scholarly journals Review on dynamic group data sharing in cloud environment

2018 ◽  
Vol 7 (2) ◽  
pp. 646
Author(s):  
Sathishkumar Easwaramoorthy ◽  
Anilkumar Chunduru ◽  
Usha Moorthy ◽  
Sravankumar B

Information sharing or exchange of data within entities plays a significant role in cloud storage. In cloud computing, a robust and practical methodology is developed which can be utilized by cloud users for sharing information among multiple group members in the cloud with lowered maintenance and management costs. Furthermore, a service provider in the cloud does not share data with anyone other than the Trusted Third Party (TTP) sources due to the semi-trusted characteristics of the cloud. In this way, there is no global security mechanism for dynamic group data sharing over the cloud. Subsequently, the Cloud Service Providers (CSPs) can convey different services to cloud users through powerful data centres. Hence, data is secured through the validation of users in the cloud. Meanwhile, CSPs should offer outsourced security assurance for data file sharing. Assuring privacy in data sharing is still a critical issue due to continuous change in cloud users, particularly, for unauthenticated or third party users because of the risk of collusion attacks. However, security concerns turn into a major restraint as outsourcing storage data is perhaps a delicate concern for cloud providers. Additionally, sharing information in a multi-proprietary approach while protecting information and individual security to the data from unauthorized or third party users is still a challenging task as there is a frequent change in cloud members. In this regard, previous studies are reviewed and discussed which are related to dynamic group data sharing using cloud computing.

Author(s):  
Prerna Agarwal Et. al.

A comprehensive and functional approach is built in cloud computing, which can be used by cloud users to exchange information. Cloud service providers (CSPs) can transfer through server services through powerful data centres to cloud users. Data is protected through authentication of cloud users and CSPs can have outsourced data file sharing security assurance. The continuing change in cloud users, especially unauthenticated users or third parties poses a critical problem in ensuring privacy in data sharing. The multifunctional exchange of information while protecting information and personal protection from unauthorized or other third-party users remains a daunting challenge


2019 ◽  
Vol 8 (2) ◽  
pp. 6408-6412

Cloud computing is a technology where it provides software, platform, infrastructure, security and everything as a service. But this technology faces many security issues because all the data or information are stored in the hands of the third party. The cloud users unable to know where the data are store in the cloud environment and also it is very difficult to analyze the trustworthiness of the cloud service providers. In this technology providing security is a very big challenging task. This challenge was overcome by developing different cloud security algorithms using cryptographic techniques. Recently many researchers identified that if the cryptographic algorithms are combined in a hybrid manner it will increase the security in the cloud environment. Even though, many research works are still carried out to improve security in the cloud computing environment. In this research article, a new step was taken to develop a new cloud security algorithm


Author(s):  
Jin Han ◽  
Jing Zhan ◽  
Xiaoqing Xia ◽  
Xue Fan

Background: Currently, Cloud Service Provider (CSP) or third party usually proposes principles and methods for cloud security risk evaluation, while cloud users have no choice but accept them. However, since cloud users and cloud service providers have conflicts of interests, cloud users may not trust the results of security evaluation performed by the CSP. Also, different cloud users may have different security risk preferences, which makes it difficult for third party to consider all users' needs during evaluation. In addition, current security evaluation indexes for cloud are too impractical to test (e.g., indexes like interoperability, transparency, portability are not easy to be evaluated). Methods: To solve the above problems, this paper proposes a practical cloud security risk evaluation method of decision-making based on conflicting roles by using the Analytic Hierarchy Process (AHP) with Aggregation of Individual priorities (AIP). Results: Not only can our method bring forward a new index system based on risk source for cloud security and corresponding practical testing methods, but also can obtain the evaluation result with the risk preferences of conflicting roles, namely CSP and cloud users, which can lay a foundation for improving mutual trusts between the CSP and cloud users. The experiments show that the method can effectively assess the security risk of cloud platforms and in the case where the number of clouds increased by 100% and 200%, the evaluation time using our methodology increased by only by 12% and 30%. Conclusion: Our method can achieve consistent decision based on conflicting roles, high scalability and practicability for cloud security risk evaluation.


2018 ◽  
pp. 54-76
Author(s):  
Tabassum N. Mujawar ◽  
Ashok V. Sutagundar ◽  
Lata L. Ragha

Cloud computing is recently emerging technology, which provides a way to access computing resources over Internet on demand and pay per use basis. Cloud computing is a paradigm that enable access to shared pool of resources efficiently, which are managed by third party cloud service providers. Despite of various advantages of cloud computing security is the biggest threat. This chapter describes various security concerns in cloud computing. The clouds are subject to traditional data confidentiality, integrity, availability and various privacy issues. This chapter comprises various security issues at different levels in environment that includes infrastructure level security, data level and storage security. It also deals with the concept of Identity and Access Control mechanism.


2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Keyang Liu ◽  
Weiming Zhang ◽  
Xiaojuan Dong

With the growth of cloud computing technology, more and more Cloud Service Providers (CSPs) begin to provide cloud computing service to users and ask for users’ permission of using their data to improve the quality of service (QoS). Since these data are stored in the form of plain text, they bring about users’ worry for the risk of privacy leakage. However, the existing watermark embedding and encryption technology is not suitable for protecting the Right to Be Forgotten. Hence, we propose a new Cloud-User protocol as a solution for plain text outsourcing problem. We only allow users and CSPs to embed the ciphertext watermark, which is generated and embedded by Trusted Third Party (TTP), into the ciphertext data for transferring. Then, the receiver decrypts it and obtains the watermarked data in plain text. In the arbitration stage, feature extraction and the identity of user will be used to identify the data. The fixed Hamming distance code can help raise the system’s capability for watermarks as much as possible. Extracted watermark can locate the unauthorized distributor and protect the right of honest CSP. The results of experiments demonstrate the security and validity of our protocol.


The tradition of moving applications, data to be consumed by the applications and the data generated by the applications is increasing and the increase is due to the advantages of cloud computing. The advantages of cloud computing are catered to the application owners, application consumers and at the same time to the cloud datacentre owners or the cloud service providers also. Since IT tasks are vital for business progression, it for the most part incorporates repetitive or reinforcement segments and framework for power supply, data correspondences associations, natural controls and different security gadgets. An extensive data centre is a mechanical scale task utilizing as much power as a community. The primary advantage of pushing the applications on the cloud-based data centres are low infrastructure maintenance with significant cost reduction for the application owners and the high profitability for the data centre cloud service providers. During the application migration to the cloud data centres, the data and few components of the application become exposed to certain users. Also, the applications, which are hosted on the cloud data centres must comply with the certain standards for being accepted by various application consumers. In order to achieve the standard certifications, the applications and the data must be audited by various auditing companies. Few of the cases, the auditors are hired by the data centre owners and few of times, the auditors are engaged by application consumers. Nonetheless, in both situations, the auditors are third party and the risk of exposing business logics in the applications and the data always persists. Nevertheless, the auditor being a third-party user, the data exposure is a high risk. Also, in a data centre environment, it is highly difficult to ensure isolation of the data from different auditors, who may not be have the right to audit the data. Significant number of researches have attempted to provide a generic solution to this problem. However, the solutions are highly criticized by the research community for making generic assumptions during the permission verification process. Henceforth, this work produces a novel machine learning based algorithm to assign or grant audit access permissions to specific auditors in a random situation without other approvals based on the characteristics of the virtual machine, in which the application and the data is deployed, and the auditing user entity. The results of the proposed algorithm are highly satisfactory and demonstrates nearly 99% accuracy on data characteristics analysis, nearly 98% accuracy on user characteristics analysis and 100% accuracy on secure auditor selection process


Author(s):  
R.Santha Maria Rani ◽  
Dr.Lata Ragha

Cloud computing provides elastic computing and storage resource to users. Because of the characteristic the data is not under user’s control, data security in cloud computing is becoming one of the most concerns in using cloud computing resources. To improve data reliability and availability, Public data auditing schemes is used to verify the outsourced data storage without retrieving the whole data. However, users may not fully trust the cloud service providers (CSPs) because sometimes they might be dishonest. Therefore, to maintain the integrity of cloud data, many auditing schemes have been proposed. In this paper, analysis of various existing auditing schemes with their consequences is discussed.  Keywords: — Third Party Auditor (TPA), Cloud Service Provider (CSP), Merkle-Hash Tree (MHT), Provable data Possession (PDP), Dynamic Hash Table (DHT).


Cloud computing or in other words, shared computing is a unique way of sharing resources via the Internet. It combines and extends features of parallel processing, grid computing, and distributed computing. Cloud Computing environments provide a competent way to schedule and process various jobs on remote machines. Rather than relying on local machines, Cloud users access services remotely via high-speed networks. Various users submitting jobs to be processed to Cloud would expect Quality of Service (QoS). So, currently, many researchers are proposing various heuristics that provide QoS to cloud users. The job scheduler is responsible for scheduling various jobs to its best-matched resource to achieve desired QoS. There are Service Level Agreements (SLAs) between Cloud Service Providers (CSPs) and Cloud users, which need to be followed by both the parties. Benefits would be affected in case of not complying with SLAs. In this paper various SLAs like Hard SLA, Best Effort SLA and Soft SLA are proposed. Jobs with required QoS parameters like Reliability, Execution Time and Priority are submitted to the scheduler. QoS of resources is determined by parameters like Reliability, Job Completion Time and the Cost of the resource. Schedulers then assign the Job to the best-matched resource according to specified SLA. Simulation is performed for First Fit and Best Fit heuristic approaches. Performances of both the heuristic approaches are evaluated with performance parameters like Average Resource Utilization (ARU), Success Rate of Jobs (SR) and Total Completion Time (TCT). This research work is useful for various organizations that provide various Cloud services to users who seek different levels of QoS for various applications.


Author(s):  
K. V. Uma Maheswari ◽  
Dr. Dhanaraj Cheelu

Cloud computing is recognized as an alternative to traditional information technology due to its intrinsic resource sharing and low maintenance characteristics. Cloud computing provides an economical and efficient solution for sharing group resource among cloud users. Unfortunately, when sharing the data in a group while preserving data, identity privacy is still a challenging issue due to frequent change in membership. In overcome this problem, a secure data sharing scheme for dynamic groups is proposed so that any user within a group can share the data in a secure manner by leveraging both the group signature and dynamic broadcast encryption techniques. It should enable any cloud user to anonymously share data with others within the group and support efficient member revocation. The storage overhead and encryption computation cost are dependent on the number of revoked users.


Author(s):  
V E Sathishkumar ◽  
Wesam Atef Hatamleh ◽  
Abeer Ali Alnuaim ◽  
Mohamed Abdelhady ◽  
B. Venkatesh ◽  
...  

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