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Cloud storage greatly facilitates both individuals and organizations to share data over the Internet. However, there are several security issues that impede to outsource their data. Among various approaches introduced to overcome these issues, attribute-based encryption (ABE) provides secure and flexible access control on shared data, and thus is rather promising. But the original ABE is not adaptable to some special circumstances, where attributes are organized in a hierarchical structure, such as enterprises and official institutions. On the other hand, although the wide use of mobile devices enables users to conveniently access shared data anywhere and anytime, this also increases the risk of key exposure, which will result into unwanted exposure of the shared data. In this paper, we extend the functionality of the original ABE and enhance its security by providing key generation delegation and forward security. Consequently, the enhanced ABE meets applications of large organizations with hierarchies and minimizes the damage in the case of unexpected key exposures. Specifically speaking, we present a forward-secure ciphertext-policy hierarchical attribute-based encryption scheme in prime order bilinear groups, as a core building of attribute-based data sharing scheme. The security of the proposed scheme is proven in the standard model. We conduct experiments to demonstrate its efficiency and practicability.

A cloud storage system which incorporates the deletion and deduplication functionalities will have both security and efficiency advantages over exiting solutions which provide only one of them. However, the security models of secure data deletion and data deduplication functionalities are not compatible with each other, which will cause security and efficiency vulnerability under coercive adversaries. To solve these security and efficiency challenges, we define and construct a scheme, whose security relies on the proper erasure of keys in the wrapped key tree and periodical update of the deduplication encryption keys. Moreover, we enhance the efficiency of the proposed scheme by introducing incremental data update, where only the changed part is encrypted/decrypted and uploaded/downloaded in data updating. Further security analysis shows that the proposed scheme is secure against coercive attack. Finally, the practical implementation shows that our scheme is performance efficient in computation, storage and communication for both the cloud storage server and users.

In recent years, intense usage of computing has been the main strategy of investigations in several scientific research projects. The progress in computing technology has opened unprecedented opportunities for systematic collection of experimental data and the associated analysis that were considered impossible only few years ago.

This paper focuses on the strategies in use: it reviews the various components that are necessary for an effective solution that ensures the storage, the long term preservation, and the worldwide distribution of large quantities of data that are necessary in a large scientific research project.

The paper also mentions several examples of data management solutions used in High Energy Physics for the CERN Large Hadron Collider (LHC) experiments in Geneva, Switzerland which generate more than 30,000 terabytes of data every year that need to be preserved, analyzed, and made available to a community of several tenth of thousands scientists worldwide.

By advances in cloud storage systems, users have access to the data saved in the cloud and can manipulate the data without limitation of time and place. As the data owner no longer possesses data physically, he is required to ensure the integrity of the data stored in the cloud with the public key given by public key infrastructure (PKI). Thus the security of PKI and certificates are essential. However, there are numerous security risks in the traditional PKI and it is complex to administer the certificates. Certificateless public key cryptography is used in this paper to solve these problems. We also use elliptic curve group to reduce computation overhead. In this paper, we design a certificateless public verification mechanism to check the integrity of data outsourced in the cloud and we further extend it to support a multiuser group by batch verification. Specifically, a public verifier who replaces the data owner to check the integrity in the proposed scheme does not require to manage any certificates during the verification process. Meanwhile, a verifier is not required to download the entire file for integrity checking. Theoretical analyses verify the security of our scheme and experimental results show its efficiency.

Traditional image encryption methods typically make a trade-off between privacy protection and visual usability. To address this issue, a novel thumbnail-preserving encryption scheme is proposed based on a hybrid of decimal and binary pixel values in three pixel groups, utilizing the excellent dynamic characteristics of a generalized coupled logistic map. Theoretically, it is proved that the core algorithm of this scheme is sum-preserving. Experimentally, it is demonstrated that this scheme not only excels in efficiency and resistance to attacks, effectively safeguarding image privacy, but also retains high-quality thumbnails after encryption, achieving both objectives of image privacy protection and visual usability.

This paper considers a cloud provider selection problem to optimize the cloud-redundant array of independent disks (RAID) storage system subject to imperfect coverage (IPC), where an uncovered disk fault causes extensive damages to the entire system despite the presence of adequate redundancy. Given available cloud storage disk providers with disks having different costs, failure parameters and coverage factors, the objective of the optimal design is to select the combination of cloud providers minimizing system unreliability or cost. Both unconstrained and constrained optimization problems are considered. The solution methodology encompasses an analytical, combinatorial method for reliability analysis of the considered cloud-RAID storage system with the IPC behavior. Based on practical design parameters, the brute force approach is utilized to obtain the optimal design configuration. Several case studies are provided to illustrate the proposed optimization problems and solution method.

This paper uses the chaotic fuzzy encryption (CFE) technique and a greedy chemical reaction optimization algorithm based on mobile cloud computing to protect data from any assault. Mobile users who use protected mobile cloud computing (Mobi-Cloud) must trust the cloud service provider to keep the data sent from their mobile devices safe when mobile users express strong reservations about storing personal information in the public cloud. The Greedy Chemical Reaction Optimization (G-CRO) algorithm reduces critical limitations by determining the offloading end with motion at run time, i.e. the task’s operating time, CPU usage, memory utilization, and energy usage. The experimental results show that the proposed method performs better in terms of file uploading time, file downloading time, memory usage in file uploading, memory usage in file downloading, encryption time, decryption time, memory usage on file encryption, memory usage on file decryption, security levels, and key generation time. Compared to the Proxy Re-Encryption (PRE) algorithm, the suggested method consumes less time for key creation (26.04).

Nowadays, improving a crop yield ($C_Y$) is an emerging and essential task to reduce food scarcity. Factors impacting $C_Y$ improvement include rising population, water shortage, fertilizer use, climate change and unprecedented insect attacks. To resolve these issues, a smart agriculture technique is proposed in this work. Internet of Things (IoT) sensor devices are used to collect data from farms, following which the fuzzy association rule-based classification technique classifies the data into two, valuable and nonvaluable. An improved artificial neural network (IANN) algorithm is applied to identify and analyze the factors involved in monitoring $C_Y$’s. Thereafter, all valuable data pertaining to the type of seed, fertilizer and crop cost is stored in blocks to secure data and communication between members of the farming community. Finally, an edge computing device is used to store the blocks and transfer information. The valuable data collected is classified using the fuzzy association rule and analyzed using the IANN technique, both of which facilitate a comparison with the historical data so as to enable better decision making in terms of seed and fertilizer selection. Similarly, crop price is predicted through a comparison of present and historical yields. To overcome breaches in security, a blockchain technique is employed in this work to secure communication between farmers, investors and merchants. The investor dispatches instructions on the selection of the seed and fertilizer, as well as the crop cost, through the blockchain to the farmer and the merchant. Such secure communication bypasses third-party involvement and inconsistencies in the data. When compared to the traditional method, the proposed technique offers better accuracy and profits, right from seed selection to trading. The proposed IANN technique produced a higher yield than the traditional method with a profit of 51%, 35% and 20% for rice, bananas and flowers, respectively. Similarly, the IANN technique provides 99.15% prediction accuracy in terms of a profit analysis. The blockchain and edge computing-based transactions improve security and reduce transactional latency. The proposed system ensures sustainability and traceability in agriculture.

Cloud storage has seen an increasing trend with the development of social networks, but its security remains an important problem to be solved. In this paper, a new encryption scheme based on dynamic attributes is proposed to solve the problem in the attribute based encryption scheme. In the scheme, a data encryption access control strategy is generated by the sender attributes according to certain logical relationships. Additionally, an access control tree structure is used to describe the access control policy. Only when the attribute set of receiver meets the access policy can the data be decrypted; to achieve this, the access control tree structure is dynamically adjusted simultaneously with changes in the attribute set of sender.

To tackle the problems of encrypted cloud storage in a limited bandwidth environment, we proposed a scheme that divided encryption block of plaintext according to the content changes. The scheme based on the optimized AES algorithm and exhibits improved efficiency and security of data synchronizing in the limited bandwidth environment.

With the rapid development of the e-business, social networking and enterprise information system, the volume of data produced by individuals and enterprises is increasing rapidly, resulting in a rise of cloud storage as an increasing number of enterprises and individuals store their data in the cloud for greater flexibility and economic savings. However the risk of leakage of sensitive user data is still prevalent. Although several keyword search schemes over encrypted data with privacy preserving has been previously proposed, we propose a novel scheme to support the multi-keywords fuzzy search while also supporting Chinese search. We utilize the locality-sensitive hashing technique to solve the fuzzy match and the experiments on real-world data demonstrate that our proposed scheme is accurate, efficient and secure.

Access control plays an important role in cloud storage. Attribute-based encryption enables the data owner embedded the access policy in the data. Many solutions have been proposed to ensure data security on cloud. However, in the existing indirectly revocation schemes, the efficiency and computational costs need to be improved. In order to realize fine-grained access control and reduce the computing burden of the data owner and users, we propose a scheme which includes attribute-based access control with revocation. The scheme could ensure data security, achieve higher computing efficiency and realize expressive policy.