Improving Security on Cloud Based Deduplication System

According to Cisco Global Cloud Index, cloud storage users will store 1.6 Gigabytes data per month by 2019, compared to 992 megabytes data per month in 2014. With this trend, it has been shown that more and more data will reside in cloud storage and it is expected to grow further. As cloud storage is becoming an option for users for keeping their data online, it comes with security concerns for protecting data from threats. This thesis addresses the need to investigate the security factors that will enable efficient security protection for data in cloud storage and the relationships that exist between the different security factors. Consequently, this research has developed a conceptual framework that supports security in cloud storage. The main contribution of this research is the development of a Cloud Storage Security Framework (CSSF) to support an integrative approach to understanding and evaluating security in cloud storage. The framework enables understanding of the makeup of security in cloud storage and measures the understanding of security in cloud storage. Drawing upon established theories and prior research findings, the framework indicates that security in cloud storage can be determined by nine factors: (1) security policies implementation in cloud storage, security measure that relates to (2) protecting the data accessed in cloud storage; (3) modifications of data stored; (4) accessibility of data stored in cloud storage; (5) non-repudiation to the data stored; (6) authenticity of the original data; (7) reliability of the cloud storage services; (8) accountability of service provision; and (9) auditability of the data accessed and stored in cloud storage. An example of CSSF application has been demonstrated through the development of a measuring instrument called Security Rating Score (SecRaS) and through a series of experiments, SecRaS has been validated and used in a research scenario. The instrument consists of several items generated using goal-question-metric approach. These potential items were evaluated by a series of experiments; the security experts assessed using content validity ratio while the security practitioners took part in the validation study. The validation study completed two experiments that look into the correlation analyses and internal reliability. SecRaS instrument was later applied in a research scenario; the validated instrument was distributed and a number of 218 usable responses were received. Using structural equation modelling, the data has revealed a good fit of the measurement analyses and structural model. The key findings were as follow: the relationships between factors were found to have both direct and indirect effects in the result. While establishing the relationship(s) among the factors, the structural model proposes three types of causal relationships in terms of how the security implementation in cloud storage could be affected by the security factors. This thesis presents a detailed discussion of the CSSF development, confirmation, and application in a research scenario. For security managers, CSSF offers a new paradigm on how stakeholders can make cloud storage security implementation successful in some depth. For security practitioners, the CSSF enables deconstruction of the concept of security in cloud storage into smaller, conceptually distinct and manageable factors to guide the design of security in cloud storage. For researchers, the CSSF provides a common framework in which to conceptualise their research and make it easier to see how the security factors fit into the larger picture.

Using cloud data clients may transfer data from their computer systems to cloud servers. Hence, user will not have any burden of maintenance and also he gets high quality data storage services. Many security issues are concerned with cloud storage. Cloud service providers or storage servers are not completely trustworthy. The user is concerned about the information stored on cloud are in place or not turns. This paper is based on homomorphic hash algorithm. Further this supports dynamic operations such as insert, update, delete and modify at block level, for data dynamics Merkle Hash Tree is used which helps to find the location of each dynamic operation. Third party auditor checks the user's data for correctness and gives the accuracy of the data that is stored in cloud server. The communication and computation overhead are reduced. Deduplication technique is used to check whether the file that user need to store in cloud storage is already exist at cloud server or not. This framework is effective and secure against replace attack launch by malicious server.

Modern technological advances have given rise to the popularity and success of cloud in organizations and industries because it provides data storage facility and computing services at minimal cost. Data security is one of the important requirements for outsourced data in a cloud storage environment. It also brings new security vulnerabilities for assuring the data confidentiality, data integrity and data access control. Data security of a cloud system depends heavily on the cloud service provider, data owner and cloud users. So, there needs to be some methodology to monitor security vulnerabilities and providing data security in cloud environment. Now a day’s providing data security in cloud storage is one of the most critical tasks. For the past few years many works have been done to assure data security but they are failed in providing data security such as information leakage, secret-key management, cloud-user authentication, breach of data confidentiality, because of collusion attack and lots of computational activities (because of large number of secret keys).In this paper, we used threshold cryptography technique for providing data security in cloud storage system. Proposed approach addresses the data security issues in cloud system more efficiently. In this Threshold cryptography technique data owner create users in groups based on place or location, project, and department, data owner allocates single secret key to each group of users for decryption of data and every users in the group shares parts or pieces of the secret key. Proposed methodology also uses data access control list to control the data access. Proposed approach provides data security more efficiently, it also increases the performance of the system and also it minimizes the number of secret keys.

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.

With the rapid development of cloud computing, an increasing number of data owners are willing to employ cloud storage service. In cloud storage, the resource-constraint data owners can outsource their large-scale data to the remote cloud server, by which they can greatly reduce local storage overhead and computation cost. Despite plenty of attractive advantages, cloud storage inevitably suffers from some new security challenges due to the separation of outsourced data ownership and its management, such as secure data insertion and deletion. The cloud server may maliciously reserve some data copies and return a wrong deletion result to cheat the data owner. Moreover, it is very difficult for the data owner to securely insert some new data blocks into the outsourced data set. To solve the above two problems, we adopt the primitive of Merkle sum hash tree to design a novel publicly verifiable cloud data deletion scheme, which can also simultaneously achieve provable data storage and dynamic data insertion. Moreover, an interesting property of our proposed scheme is that it can satisfy private and public verifiability without requiring any trusted third party. Furthermore, we formally prove that our proposed scheme not only can achieve the desired security properties, but also can realize the high efficiency and practicality.

This paper explores the benefits of cloud storage, a fundamental component of cloud computing, which provides users with nearly limitless storage capabilities. Users can substantially decrease their local storage requirements by allowing data to be outsourced to cloud servers. However, the paper also addresses security privacy concerns linked to cloud storage, which stem from data ownership and management division, resulting in users losing direct control over their outsourced data. The authors concentrate on the challenge of verifiable outsourced data deletion, a significant issue that has not been adequately addressed in either industry or academic circles. They present an effective fine-grained outsourced data deletion scheme utilizing the invertible Bloom filter. This solution facilitates both public and private verification of the storage and deletion processes. Suppose the cloud server fails to manage or remove the data accurately and creates the associated evidence. In that case, users can detect any malicious actions by the cloud server with a high likelihood. Additionally, the authors note that within their proposed scheme, the computational complexity of both data deletion and verification of deletion results remains unaffected by the quantity of outsourced data blocks. This property makes the scheme appropriate for extensive data deletion scenarios. Ultimately, the paper includes a thorough security evaluation and performance assessment, validating the security and practicality of the proposed scheme. This comprehensive method for tackling the issue of verifiable outsourced data deletion in cloud storage represents a notable contribution to the field

Cloud storage enables users to remotely store their data and benefit of the demand high quality cloud applications without the difficulty of local hardware and software management. Though the benefits are clear, such a service is also reliable to the users’ physical possession of their outsourced data, which inevitably poses new security risks towards the recovery of the data in cloud. In order to address this new problem and further achieve a secure and useful cloud storage service, we propose in this study a flexible distributed storage integrity mechanism, utilizing the homomorphic token and distributed data. The proposed design allows users to check the cloud storage with very lightweight communication and computation cost. The auditing result not only ensures strong cloud storage correctness guarantee, efficiency, but also simultaneously to access data error localization, i.e., the identification of misbehaving server. Considering the cloud data are dynamic in nature, the proposed design future supports secure and efficient dynamic operations on outsourced data, including block modification, update, deletion and append. The proposed scheme is highly efficient and secure against Byzantine failure, malicious data modification attack and even server colluding attacks.

Provable data deletion from efficient data integrity auditing and insertion in cloud storage

Provable data transfer from provable data possession and deletion in cloud storage

Attribute-based encryption has been widely employed to achieve data confidentiality and fine-grained access control in cloud storage. To enable users to identify accessible data in numerous dataset, clear attributes should be appended to the ciphertext, which results in the exposure of attribute privacy. In this paper, we propose an efficient attribute-based access control with authorized search scheme (EACAS) in cloud storage by extending the anonymous key-policy attribute-based encryption (AKP-ABE) to support fine-grained data retrieval with attribute privacy preservation. Specifically, by integrating the key delegation technique into AKP-ABE, EACAS enables data users to customize search policies based on their access policies, and generate the corresponding trapdoor using the secret key granted by the data owner to retrieve their interesting data. In addition, a virtual attribute with no semantic meaning is utilized in data encryption and trapdoor generation to empower the cloud to perform an attribute-based search on the outsourced ciphertext without knowing the underlying attributes or outsourced data. The data owners can achieve fine-grained access control on their outsourced data, and the data users are flexible to search their interesting data based on protected attributes through customizing the search policies. Finally, we demonstrate that EACAS is more efficient than existing solutions on computation and storage overheads.

Data de-duplication refers to providing cloud providers with a way to manage the uncontrollable data and the challenges of cloud storage. The success of IOT and social media led us to face big data challenges. Big data is interesting but also becomes a critical challenge for cloud service providers. Data storage and management become also the topic of discussion where big data generate business opportunities as well as come with big issues for the cloud providers. In this paper, we discussed the issues of redundant data and techniques to prevent data redundancy on the cloud. A third-party auditor checks the user’s data for correctness and gives the accuracy of the data that is stored in a cloud server. The communication and computation overheads were reduced. The deduplication technique is used to check whether the file that users need to store in cloud storage already exists on the cloud server.

Cloud computing has empowered the individual user by providing seemingly unlimited storage space and availability and accessibility of data anytime and anywhere. Cloud service providers are able to maximize data storage space by incorporating data deduplication into cloud storage. Although data deduplication removes data redundancy and data replication, it also introduces major data privacy and security issues for the user. In this paper, a new privacy-preserving framework that addresses this issue is proposed. Our framework uses an efficient deduplication algorithm to divide a given file into smaller units. These units are then encrypted by the user using the combination of a secure hash function and a block encryption algorithm. An index tree of hash values of these units is also generated and encrypted using an asymmetric search encryption scheme by the user. This index tree will enable the cloud service provider to search through the index and return the requested units. We will show that our proposed framework will allow cloud service and storage providers to employ data deduplication techniques without giving them access to either the users' plaintexts or the users' decryption keys.

<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>

This article describes how in order to reduce the amount of data, deduplication technology is introduced in the cloud storage. Adopting this technology, the duplicated data can be eliminated, users can conserve the storage requirement. However, deduplication technology also increases the data unavailability. To solve this problem, the authors propose a method to improve data availability in the deduplication storage system. It is based on the data chunk reference count and access frequency, and increases redundant information for the data chunks, to ensure data availability and minimize storage overhead. Extensive experiments are conducted to evaluate effectiveness of the improved method. WFD, CDC, and sliding block deduplication technology are used for comparison. The experimental results show that the proposed method can achieve higher data availability than the conventional method and increase little storage overhead.

Nowadays, more and more corporate and private users outsource their data to cloud service provider. It is provide lots of services to the users. Due to the large amount of data stored by multiple users on cloud one critical problem must be faced by users. In this large amount of data there are so many copies of repeated data. Data duplication is compress repeated data. We can use this technique To make data management scalable and mitigate the increased amount of data. In the proposed system, we are going to used two cloud server, public cloud server and private cloud server. Public cloud server store data (hash, encrypted data) and compare hash which is generated by private cloud. After comparison hash is stored in the data base by private cloud. This proposed system used to mitigate the problem of data duplication. Based on this we can improve storage utilization and efficiency of cloud storage.