Private data deduplication protocols in cloud storage

<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>

Deduplication of encrypted data is a significant function for both the privacy of stored data and efficient storage management. Several deduplication techniques have been designed to provide improved security or efficiency. In this study, we focus on the client-side deduplication technique, which has more advantages than the server-side deduplication technique, particularly in communication overhead, owing to conditional data transmissions. From a security perspective, poison, dictionary, and identification attacks are considered as threats against client-side deduplication. Unfortunately, in contrast to other attacks, identification attacks and the corresponding countermeasures have not been studied in depth. In identification attacks, an adversary tries to identify the existence of a specific file. Identification attacks should be countered because adversaries can use the attacks to break the privacy of the data owner. Therefore, in the literature, some counter-based countermeasures have been proposed as temporary remedies for such attacks. In this paper, we present an analysis of the security features of deduplication techniques against identification attacks and show that the lack of security of the techniques can be eliminated by providing uncertainness to the conditional responses in the deduplication protocol, which are based on the existence of files. We also present a concrete countermeasure, called the time-locked deduplication technique, which can provide uncertainness to the conditional responses by withholding the operation of the deduplication functionality until a predefined time. An additional cost for locking is incurred only when the file to be stored does not already exist in the server’s storage. Therefore, our technique can improve the security of client-side deduplication against identification attacks at almost the same cost as existing techniques, except in the case of files uploaded for the first time.

Distributed networks remarkably enhance the convenience of network connectivity. How to achieve efficient cooperative computation while preserving data privacy is a challenge in the scenario of distributed networks. Secure computation, as the key technology of information security and privacy protection in the distributed networks, attracts more and more attention. In the paper, we develop the protocols of secure two-party computation in the presence of malicious adversaries which are constructed with homomorphic probabilistic cryptosystem, and propose four honest-verifier zero-knowledge proof protocols to detect two cheating behaviours of the malicious adversary. The proposed protocols are more targeted than the existing work. The analysis shows that the proposed protocols are complete, sound and zero-knowledge. As an application, we show how to use our protocols in a secure two-party protocol to detect cheating, which can make it secure in the presence of malicious adversaries.

In this paper we show that using standard smartcards it is possible to construct truly practical secure protocols for a variety of tasks. Our protocols achieve full simulation-based security in the presence of malicious adversaries, and can be run on very large inputs. We present protocols for secure set intersection, oblivious database search and more. We have also implemented our set intersection protocol in order to show that it is truly practical: on sets of size 30,000 elements takes 20 seconds for one party and 30 minutes for the other (where the latter can be parallelized to further reduce the time). This demonstrates that in settings where physical smartcards can be sent between parties (as in the case of private data mining tasks between security and governmental agencies), it is possible to use secure protocols with proven simulation-based security.

Student health records play a pivotal role in nursing education, offering a comprehensive insight into students' health histories, immunization statuses, and clinical experiences. This study aims to identify the challenges and specific needs of NEUST-CON students to develop an efficient health record management system, design an Electronic Medical Record that outlines data collection, storage, security, and access protocols, and create a system prototype incorporating essential features and functionalities based on user requirements. This study utilizes applied quantitative research to gather numerical data, objectively measuring factors like the frequency and impact of issues related to record accessibility, availability, data retrieval and update, and data security and privacy. Furthermore, it employs a descriptive correlational design to examine the relationships between the demographic profile and the challenges on the student health information record system among NEUST-CON students. Findings revealed that most nursing students at NEUST are female, aged 18 to 21, primarily in their first year. The study identified challenges related to availability, accessibility, data retrieval and update, and data security and privacy in student health information records. Notably, availability emerged as the most pressing challenge. While overall satisfaction was reported among respondents, data security and privacy concerns persisted. A significant relationship was also observed between students' year levels and ages. Therefore, enhancements in infrastructure and functionalities are essential to ensure consistent availability of data and resources, mitigating downtime and ensuring uninterrupted access to the SHIR prototype system.

Cloud auditing is a mechanism that can effectively check the integrity of outsourced data stored on cloud servers without the need to download whole data. Identity-based cloud auditing schemes avoid the dependency issues of public key infrastructure and certificate management in traditional auditing protocols, and have therefore received widespread attention and research. Fuzzy identities, represented by biometric features, have the advantages of being easy to carry, not easily lost or damaged, which also provides convenience for sharing cloud storage data. Therefore, how to apply fuzzy identity technology to cloud auditing is a meaningful research question. Based on the current research on identity-based cloud audit mechanism, this paper proposes a fuzzy identity-based cloud audit scheme that can achieve secure access control of storage data in the process of sharing. This solution not only enables reliable auditing of remote data, but also allows other users to use fuzzy identities for secure access control. In order to avoid privacy information leakage during the data sharing process, key information will be hidden during the data upload processing stage. In addition, detailed security proof will be provided for the designed protocol based on standard cryptographic assumptions. Finally, the performance analysis issues, such as communication overhead, computational cost, and storage redundancy, are also considered, which are compared with related research works. The results indicate that our proposed scheme has certain performance advantages.

The new development trends including Internet of Things (IoT), smart city, enterprises digital transformation and world's digital economy are at the top of the tide. The continuous growth of data storage pressure drives the rapid development of the entire storage market on account of massive data generated. By providing data storage and management, cloud storage system becomes an indispensable part of the new era. Currently, the governments, enterprises and individual users are actively migrating their data to the cloud. Such a huge amount of data can create magnanimous wealth. However, this increases the possible risk, for instance, unauthorized access, data leakage, sensitive information disclosure and privacy disclosure. Although there are some studies on data security and privacy protection, there is still a lack of systematic surveys on the subject in cloud storage system. In this paper, we make a comprehensive review of the literatures on data security and privacy issues, data encryption technology, and applicable countermeasures in cloud storage system. Specifically, we first make an overview of cloud storage, including definition, classification, architecture and applications. Secondly, we give a detailed analysis on challenges and requirements of data security and privacy protection in cloud storage system. Thirdly, data encryption technologies and protection methods are summarized. Finally, we discuss several open research topics of data security for cloud storage.

The smart collection and sharing of data is an important part of cloud-based systems, since huge amounts of data are being created all the time. This feature allows users to distribute data to particular recipients, while also allowing data proprietors to selectively grant access to their data to users. Ensuring data security and privacy is a formidable task when selective data is acquired and exchanged. One potential issue that emerges is the risk that data may be transmitted by cloud servers to unauthorized users or individuals who have no interest in the particular data or user interests. The prior research lacks comprehensive solutions for balancing security, privacy, and usability in secure data selective sharing schemes inside Cloud-Based decentralized trust management systems. Motivating factors for settling this gap contain growing concerns concerning data privacy, the necessity for scalable and interoperable frameworks, and the increasing dependency on cloud services for data storage and sharing, which necessitates robust and user-friendly mechanisms for secure data management. An effective and obviously secure data selective sharing and acquisition mechanism for cloud-based systems is proposed in this work. We specifically start by important a common problematic related to the selective collection and distribution of data in cloud-based systems. To address these issues, this study proposes a Cloud-based Decentralized Trust Management System (DTMS)-connected Efficient, Provably Secure Data Selection Sharing Scheme (EPSDSS). The EPSDSS approach employs attribute-based encryption (ABE) and proxy re-encryption (PRE) to provide fine-grained access control over shared data. A decentralized trust management system provides participant dependability and accountability while mitigating the dangers of centralized trust models. The EPSDSS-PRE paradigm would allow data owners to regulate granular access while allowing users to customize data collection without disclosing their preferences. In our strategy, the EPSDSS recognizes shared data and generates short fingerprints for information that can elude detection before cloud storage. DTMS also computes user trustworthiness and improves user behaviour administration. Our research demonstrates that it’s able to deliver trustworthy and safe data sharing features in cloud-based environments, making it a viable option for enterprises seeking to protect sensitive data while maximizing collaboration and utilization of resources.

With the development of cloud storage, data owners no longer physically possess their data and thus how to ensure the integrity of their outsourced data becomes a challenging task. Several protocols have been proposed to audit cloud storage, all of which rely mainly on data block tags to check data integrity. However, their block tag constructions employ cryptographic operations, which makes them computationally complex. In this paper, we investigate a secure cloud storage protocol based on the classic discrete logarithm problem. Our protocol generates data block tags with only basic algebraic operations, which brings substantial computation savings compared with previous work. We also strictly prove that the proposed protocol is secure under a definition which captures the real-world uses of cloud storage. In order to fit more application scenarios, we extend the proposed protocol to support data dynamics by employing an index vector and third-party public auditing by using a random masking number, both of which are efficient and provably secure. At last, theoretical analysis and experimental evaluation are provided to validate the superiority of the proposed protocol.

Secure computation protocols inherently involve multiple rounds of interaction among the parties where, typically a party has to keep a state about what has happened in the protocol so far and then wait for the other party to respond. We study if this is inherent. In particular, we study the possibility of designing cryptographic protocols where the parties can be completely stateless and compute the outgoing message by applying a single fixed function to the incoming message (independent of any state). The problem of designing stateless secure computation protocols can be reduced to the problem of designing protocols satisfying the notion of resettable computation introduced by Canetti, Goldreich, Goldwasser and Micali (FOCS'01) and widely studied thereafter. The current start of art in resettable computation allows for construction of protocols which provide security only when a single predetermined party is resettable [15]. An exception is for the case of the zero-knowledge functionality for which a protocol in which both parties are resettable was recently obtained by Deng, Goyal and Sahai (FOCS'09). The fundamental question left open in this sequence of works is, whether fully-resettable computation is possible, when: 1) An adversary can corrupt any number of parties, and 2) The adversary can reset any party to its original state during the execution of the protocol and can restart the protocol. In this paper, we resolve the above problem by constructing secure protocols realizing any efficiently computable multi-party functionality in the plain model under standard cryptographic assumptions. First, we construct a Fully-Resettable Simulation Sound Zero-Knowledge (ss-rs-rZK) protocol. Next, based on these ss-rs-rZK protocols, we show how to compile any semi-honest secure protocol into a protocol secure against fully resetting adversaries. Next, we study a seemingly unrelated open question: "Does there exist a functionality which, in the concurrent setting, is impossible to securely realize using BB simulation but can be realized using NBB simulation?". We resolve the above question in the affirmative by giving an example of such a (reactive) functionality. Somewhat surprisingly, this is done by making a connection to the existence of a fully resettable simulation sound zero-knowledge protocol.

Cloud computing paradigm builds on the foundations of distributed computing, grid computing, virtualisation, service orientation, etc. Cloud storage, which is one of the most attractive cloud services, offers numerous benefits from both the technology and functionality perspectives such as increased availability, flexibility, and functionality. Therefore, Cloud-based platforms have become fundamental to collaborative and data management systems. However, the new Cloud environment creates major collaborative and data management challenges such as efficient and reliable remote storage, online data query processing, data integrity, outsourcing computation, and secure virtualisation, among others. Such issues need to be carefully studied and solved to enable the wide deployment and adoption of Cloud computing in businesses, industry, etc. The purpose of this special issue is to publish recent advances in Cloud-based collaborative systems and Cloud storage. The special issue comprises five high-quality papers, which are arranged as follows. De Maio et al in the first paper1 “Social Media Marketing through Time-Aware Collaborative Filtering,” define a time-aware collaborative filtering for estimating users' interest along the time in Twitter. Their approach uses text analysis services to semantically annotate tweets' content and to track concepts considering post frequencies along the time. A model-based approach implementing K-Nearest Neighbors is used to estimate user's similarity representing their profile by sampling user's interest with three different techniques: Vectorial Representation, Symbolic Aggregation Approximation, and Median. The authors present experimental results comparing these techniques and performing model training in different time windows. The second paper2 “SERNOTATE: An Automated Approach for Business Service Description Annotation for efficient Service Retrieval and Composition” by Chotipant et al proposes an automated approach, namely, SERNOTATE, for business service description annotation for efficient service retrieval and composition. To that end, the authors employ new semantic-based linking approaches, namely, Extended Case-based Reasoning, Vector-based and Classification-based, that automatically annotate business services to relevant service concepts. The experimental results test and validate the applicability of the proposed approaches to the automatic annotation of business service descriptions to service concepts on a real-world dataset. In the third paper,3 “Sensor Data Management in the Cloud: Data Storage, Data Ingestion, and Data Retrieval,” the authors address an increasing need to capture, store, and analyse the dynamic semistructured data from sensors. A similar growth of semistructured data in the modern Web has led to the creation of NoSQL data stores for scalability, availability, and performance, whereas large-scale data processing frameworks for parallel analysis. The authors study how sensor data management can benefit from MongoDB with Apache Spark technologies, specifically for ingesting high-velocity sensor data and parallel retrieval of high volume data. The performance of MongoDB sharding and no-sharding databases with Apache Spark are evaluated to identify the right software environment for sensor data management. Park et al in the fourth paper,4 “Study on the SDN-IP based Solution of Well-known Bottleneck Problems in Private Sector of National R&E Network for Big Data Transfer,” deal with issues arising in Software Defined Networking (SDN). The key feature of SDN networks is the provisioning of dynamic service architecture. Therefore, it is more appropriate for the big data science computing trends, for handling today's big data science, which requires massive parallel processing and a constant demand for additional capacity and on demand connectivity. The authors bring the experience from KREONET (Korea Research Environment Open Network) and Korea National R&E Network, which adopt SDN as a platform service for big data scientific application. The big data application for KREONET SDN service comprises high-energy physics, astrophysics, biology/genetics, meteorology, artificial satellite data, etc. The last paper5 “Improved Outsourced Private Set Intersection Protocol Based on Polynomial Interpolation” by Yang et al investigates issues in private set intersection (PSI) protocols, which enable two parties to compute the intersection of their inputs without compromising anything about the datasets beyond the intersection. The authors present a variant of delegated private set intersection protocol secure in the semi-honest model under RSA assumption as well as an efficient and secure outsourcing computation algorithm for RSA crypto-system. Based on this algorithm, the authors transform a variant of delegated private set intersection protocol into an improved outsourced one, which enables the clients to perform only simple modular multiplication for computing during the execution of the protocol. Compared with the state of the art, the proposed protocol has a great advantage in efficiency. The editor of this special issue would like to thank all authors for their contributions and the reviewers for their constructive and useful feedback to authors. I would like to thank Prof Geoffrey Fox, the Editor-in-Chief of Concurrency and Computation: Practice and Experience, for the opportunity to edit this special issue and his support.

Along with the widespread interest in cloud computing, there are still concerns that hinder the proliferation and the adoption of cloud services. One of the main concerns is data security in cloud storage environments. Numerous research problems belonging to cloud storage security have been studied intensively before. However, addressing the three dimensions of outsourced data security (i.e., confidentiality, availability, and integrity) as a cloud service is still a challenge in cloud storage. As there is always a tradeoff between maintaining security and obtaining efficiency, it is difficult but nevertheless essential to explore how to efficiently address security challenges over dynamic cloud data. This paper proposes an integrated security model for data storage in the cloud that provides authentication, access control, auditing and data management services. A strong authentication sub-system that is based on the traditional password and the user keystroke dynamics is presented. A dynamic access control system is proposed to ensure data confidentiality in cloud computing. A public auditing system is proposed to delegate the integrity verification of outsourced data in the cloud storage to a third party auditor while maintaining the data privacy. Experimental results demonstrate the effectiveness and efficiency of the proposed model.

Adaptive Oblivious Transfer Protocol with Hidden Access Policy (AOT-HAP) is a well known cryptographic primitive that combines each message of a database with an access policy which is kept hidden. The database is held by a sender who encrypts each message of the database under its access policy and publishes encrypted database in which access policies are embedded implicitly. A receiver possesses an attribute set and recovers the message correctly if the attribute set satisfies the access policy implicitly. Otherwise, a garbage message is recovered by the receiver. In this paper, an efficient \(\mathsf{AOT{\text {-}}HAP}\) is presented. The proposed protocol realizes more expressive access policies, i.e., conjunction as well as disjunction of attributes. The proposed \(\mathsf{AOT{\text {-}}HAP}\) is secure assuming the hardness of standard assumptions in the presence of malicious adversary in full-simulation security model. It exhibits significant improvement over the existing similar schemes in terms of both communication and computation.KeywordsOblivious transferAccess policyAttribute based encryptionFull simulation security model

Cloud data storage is a model of data storage where data in its digital form is stored in logical pools across the physical storage which is distributed across multiple servers usually in diverse locations. The full physical environment is owned and managed by an organization called Cloud Service Provider (CSP). In this type of storage, the data is distributed and owned by third party, and there is risk of unauthorized access. This makes security, reliability, confidentiality and privacy of data more important when storage in cloud is thought of. Although there are methods available for providing security, much work is not done with emphasis on dynamic nature of the data. Hence securing the data while updating becomes important. In this paper, a method that ensures confidentiality of data stored in cloud using homomorphic encryption is presented. The paper also provides a technique to ensure confidentiality during data updates in cloud. The presented method includes byte level automorphism for ensuring data integrity and confidentiality. The tabulated experimental results show that the proposed method provides more secure frame work for ensuring confidentiality and integrity of data in cloud.

With the development and application of cloud computing, cloud storage is becoming more and more popular with many organizations, but traditional principal-minor structure for cloud storage is at risk of single point of failure. Moreover, it has brought safety risk. Cloud storage security has become the key problem of restricting the development of cloud computing. The paper has a deep research of cloud storage structure and cloud storage security, proposes a entity authentication protocol for P2P cloud storage based on ternary Huffman Merkle hash tree (HuffMHT).This method using the concept of ternary HuffMHT can obtain an effective safe strategy. At the same time, symmetrical key algorithm and public key algorithm are just combined to reduce the authentication delay effectively and increase the network lifetime and enhances the security of the networks. Moreover, signatures of knowledge is used in this paper, which notes number of hash is reduced, the power which notes consume is debased, the network load is decreased. The performance of the system is discussed, and the encryption method has high efficiency and high security.