Improving public auditability, data possession in data storage security for cloud computing

The significance of the cloud enables the data owners (DOs) to store data remotely in cloud server (CS). The external and internal attacks on the stored data at CS can deliberately remove data. Furthermore, the CS removes the stored data to make empty location for the user's upcoming new data. However, it is a legal expectation of DOs to know whether their data are correctly stored or altered in CS. In this article, we propose a novel privacy-aware and hash-parity-bits-based public auditing (PA-HPPA) framework to secure full data, left half of the data, and the right half of the data, generated by a DO. DO generates two private key pairs with the assistance of a virtual key and a user ID (IP). The virtual key is the sequence number of DO who is registered and provided by the trusted data manager (TDM) while IP is the sequence number of DO working in an organization. Subsequently, DO blinds the categorized data and generates their signatures and hashes. In addition, DO generates the parity bits using xor and assigns to each hard drive (HD) in CS, which assistants to TDM in public auditing. Second, how to identify the error in the stored data and how to securely recover the error/missed data? Extension to the framework, the novel proposed data error identification and secure data recovery produce tags for installed HDs of CS using truth table and recover the altered/missed data via a authenticator, which is produced using xor function. Third, how to protect a valid user from revocation and, in case a user has revoked on merit basis, then how to securely access the stored data of it? This novel work has proposed three conditions to meet the validity of the valid user from revocation and securely generating the public-private key pairs to access the stored data of the revoked user securely from CS. Fourth, there is an efficient novel proposed dynamic operation scheme to insert, update, or delete the stored data at CS without regenerating the signatures, hashes, and tags for the whole stored data in cloud. The security analysis and the performance evaluation of the proposed solutions are provably efficient and secure with reduced communication costs.

We describe a novel approach for building a secure and fault tolerant data storage service in collaborative work environments, which uses perfect secret sharing schemes to store data. Perfect secret sharing schemes have found little use in managing generic data because of the high computation overheads incurred by such schemes. Our proposed approach uses a novel combination of XOR secret sharing and replication mechanisms, which drastically reduce the computation overheads and achieve speeds comparable to standard encryption schemes. The combination of secret sharing and replication manifests itself as an architectural framework, which has the attractive property that its dimension can be varied to exploit tradeoffs amongst different performance metrics. We evaluate the properties and performance of the proposed framework and show that the combination of perfect secret sharing and replication can be used to build efficient fault-tolerant and secure distributed data storage systems.

Cloud storage relieves the user from the local management of software and hardware by enabling high quality on demand storage services to store their data in remote locations. Storing the data in remote locations not only reduces the management overheads but also eliminates the user’s physical control over data storage and data security. The loss of physical control over data brings out various security issues such as data loss, tampering of data, data modification. The primary issue is to ensure the correctness of data stored in remote locations which can be resolved by enabling public auditing for cloud storage services. In public auditing, not only the user but anyone can verify the data correctness. The introduction of third-party auditor, who works on behalf of cloud user to verify data integrity helps to reduce user computation resources and cost. The key prerequisite for the public auditing protocol is to support dynamic data operations as data in cloud are dynamic in nature. Cloud is a multiuser environment, so the auditing protocol must scale well to handle multiple auditing processes simultaneously. This paper aims at an extensive survey which mainly outlines the requirements for cloud public auditability and compares varied public auditing protocols.

<span lang="EN-US">Cloud Computing is the ability to improve the utility or train new human resources without investing in new infrastructure, or add capabilities to existence without the latest software licensing. It expanded the capabilities of Information Technology (IT). From the past few years, cloud computing has developed from a good business concept in the best rising sectors of the IT industry. But more information on individuals and companies was put in the cloud, and concerns began to think about how secure the cloud environment was. Despite cloud surrounding structures, enterprise users still do not want to expand their business in the cloud. Security reduces the growth of cloud computing and continues to spread the market with complexity with data privacy and data protection. The security of cloud computing has constantly been an significant aspect of improved quality of service from cloud service providers. Data storage in the cloud has a problem related to data security. However, cloud computing construct many new security challenges which have not been well examine. In order to ensure that the user's data in the cloud is secure, we have proposed an effective mechanism with a distinctive feature of data integrity and privacy. This paper focusing on problems relating to the cloud data storage techniques and security in virtual environment. We recommend a method for providing data storage and security in cloud using public key Cryptosystem, which uses the concept of the modified RSA algorithm to provide better security for the data stored in the cloud. </span>

Cloud data storage outsourcing has emerged as a service that can facilitate data owners (DOs) to store their data remotely. Outsourcing health, educational, financial, multimedia data to cloud storage server is beneficial as it eliminate the burden of initial infrastructure setup and maintenance costs. However data storage security and integrity remains challenging due to lack of control and physical possession over the data by the DOs. In this paper we present a lightweight auditing method for integrity verification and deduplication of outsourced data. The proposed scheme combines hashing and symmetric encryption with improved distributed hash table data structure which reduces the communication and computation overhead for integrity verification and also enables efficient dynamic operations of the data. The storage cost is drastically decreased by deduplication using the combined techniques of convergent encryption and filters. The outcome of the proposed methodology demonstrates that this light weight data audit protocol outperforms the other state of art schemes in computation, communication and storage costs.

Data security storage technology is an important part of information management. The security of data storage is the key to user information security, system operation efficiency and economic benefits. The implementation of data security storage technology plays an important role in improving the efficiency of data management and reducing the operating costs of enterprises. Due to the data leakage caused by intentional or unintentional wrong operation, which infringes the user’s personal privacy, the traditional data storage methods face greater risks in the operation process. These disadvantages affect the use effect of the system, and even lead to system paralysis and data loss in serious cases. Distributed database has the characteristics of high degree of structure, good openness and small storage space requirements, and plays an important role in data management. In this paper, a data security storage model is studied combining the symmetric encryption algorithm, asymmetric encryption algorithm and the hash algorithm. A data security storage system is then proposed based on distributed storage while its functional composition, data transmission framework and database design are described. The proposed system in this paper is expected improve the data storage security so as to reduce the risks of information leakage.

JCDC: A blockchain-based framework for secure data storage and circulation in JointCloud

In recent years, wireless medical sensor networks meet the web to enable exciting healthcare applications that require data communication over the Internet. Often these applications suffer from data disclosure due to malicious users’ activities. To prevent such data disclosure in the healthcare systems, many public key cryptographic techniques have been used. However, most of them are too expensive to implement in the web-enabled wireless medical sensor networks. In 2013, Xun et al. introduced a lightweight encryption algorithm to protect communication between the sensor node and the data servers. Their scheme is based on the Sharemind framework. However, Sharemind framework has a limitation on the number of data storage servers (ie., three servers only). In addition, Xun et al’s scheme does not support privacy-preserving patient data analysis for distributed databases of different hospitals. In this paper, we introduce a new practical approach to prevent data disclosure from inside attack. Our new proposal is based on FairplayMP framework which enables programmers who are not experts in the theory of secure computation to implement such protocols. In addition, it support any number of n participants and is suitable for distributed environments. Moreover, in our new scheme, each sensor node needs only one secret key stored in advance to communicate with n different data servers, whereas three secret keys are embedded in advance into each sensor in order to communicate with three data servers in Xun et al’s scheme.

SummaryObjectives: To survey international regulatory frameworks that serve to protect privacy of personal data as a human right as well as to review the literature regarding privacy protections and data ownership in mobile health (mHealth) technologies between January 1, 2016 and June 1, 2019 in order to identify common themes.Methods: We performed a review of relevant literature available in English published between January 1, 2016 and June 1, 2019 from databases including PubMed, Google Scholar, and Web of Science, as well as relevant legislative background material. Articles out of scope (as detailed below) were eliminated. We categorized the remaining pool of articles and discrete themes were identified, specifically: concerns around data transmission and storage, including data ownership and the ability to re-identify previously de-identified data; issues with user consent (including the availability of appropriate privacy policies) and access control; and the changing culture and variable global attitudes toward privacy of health data.Results: Recent literature demonstrates that the security of mHealth data storage and transmission remains of wide concern, and aggregated data that were previously considered “de-identified” have now been demonstrated to be re-identifiable. Consumer-informed consent may be lacking with regard to mHealth applications due to the absence of a privacy policy and/or to text that is too complex and lengthy for most users to comprehend. The literature surveyed emphasizes improved access control strategies. This survey also illustrates a wide variety of global user perceptions regarding health data privacy.Conclusion: The international regulatory framework that serves to protect privacy of personal data as a human right is diverse. Given the challenges legislators face to keep up with rapidly advancing technology, we introduce the concept of a “healthcare fiduciary” to serve the best interest of data subjects in the current environment.

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.

Nanopores are powerful single-molecule tools for label-free sensing of nanoscale molecules including DNA that can be used for building designed nanostructures and performing computations. Here, DNA hard drives (DNA-HDs) are introduced based on DNA nanotechnology and nanopore sensing as a rewritable molecular memory system, allowing for storing, operating, and reading data in the changeable three-dimensional structure of DNA. Writing and erasing data are significantly improved compared to previous molecular storage systems by employing controllable attachment and removal of molecules on a long double-stranded DNA. Data reading is achieved by detecting the single molecules at the millisecond time scale using nanopores. The DNA-HD also ensures secure data storage where the data can only be read after providing the correct physical molecular keys. Our approach allows for easy-writing and easy-reading, rewritable, and secure data storage toward a promising miniature scale integration for molecular data storage and computation.

This study constructs a secure and efficient data storage and sharing architecture for the Internet of Vehicles. A practical Byzantine fault-tolerant consensus algorithm using reputation was proposed to address the shortcomings of roadside unit equipment in the architecture. The experimental results showed that in the performance verification of reinforced data storage, the storage proportion of the research scheme was always lower than that of the comparison algorithm. In the simulated 5000 transactions, it was always lower than 40 MB, while the comparison algorithm reached a maximum of 72 MB. The efficiency of querying registration information and vehicle data increased by 38.2% and 49.1%, respectively. In the shared performance verification, the fully loaded roadside unit devices decreased by a maximum of 2.8%. Under heavy load conditions, the fully loaded nodes decreased by a maximum of 20.7%. In the validation of the proposed consensus algorithm, its performance was more stable in terms of throughput, and the number of transactions processed per second by d (10) remained basically between 380 and 640. Overall, the constructed secure and efficient data storage and sharing architecture for the Internet of Vehicles is efficient and secure, which can be effectively applied in practical IoV systems.

With the fast development of industrial Internet of things (IIoT), a large amount of data is being generated continuously by different sources. Storing all the raw data in the IIoT devices locally is unwise considering that the end devices’ energy and storage spaces are strictly limited. In addition, the devices are unreliable and vulnerable to many threats because the networks may be deployed in remote and unattended areas. In this paper, we discuss the emerging challenges in the aspects of data processing, secure data storage, efficient data retrieval and dynamic data collection in IIoT. Then, we design a flexible and economical framework to solve the problems above by integrating the fog computing and cloud computing. Based on the time latency requirements, the collected data are processed and stored by the edge server or the cloud server. Specifically, all the raw data are first preprocessed by the edge server and then the time-sensitive data (e.g., control information) are used and stored locally. The non-time-sensitive data (e.g., monitored data) are transmitted to the cloud server to support data retrieval and mining in the future. A series of experiments and simulation are conducted to evaluate the performance of our scheme. The results illustrate that the proposed framework can greatly improve the efficiency and security of data storage and retrieval in IIoT.

Efficient integrity verification of replicated data in cloud computing system

Efficient secure data storage based on novel blockchain model over IoT-based smart computing systems