Light-Weight Accountable Privacy Preserving Protocol in Cloud Computing Based on a Third-Party Auditor

Cloud computing is emerging as the next disruptive utility paradigm [1]. It provides extensive storage capabilities and an environment for application developers through virtual machines. It is also the home of software and databases that are accessible, on-demand. Cloud computing has drastically transformed the way organizations, and individual consumers access and interact with Information Technology. Despite significant advancements in this technology, concerns about security are holding back businesses from fully adopting this promising information technology trend. Third-party auditors (TPAs) are becoming more common in cloud computing implementations. Hence, involving auditors comes with its issues such as trust and processing overhead. To achieve productive auditing, we need to (1) accomplish efficient auditing without requesting the data location or introducing processing overhead to the cloud client; (2) avoid introducing new security vulnerabilities during the auditing process. There are various security models for safeguarding the CCs (Cloud Client) data in the cloud. The TPA systematically examines the evidence of compliance with established security criteria in the connection between the CC and the Cloud Service Provider (CSP). The CSP provides the clients with cloud storage, access to a database coupled with services. Many security models have been elaborated to make the TPA more reliable so that the clients can trust the third-party auditor with their data. Our study shows that involving a TPA might come with its shortcomings, such as trust concerns, extra overhead, security, and data manipulation breaches; as well as additional processing, which leads to the conclusion that a lightweight and secure protocol is paramount to the solution. As defined in [2] privacy-preserving is making sure that the three cloud stakeholders are not involved in any malicious activities coming from insiders at the CSP level, making sure to remediate to TPA vulnerabilities and that the CC is not deceitfully affecting other clients. In our survey phase, we have put into perspective the privacy-preserving solutions as they fit the lightweight requirements in terms of processing and communication costs, ending up by choosing the most prominent ones to compare with them our simulation results. In this dissertation, we introduce a novel method that can detect a dishonest TPA: The Light-weight Accountable Privacy-Preserving (LAPP) Protocol. The lightweight characteristic has been proven simulations as the minor impact of our protocol in terms of processing and communication costs. This protocol determines the malicious behavior of the TPA. To validate our proposed protocol’s effectiveness, we have conducted simulation experiments by using the GreenCloud simulator. Based on our simulation results, we confirm that our proposed model provides better outcomes as compared to the other known contending methods

Secure Dynamic Groups Auditing Service with Group Signature for Cloud Storage

Cloud storage has become a commonplace of storing and sharing data across multiple users. It is a challenge to preserve confidentiality and maintain identity privacy while sharing data within multiple dynamic groups, due to frequent change in the membership. Also, maintaining data integrity is an issue as data is stored and audited by untrusted cloud service provider (CSP). In this paper, we propose, third party auditor (TPA) auditing scheme to maintain data integrity and enabling TPA to perform audits for multiple users efficiently and simultaneously. By exploiting group signature scheme any member can anonymously share data within the group. The efficiency and the computation cost of the proposed system are independent with the number of users revoked and the data stored on the cloud. DOI: 10.17762/ijritcc2321-8169.150612

Group Based Secure Sharing of Cloud Data with Provable Data Freshness

With cloud computing technology it is realized that data can be outsource and such data can also be shared among users of cloud. However, the data outsourced to cloud might be subjected to integrity problems due to the problems in the underlying hardware or software errors. Human errors also may contribute to the integrity problems. Many techniques came into existence in order to ensure data integrity. Most of the techniques have some sort of auditing. Public auditing schemes meant for data integrity of shared data might disclose confidential information. To overcome this problem, recently, Wang et al. proposed a novel approach that supports public auditing and also do not disclose confidential information. They exploited ring signatures that are used to compute verification metadata on the fly in order to audit the correctness of shared data. The public verifiers do not know the identity of the signer. It does mean that the verifier can verify data without knowing the identity of the signer. However, this scheme does not consider the freshness of data which is very important in cloud services. Obtaining latest copy of data is very important to avoid stale data access in cloud. Towards this end, in this paper, we proposed an algorithm for ensuring freshness of the data while retrieving the outsourced data in multi-user environment. Our empirical results revealed that the proposed algorithm is efficient. DOI: 10.17762/ijritcc2321-8169.15065

An extensive research survey on data integrity and deduplication towards privacy in cloud storage

Owing to the highly distributed nature of the cloud storage system, it is one of the challenging tasks to incorporate a higher degree of security towards the vulnerable data. Apart from various security concerns, data privacy is still one of the unsolved problems in this regards. The prime reason is that existing approaches of data privacy doesn't offer data integrity and secure data deduplication process at the same time, which is highly essential to ensure a higher degree of resistance against all form of dynamic threats over cloud and internet systems. Therefore, data integrity, as well as data deduplication is such associated phenomena which influence data privacy. Therefore, this manuscript discusses the explicit research contribution toward data integrity, data privacy, and data deduplication. The manuscript also contributes towards highlighting the potential open research issues followed by a discussion of the possible future direction of work towards addressing the existing problems

Public cloud data auditing with practical key update and zero knowledge privacy

Data integrity is extremely important for cloud based storage services, where cloud users no longer have physical possession of their outsourced files. A number of data auditing mechanisms have been proposed to solve this problem. However, how to update a cloud user\u27s private auditing key (as well as the authenticators those keys are associated with) without the user\u27s re-possession of the data remains an open problem. In this paper, we propose a key-updating and authenticator-evolving mechanism with zero-knowledge privacy of the stored files for secure cloud data auditing, which incorporates zero knowledge proof systems, proxy re-signatures and homomorphic linear authenticators. We instantiate our proposal with the state-of-the-art Shacham-Waters auditing scheme. When the cloud user needs to update his key, instead of downloading the entire file and re-generating all the authenticators, the user can just download and update the authenticators. This approach dramatically reduces the communication and computation cost while maintaining the desirable security. We formalize the security model of zero knowledge data privacy for auditing schemes in the key-updating context and prove the soundness and zero-knowledge privacy of the proposed construction. Finally, we analyze the complexity of communication, computation and storage costs of the improved protocol which demonstrates the practicality of the proposal

A Framework for Uncertain Cloud Data Security and Recovery Based on Hybrid Multi-User Medical Decision Learning Patterns

Machine learning has been supporting real-time cloud based medical computing systems. However, most of the computing servers are independent of data security and recovery scheme in multiple virtual machines due to high computing cost and time. Also, this cloud based medical applications require static security parameters for cloud data security. Cloud based medical applications require multiple servers to store medical records or machine learning patterns for decision making. Due to high Uncertain computational memory and time, these cloud systems require an efficient data security framework to provide strong data access control among the multiple users. In this work, a hybrid cloud data security framework is developed to improve the data security on the large machine learning patterns in real-time cloud computing environment. This work is implemented in two phases’ i.e. data replication phase and multi-user data access security phase. Initially, machine decision patterns are replicated among the multiple servers for Uncertain data recovering phase. In the multi-access cloud data security framework, a hybrid multi-access key based data encryption and decryption model is implemented on the large machine learning medical patterns for data recovery and security process. Experimental results proved that the present two-phase data recovering, and security framework has better computational efficiency than the conventional approaches on large medical decision patterns

From security to assurance in the cloud: a survey

The cloud computing paradigm has become a mainstream solution for the deployment of business processes and applications. In the public cloud vision, infrastructure, platform, and software services are provisioned to tenants (i.e., customers and service providers) on a pay-as-you-go basis. Cloud tenants can use cloud resources at lower prices, and higher performance and flexibility, than traditional on-premises resources, without having to care about infrastructure management. Still, cloud tenants remain concerned with the cloud's level of service and the nonfunctional properties their applications can count on. In the last few years, the research community has been focusing on the nonfunctional aspects of the cloud paradigm, among which cloud security stands out. Several approaches to security have been described and summarized in general surveys on cloud security techniques. The survey in this article focuses on the interface between cloud security and cloud security assurance. First, we provide an overview of the state of the art on cloud security. Then, we introduce the notion of cloud security assurance and analyze its growing impact on cloud security approaches. Finally, we present some recommendations for the development of next-generation cloud security and assurance solutions

Data Auditing and Security in Cloud Computing: Issues, Challenges and Future Directions

Cloud computing is one of the significant development that utilizes progressive computational power and upgrades data distribution and data storing facilities. With cloud information services, it is essential for information to be saved in the cloud and also distributed across numerous customers. Cloud information repository is involved with issues of information integrity, data security and information access by unapproved users. Hence, an autonomous reviewing and auditing facility is necessary to guarantee that the information is effectively accommodated and used in the cloud. In this paper, a comprehensive survey on the state-of-art techniques in data auditing and security are discussed. Challenging problems in information repository auditing and security are presented. Finally, directions for future research in data auditing and security have been discussed