IoT systems, in which the IoT data can be outsourced to cloud server. Since cloud service provider (CSP) is not fully trusted, a variety of methods have been proposed to deal with the problem of data integrity checking. In traditional data integrity audition schemes, the task of data auditing is usually performed by Third Party Auditor (TPA) which is assumed to be trustful. However, in real-life TPA is not trusted as people thought. Therefore, these schemes suffer from the underlying problem of single-point failure. Moreover, most of the traditional schemes are designed by RSA or bilinear map techniques which consume heavy computation and communication cost. To overcome these shortcomings, we propose a novel data integrity checking scheme for cloud-IoT data based on blockchain technique and homomorphic hash. In our scheme, the tags of all data blocks are computed by a homomorphic hash function and stored in blockchain. Moreover, each step within the process of data integrity checking is signed by the performer, and the signatures are stored in blockchain through smart contracts. As a result, each behavior for data integrity checking in our scheme can be traced and audited which improves the security of the scheme greatly. Furthermore, batch-audition for multiple data challenges is also supported in our scheme. We formalize the system model of our scheme and give the concrete construction. Detailed performance analyses demonstrate that our proposed scheme is efficient and practical without the trust-assumption of TPA.     

基于企业外包存储的可行模型研究

近年来,随着数据价值的不断提升和数据量的飞速增长,外包存储获得越来越广泛的应用,但企业该如何实施自己的外包存储？本文对企业外包存储可能的模型进行了阐述,从安全和性能上对各模型进行了比较分析,最后归纳了各种模型的优缺点及适用情况。     

Secure sharing of Personal Health Records in cloud computing: Ciphertext-Policy Attribute-Based Signcryption

The sharing of Personal Health Records (PHR) in cloud computing is a promising platform of health information exchange. However, the storage of personal medical and health information is usually outsourced to some third parties which may result in the exposure of patients’ privacy to unauthorized individuals or organizations. In order to address this security loophole, we suggest a promising solution. We propose a new approach for fine-grained access control and secure sharing of signcrypted (sign-then-encrypt) data. We call our new primitive Ciphertext-Policy Attribute-Based Signcryption (CP-ABSC) which satisfies the requirements of cloud computing scenarios for PHR. CP-ABSC combines the merits of digital signature and encryption to provide confidentiality, authenticity, unforgeability, anonymity and collusion resistance. The correctness, security and efficiency of this scheme are also proven.     

Data storage auditing service in cloud computing: challenges,methods and opportunities

Cloud computing is a promising computing model that enables convenient and on-demand network access to a shared pool of configurable computing resources. The first offered cloud service is moving data into the cloud: data owners let cloud service providers host their data on cloud servers and data consumers can access the data from the cloud servers. This new paradigm of data storage service also introduces new security challenges, because data owners and data servers have different identities and different business interests. Therefore, an independent auditing service is required to make sure that the data is correctly hosted in the Cloud. In this paper, we investigate this kind of problem and give an extensive survey of storage auditing methods in the literature. First, we give a set of requirements of the auditing protocol for data storage in cloud computing. Then, we introduce some existing auditing schemes and analyze them in terms of security and performance. Finally, some challenging issues are introduced in the design of efficient auditing protocol for data storage in cloud computing.     

Privacy-preserving edge-assisted image retrieval and classification in IoT

Internet of Things (IoT) has drawn much attention in recent years. However, the image data captured by IoT terminal devices are closely related to users’ personal information, which are sensitive and should be protected. Though traditional privacy-preserving outsourced computing solutions such as homomorphic cryptographic primitives can support privacy-preserving computing, they consume a significant amount of computation and storage resources. Thus, it becomes a heavy burden on IoT terminal devices with limited resources. In order to reduce the resource consumption of terminal device, we propose an edge-assisted privacy-preserving outsourced computing framework for image processing, including image retrieval and classification. The edge nodes cooperate with the terminal device to protect data and support privacy-preserving computing on the semitrusted cloud server. Under this framework, edge-assisted privacy-preserving image retrieval and classification schemes are proposed in this paper. The security analysis and performance evaluation show that the proposed schemes greatly reduce the computational, communication and storage burden of IoT terminal device while ensuring image data security.     

A secure re‐encryption scheme for data services in a cloud computing environment

Cloud computing as a promising technology and paradigm can provide various data services, such as data sharing and distribution, which allows users to derive benefits without the need for deep knowledge about them. However, the popular cloud data services also bring forth many new data security and privacy challenges. Cloud service provider untrusted, outsourced data security, hence collusion attacks from cloud service providers and data users become extremely challenging issues. To resolve these issues, we design the basic parts of secure re‐encryption scheme for data services in a cloud computing environment, and further propose an efficient and secure re‐encryption algorithm based on the EIGamal algorithm, to satisfy basic security requirements. The proposed scheme not only makes full use of the powerful processing ability of cloud computing but also can effectively ensure cloud data security. Extensive analysis shows that our proposed scheme is highly efficient and provably secure under existing security model. Copyright © 2015 John Wiley & Sons, Ltd.     

分布式云灾备平台搭建及性能分析

云存储服务,作为云计算的衍生产物,目的是为网络海量数据的存储提供有效的解决方案,节约存储成本和系统资源,提供一个完善的备份、容灾的数据中心,并能够保证数据安全性、容错性.现阶段云灾备模型局限于有限的网络位置,使用虚拟化技术,依托本地服务器实现,与传统云灾备模型不同,介绍了一种基于DHT的云灾备模型,可适用于广域网的、普适的数据级灾备解决方案;最后,在本地云计算集群中对该方案进行模拟,验证该模型的可行性.