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The purpose of this paper is to compare and evaluate the personal cloud storage products (PCSPs) in China and find the gap among them for promoting their service level. There are five representative products including Baidu cloud, Tencent cloud, Qihoo 360-cloud, Kingsoft cloud and Huawei DBank.

This study, first, extracts corresponding indicators based on the extant literature to evaluate PCSPs, and then collects the data about each index by investigation and the performance test, finally proposes a model to rank PCSPs, which applies analytic hierarchy process (AHP) to determine the indexed weights and the technique for order preference by similarity to ideal solution-grey relational analysis calculate evaluation score of each PCSP.

Among them, Qihoo 360-cloud gets the highest evaluation score contributed by large space, file editing and fast transmission speed. The rest are Kingsoft cloud, Baidu cloud, Huawei DBank and Tencent cloud in order. These storage products are all want of the addition or improvement of the online editing service similar as Google Docs.

AHP method is subjective, some of the data is incomplete, and some accidental error and systematic error exist in the actual testing process.

The findings can assist users in selecting more suitable products and offer cloud storage providers (CSPs) a general direction of improving their product performance.

Contributing to improve the overall level of the cloud storage services in China.

The study perfects the evaluation index system of the PCSP and fills the research gap in studying PCSPs in China, and expands the application field of the multiple criteria decision-making problems. This evaluation process and results have implied that CSPs in China should provide good services of large capacity, cooperation and security with the good internet environment of economical, high and stable speed by institutions and internet access providers.

The aim of this research is to secure the sensitive outsourced data with minimum encryption within the cloud provider. Unfaithful solutions for providing privacy and security along with performance issues by encryption usage of outsourced data are the main motivation points of this research.

This paper presents a method for secure and confidential storage of data in the cloud environment based on fragmentation. The method supports minimal encryption to minimize the computations overhead due to encryption. The proposed method uses normalization of relational databases, tables are categorized based on user requirements relating to performance, availability and serviceability, and exported to XML as fragments. After defining the fragments and assigning the appropriate confidentiality levels, the lowest number of Cloud Service Providers (CSPs) is used required to store all fragments that must remain unlinkable in separate locations.

Particularly in the cloud databases are sometimes de‐normalised (their normal form is decreased to lower level) to increase the performance.

The paper proposes a methodology to minimize the need for encryption and instead focus on making data entities unlinkable so that even in the case of a security breach for one set of data, the privacy impact on the whole is limited. The paper would be relevant to those people whose main concern is to preserve data privacy in distributed systems.

The purpose of this paper is to critically examine the vulnerabilities of the cloud platform affecting businesses trading on the internet. It aims to examine the appropriateness of the cloud computing, its benefits to the industry and helps to identify security concerns for businesses that plan to deploy one of the cloud platforms. It helps to identify areas where businesses should focus before choosing an appropriate Cloud Service Provider (CSP).

This paper presents the findings of an original research survey (200 IT professionals working both in the public and private sectors) undertaken to examine their privacy, and data security concerns associated with the cloud platform. Views of those who have yet to deploy cloud were analysed to detect the patterns of common security issues. Cyber fraud and trust concerns of the organisations are addressed and deployment of the secured cloud environment is outlined.

The survey analysis highlighted that the top concerns for organisations on cloud were security (93.8 per cent), governance (61.1 per cent) and a lack of control over service availability (56.6 per cent). The survey highlighted that the majority of IT professionals were not aware that some CSPs currently control the decryption keys that enable them to decrypt their client's data. This should be considered as a major security concern and it is one of the factors that should be looked into while vetting the service level agreement (SLA). Data loss and leakage (73.5 per cent) were voted as the top threat to cloud computing by respondents; this was followed by account, service and traffic hijacking (60.8 per cent). The paper examines various types of cloud threats companies have encountered.

The vast majority of the data are drawn from IT professionals with businesses mainly in the UK and the USA.

The paper advocates a proactive and holistic cloud‐cyber security prevention typology to prevent e‐crime, with guidance of what features to look for when choosing an appropriate cloud service provider.

This is the first analysis done that includes IT auditors, physical security personnel as well as IT professionals. The paper is of value to companies considering adoption or implementation of a cloud platform. It helps to assess the cloud by evaluating a detailed comparison of benefits and risk associated with the platform.

Until now, a lot of research has been done and applied to provide security and original data from one user to another, such as third-party auditing and several schemes for securing the data, such as the generation of the key with the help of encryption algorithms like Rivest–Shamir–Adleman and others. Here are some of the related works that have been done previously. Remote damage control resuscitation (RDCR) scheme by Yan et al. (2017) is proposed based on the minimum bandwidth. By enabling the third party to perform the verification of public integrity. Although it supports the repair management for the corrupt data and tries to recover the original data, in practicality it fails to do so, and thus it takes more computation and communication cost than our proposed system. In a paper by Chen et al. (2015), using broadcast encryption, an idea for cloud storage data sharing has been developed. This technique aims to accomplish both broadcast data and dynamic sharing, allowing users to join and leave a group without affecting the electronic press kit (EPK). In this case, the theoretical notion was true and new, but the system’s practicality and efficiency were not acceptable, and the system’s security was also jeopardised because it proposed adding a member without altering any keys. In this research, an identity-based encryption strategy for data sharing was investigated, as well as key management and metadata techniques to improve model security (Jiang and Guo, 2017). The forward and reverse ciphertext security is supplied here. However, it is more difficult to put into practice, and one of its limitations is that it can only be used for very large amounts of cloud storage. Here, it extends support for dynamic data modification by batch auditing. The important feature of the secure and efficient privacy preserving provable data possession in cloud storage scheme was to support every important feature which includes data dynamics, privacy preservation, batch auditing and blockers verification for an untrusted and an outsourced storage model (Pathare and Chouragadec, 2017). A homomorphic signature mechanism was devised to prevent the usage of the public key certificate, which was based on the new id. This signature system was shown to be resistant to the id attack on the random oracle model and the assault of forged message (Nayak and Tripathy, 2018; Lin et al., 2017). When storing data in a public cloud, one issue is that the data owner must give an enormous number of keys to the users in order for them to access the files. At this place, the knowledge assisted software engineering (KASE) plan was publicly unveiled for the first time. While sharing a huge number of documents, the data owner simply has to supply the specific key to the user, and the user only needs to provide the single trapdoor. Although the concept is innovative, the KASE technique does not apply to the increasingly common manufactured cloud. Cui et al. (2016) claim that as the amount of data grows, distribution management system (DMS) will be unable to handle it. As a result, various proven data possession (PDP) schemes have been developed, and practically all data lacks security. So, here in these certificates, PDP was introduced, which was based on bilinear pairing. Because of its feature of being robust as well as efficient, this is mostly applicable in DMS. The main purpose of this research is to design and implement a secure cloud infrastructure for sharing group data. This research provides an efficient and secure protocol for multiple user data in the cloud, allowing many users to easily share data.

The methodology and contribution of this paper is given as follows. The major goal of this study is to design and implement a secure cloud infrastructure for sharing group data. This study provides an efficient and secure protocol for multiple user data in cloud, allowing several users to share data without difficulty. The primary purpose of this research is to design and implement a secure cloud infrastructure for sharing group data. This research develops an efficient and secure protocol for multiple user data in the cloud, allowing numerous users to exchange data without difficulty. Selection scheme design (SSD) comprises two algorithms; first algorithm is designed for limited users and algorithm 2 is redesigned for the multiple users. Further, the authors design SSD-security protocol which comprises a three-phase model, namely, Phase 1, Phase 2 and Phase 3. Phase 1 generates the parameters and distributes the private key, the second phase generates the general key for all the users that are available and third phase is designed to prevent the dishonest user to entertain in data sharing.

Data sharing in cloud computing provides unlimited computational resources and storage to enterprise and individuals; moreover, cloud computing leads to several privacy and security concerns such as fault tolerance, reliability, confidentiality and data integrity. Furthermore, the key consensus mechanism is fundamental cryptographic primitive for secure communication; moreover, motivated by this phenomenon, the authors developed SSDmechanismwhich embraces the multiple users in the data-sharing model.

Files shared in the cloud should be encrypted for security purpose; later these files are decrypted for the users to access the file. Furthermore, the key consensus process is a crucial cryptographic primitive for secure communication; additionally, the authors devised the SSD mechanism, which incorporates numerous users in the data-sharing model, as a result of this phenomena. For evaluation of the SSD method, the authors have considered the ideal environment of the system, that is, the authors have used java as a programming language and eclipse as the integrated drive electronics tool for the proposed model evaluation. Hardware configuration of the model is such that it is packed with 4 GB RAM and i7 processor, the authors have used the PBC library for the pairing operations (PBC Library, 2022). Furthermore, in the following section of this paper, the number of users is varied to compare with the existing methodology RDIC (Li et al., 2020). For the purposes of the SSD-security protocol, a prime number is chosen as the number of users in this work.

This paper aims to examine the dynamism of causal relationships among cloud computing (CC) adoption factors in the Indian context, considering the perspectives of both the cloud adopter and cloud provider.

The case-study method has been used to understand the dynamics among the factors. Using data from specific cases in India, causal loop diagrams (CLDs) have been developed. System dynamic modeling (SDM) and simulation are used to study the relationships and their effect on the adoption rate.

The results revealed that adoption of CC depends on various factors such as persuasion (time-saving, cost-saving and word of mouth) and constraint factors (security and financial loss). However, it is seen that the adoption rate is very sensitive to changes in adoption per contact and word of mouth. Further, the adopter firm has a quicker time to market, which gives an added advantage to the firm. Also, with CC services, a firm can fulfill its projects or clients' requirements with little to no upfront investment in information technology (IT) services.

Lack of security, standardization and undefined service-level agreements are a few pressing issues that make it difficult for firms to evaluate the performance and reliability of services. Hence, immediate attention is needed to make transparent policies on CC and its services, thereby building trust.

This is the first and only work that has tried to explore and empirically test the dynamics of critical factors while making an adoption decision, considering both the adopter and provider perspectives. This study shows the journey of a firm, starting from being a prospective adopter to an adopter and continuous user. The work also empirically tested how adopters of technology benefit from the technology.

As the storage and processing requirement of digital information is increasing on the cloud, it is very difficult for the single cloud provider (CP) to meet the resource requirement. Multiple providers form a federation for the execution of users’ requests. For the federated cloud, this paper aims to address the issue distribution of users’ request for resources and revenue among the providers by offering fair and stable distribution models for the federated cloud.

This paper uses cooperative game (CG)-theoretical models, i.e. Shapley–Shubik power index (SSPI) and Banzhaf power index (BPI) for distribution. Performance is analysed using variance and monotonicity using a case study.

Numerical analysis is done using two scenarios. Monotonicity is evaluated. Results show that SSPI performs better as compared to BPI in terms of fairness accuracy and the framework provide the fair distribution of revenue among providers in the federated cloud.

The proposed framework works efficiently under the specific defined conditions.

Paper provides the fair distribution. It assist the centralised cloud exchange in managing the users’ request in such a way every CPs, in the federated cloud will get an equal chance of serving the users’ request. The framework also provides the stable federation. Proposed work provides less rejection rate of users’ request. Finally, it assists the providers in increasing their profits in the federation.

This paper presents a CG theoretic-based framework for the distribution of resources required and revenue. The framework analysed the performance of distribution models by considering the variance and monotonicity for multiple users’ requests.

Cloud computing (CC) services have given a tremendous boost to the creation of efficient and effective solutions. With developing countries at a slow pace of adoption, this research aims to identify factors and their interrelationships influencing the adoption of CC in a developing country context. The developing countries are enjoying numerous benefits from CC services; however, its low adoption is still a question in developing economies; hence, the authors have selected the context of information and communication technology (ICT) firms in India.

The qualitative research method is used where experts from thirteen ICT firms in India are interviewed.

Sixteen factors, twenty-eight subfactors, and 25 interrelationships are revealed through content analysis. Further, causal loop diagrams are proposed to display the behavior of cause and effect of these factors from a system's perspective. This will help to understand the relationships among the factors in order to enhance the speed of CC adoption. Possible financial loss and resistance to change are found as the key barriers to adoption. The proposed interrelationships can guide both policymakers and service providers for designing effective CC policies.

This is the first scholarly work that identifies interrelationships among factors and subfactors, thereby providing a holistic picture to decision-makers while making a choice on whether to adopt cloud services or continue with on premise data centers and servers.

Cloud computing is a relatively new phenomena. It has rarely been examined in the context of the small to medium-sized enterprises (SMEs). The purpose of this paper is to examine the drivers and barriers to cloud computing adoption by SMEs in Ireland.

This study adopted an exploratory approach. A quantitative approach was adopted in the data collection phase. An online self-completion questionnaire was distributed by e-mail to 1,500 SMEs in Ireland. A response rate of 6 per cent was achieved generating 95 usable responses.

Findings from this study indicate that Irish SMEs are adopting cloud technology. The key driver identified is the resultant cost benefits for the firm. However, concern over continuous availability of the service is identified by the SME as a key challenge and is hindering widespread adoption of cloud technology.

This study whilst exploratory in nature, has laid the foundation for further research in the area of cloud computing adoption. This research should enable further studies to replicate this process with the possibility of extending the study to include other countries, on a larger scale and with a particular focus on the knowledge intensive business services sector. This study would benefit from adding a qualitative perspective to the research topic to add depth and enhance the “richness” of the data collected during the process.

This study concludes that policy makers and cloud providers need to provide assurances to SMEs over issues of continuous availability of the cloud service through increased and on-going investment in a high-speed, broadband infrastructure and through ensuring issues pertaining to standardization and compliance are resolved.

This exploratory research has illuminated this area through examining the drivers and barriers to cloud adoption by SMEs. In the Irish context, the benefits of engaging in such activity can reap many benefits. Of particular importance to a peripheral economy such as Ireland is the value of adopting cloud computing which is central to offering competitive advantage and controlling costs.

Nowadays, cloud platforms are used in many fields, including e-commerce, web applications, data storage, healthcare, gaming, mobile social networks, etc. However, security and privacy are still two significant concerns in this area. The target of this paper is to present a system for trust management in industrial cloud computing using the multi-criteria decision making (MCDM) approach. MCDM techniques have been developed to accommodate a wide range of applications. As a result, hundreds of approaches have been generated with even minor variations on current approaches spawning new study fields.

Cloud computing provides a fully scalable, accessible and flexible computing platform for various applications. Due to the multiple applications that cloud computing has found in numerous life features, users and providers have considered providing security in cloud communications. Due to its distributive nature, dynamic space and lack of transparency in performing cloud computing, it faces many challenges in providing security. For security improvement, trust management can play a very influential role. This paper proposes a generic analytical methodology that uses a series of assessment criteria to evaluate current trust management testing prototypes in industrial cloud computing and related fields. The authors utilize a MCDM approach in the present article. Due to the multi-dimensionality of the sustainability objective and the complexities of socio-economic and biophysical processes, MCDM approaches have become progressively common in decision-making for sustainable energy.

The results of comparing and evaluating the performance of this model show its ability to manage trust and the ability to adapt to changes in the behavior of service providers quickly. Using a simulation, all results are confirmed. The results of simulations and evaluation of the present paper indicate that the proposed model provides a more accurate evaluation of the credibility of cloud service providers than other models.

The number of cloud services and customers is vast and extremely competitive in cloud environments, where novel cloud services and customers can join at any time, while others can withdraw whenever they want. Because of cloud services' highly dynamic and dispersed design, trust management mechanisms must be highly flexible to obtain feedback and update trust outcomes as quickly as possible. The model presented in this article tries to improve users' trust in the cloud industry.

Using a method (MCDM) to find the best trust management solution based on user experience in industrial cloud computing is the novelty of this paper.

To effectively develop privacy policies and practices for cloud computing, organizations need to define a set of guiding privacy objectives that can be applied across their organization. It is argued that it is important to understand individuals’ privacy values with respect to cloud computing to define cloud privacy objectives.

For the purpose of this study, the authors adopted Keeney’s (1994) value-focused thinking approach to identify privacy objectives with respect to cloud computing.

The results of this study identified the following six fundamental cloud privacy objectives: to increase trust with cloud provider, to maximize identity management controls, to maximize responsibility of information stewardship, to maximize individual’s understanding of cloud service functionality, to maximize protection of rights to privacy, and to maintain the integrity of data.

One limitation is generalizability of the cloud privacy objectives, and the second is research bias. As this study focused on cloud privacy, the authors felt that the research participants’ increased knowledge of technology usage, including that of cloud technology, was a benefit that outweighed risks associated with not having a random selection of the general population. The newness and unique qualities of privacy issues in cloud computing are better fitted to a qualitative study where issues can emerge naturally through a holistic approach opposed to trying to force fit an existing set of variables or constructs into the context of privacy and cloud computing.

The findings of this research study can be used to assist management in the process of formulating a cloud privacy policy, develop cloud privacy evaluation criteria as well as assist auditors in developing their privacy audit work plans.

Currently, there is little to no guidance in the literature or in practice as to what organizations need to do to ensure they protect their stakeholders privacy in a cloud computing environment. This study works at closing this knowledge gap by identifying cloud privacy objectives.