scholarly journals Comparable Encryption Scheme over Encrypted Cloud Data in Internet of Everything

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Qian Meng ◽  
Jianfeng Ma ◽  
Kefei Chen ◽  
Yinbin Miao ◽  
Tengfei Yang
Keyword(s):  
Model Performance ◽  
Data Integrity ◽  
Cloud Service ◽  
Third Party ◽  
Encryption Scheme ◽  
Cloud Data ◽  
Practical Applications ◽  
Internet Of Everything ◽  
Window Method ◽  
Comparable Encryption

User authentication has been widely deployed to prevent unauthorized access in the new era of Internet of Everything (IOE). When user passes the legal authentication, he/she can do series of operations in database. We mainly concern issues of data security and comparable queries over ciphertexts in IOE. In traditional database, a Short Comparable Encryption (SCE) scheme has been widely used by authorized users to conduct comparable queries over ciphertexts, but existing SCE schemes still incur high storage and computational overhead as well as economic burden. In this paper, we first propose a basic Short Comparable Encryption scheme based on sliding window method (SCESW), which can significantly reduce computational and storage burden as well as enhance work efficiency. Unfortunately, as the cloud service provider is a semitrusted third party, public auditing mechanism needs to be furnished to protect data integrity. To further protect data integrity and reduce management overhead, we present an enhanced SCESW scheme based on position-aware Merkle tree, namely, PT-SCESW. Security analysis proves that PT-SCESW and SCESW schemes can guarantee completeness and weak indistinguishability in standard model. Performance evaluation indicates that PT-SCESW scheme is efficient and feasible in practical applications, especially for smarter and smaller computing devices in IOE.

scholarly journals An Improved Blockchain-Based Secure Data Deduplication using Attribute-Based Role Key Generation with Efficient Cryptographic Methods

2021 ◽  
Author(s):  
Ruba S ◽  
A.M. Kalpana
Keyword(s):  
Cloud Storage ◽  
Data Integrity ◽  
Cloud Service ◽  
Third Party ◽  
Key Generation ◽  
Data Deduplication ◽  
Cloud Data ◽  
Redundant Data ◽  
Encrypt Data ◽  
Secure Data

Abstract Deduplication can be used as a data redundancy removal method that has been constructed to save system storage resources through redundant data reduction in cloud storage. Now a day, deduplication techniques are increasingly exploited to cloud data centers with the growth of cloud computing techniques. Therefore, many deduplication methods were presented by many researchers to eliminate redundant data in cloud storage. For secure deduplication, previous works typically have introduced third-party auditors for the data integrity verification, but it may be suffered from data leak by the third-party auditors. And also the customary methods could not face more difficulties in big data deduplication to correctly consider the two conflicting aims of high duplicate elimination ratio and deduplication throughput. In this paper, an improved blockchain-based secure data deduplication is presented with efficient cryptographic methods to save cloud storage securely. In the proposed method, an attribute-based role key generation (ARKG) method is constructed in a hierarchical tree manner to generate a role key when the data owners upload their data to cloud service provider (CSP) and to allow authorized users to download the data. In our system, the smart contract (agreement between the data owner and CSP) is done using SHA-256 (Secure Hash Algorithm-256) to generate a tamper-proofing ledger for data integrity, in which data is protected from illegal modifications, and duplication detection is executed through hash-tag that can be formed by SHA-256. Message Locked encryption (MLE) is employed to encrypt data for data uploading by the data owners to the CSP. The experimental results show that our proposed secure deduplication scheme can give higher throughput and a low duplicate elimination ratio.

A Group Collaboratable Proof of Retrievability Scheme for Cloud Data Storage

2014 ◽  
Vol 13 (7) ◽  
pp. 4625-4632
Author(s):  
Jyh-Shyan Lin ◽  
Kuo-Hsiung Liao ◽  
Chao-Hsing Hsu
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Cloud Service ◽  
Third Party ◽  
Group Collaboration ◽  
Cloud Data ◽  
Cloud Data Storage ◽  
Important Trend ◽  
Data Update ◽  
Proof Of Retrievability

Cloud computing and cloud data storage have become important applications on the Internet. An important trend in cloud computing and cloud data storage is group collaboration since it is a great inducement for an entity to use a cloud service, especially for an international enterprise. In this paper we propose a cloud data storage scheme with some protocols to support group collaboration. A group of users can operate on a set of data collaboratively with dynamic data update supported. Every member of the group can access, update and verify the data independently. The verification can also be authorized to a third-party auditor for convenience.

scholarly journals Secure and Selective Cloud Data Auditing using Deep Machine Learning

2019 ◽  
Vol 9 (2) ◽  
pp. 5471-5479
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Service Providers ◽  
Cloud Service ◽  
Third Party ◽  
Cloud Data ◽  
Data Centre ◽  
Cloud Service Providers ◽  
Characteristics Analysis ◽  
Data Centres

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

scholarly journals Mitigating the Threat due to Data Deduplication Attacks in Cloud Migration using User Layer Authentication with Light Weight Cryptography

2020 ◽  
Vol 9 (3) ◽  
pp. 2539-2545
Keyword(s):  
Data Security ◽  
Service Providers ◽  
Data Integrity ◽  
Cloud Service ◽  
Behavioral Pattern ◽  
Data Migration ◽  
Data Deduplication ◽  
Cloud Data ◽  
Template Attacks ◽  
The Impact

The widespread adoption of multi-cloud in enterprises is one of the root causes of cost-effectiveness. Cloud service providers reduce storage costs through advanced data de-duplication, which also provides vulnerabilities for attackers. Traditional approaches to authentication and data security for a single cloud need to be upgraded to be best suitable for cloud-to-cloud data migration security in order to mitigate the impact of dictionary and template attacks on authentication and data integrity, respectively. This paper proposes a scheme of user layer authentication along with lightweight cryptography. The proposed simulates its mathematical model to analyze the behavioral pattern of time-complexity of data security along with user auth protection. The performance pattern validates the model for scalability and reliability against both authentication and data integrity.

Dynamic Public Data Auditing Schemes on Cloud: A Survey

2018 ◽  
Vol 8 (1) ◽  
pp. 76 ◽  
Author(s):  
R.Santha Maria Rani ◽  
Dr.Lata Ragha
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Service Providers ◽  
Hash Table ◽  
Cloud Service ◽  
Third Party ◽  
Cloud Data ◽  
Merkle Hash Tree ◽  
Public Data ◽  
Data Auditing

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).

scholarly journals BCAS: A blockchain-based ciphertext-policy attribute-based encryption scheme for cloud data security sharing

2021 ◽  
Vol 17 (3) ◽  
pp. 155014772199961
Author(s):  
Yuting Zuo ◽  
Zhaozhe Kang ◽  
Jian Xu ◽  
Zhide Chen
Keyword(s):  
Data Privacy ◽  
Discrete Logarithm ◽  
Third Parties ◽  
Third Party ◽  
Encryption Scheme ◽  
Cloud Data ◽  
Attribute Based Encryption ◽  
Encryption Schemes ◽  
Trusted Third Parties ◽  
Ciphertext Policy

It is the most important and challenging problem to share the data safely in cloud computing. Some so-called trusted third parties may also infringe users’ data privacy. It is an urgent problem for data owners to share data safely with the designated users rather than the third party or other users. Traditional encryption schemes utilize different keys to produce multiple encrypted copies of the same data for users. It is no longer applicable for cloud data sharing security. Attribute-based encryption can solve above problems, but it needs to rely on trusted third parties to protect the users’ privacy. In this article, in order to address the above problems, we propose a blockchain-based ciphertext-policy attribute-based encryption scheme for cloud data secure sharing without relying on any trusted third parties. Blockchain-based ciphertext-policy attribute-based encryption scheme can protect the rights and security of data owner. Compared with existing cloud security schemes, the proposed scheme has more advantages in terms of the six aspects: (1) data owners have the authority to decide who can decrypt the data; (2) the operations of users are retained permanently, and all records are tamper-proof; (3) our proposed scheme has the characteristic of “one-to-many” encryption, and data is encrypted only once; (4) our scheme does not rely on any trusted third party; (5) in terms of the discrete logarithm problem and decisional q parallel-bilinear Diffie–Hellman exponent problem, we prove that our proposed scheme is secure; and (6) experiment shows that our proposed scheme is more efficient than the comparative scheme.

scholarly journals Remote Data Integrity Check

2020 ◽  
Vol 9 (5) ◽  
pp. 661-664
Keyword(s):  
Data Integrity ◽  
Third Party ◽  
Sensitive Data ◽  
Text Data ◽  
Cloud Data ◽  
The Third ◽  
Cipher Text ◽  
Data Owner ◽  
Cloud Server ◽  
The Third Party

In Cloud Storage Server, data integrity plays an important role, given cloud clients might not be aware whether the data is safe or has been tampered with. This system introduces identity-based signature algorithms to protect data that belongs to the data owner and gets the status of cloud data by means of verification through signatures. Since it is practically not possible for the data owner to be available online all the time for checking cloud data integrity, Third party auditor is tasked with verifying the data integrity every time instead of data owner. The Third party auditors should not read the cipher text data while verifying and must authenticate itself to cloud server by performing Proof of Knowledge operation; then cloud server can reveal the sensitive data as block wise and the third party auditor can verify the signature without knowledge of cipher text data. Finally, an audit report is sent to the data owner. This work demonstrates data security and integrity in the cloud..

Privacy Preserving Public Auditing in Cloud: Literature Review

2019 ◽  
pp. 2059-2083
Author(s):  
Thangavel M. ◽  
Varalakshmi P. ◽  
Sridhar S. ◽  
Sindhuja R.
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Large Data ◽  
Cloud Service ◽  
Third Party ◽  
Public Auditing ◽  
Cloud Data ◽  
Security Issues ◽  
Data Owner ◽  
Cloud Data Storage

Cloud computing has given a bloom to the technical world by providing various services. Data storage is the essential factor for the users who are having or working with lots and lots of data. Cloud data storage becomes the only way to store and maintain the large data, which can be accessed from anywhere and anytime. The open nature of cloud computing leads to some security issues. With respect to the cloud data storage, the Cloud Service Provider (CSP) has to provide security for the data outsourced. Data owner will be concerned on the data correctness after outsourcing into the cloud. To verify the data correctness, ensuring the state of data at the cloud data storage is needed, which is performed with the help of a Trusted Third Party Auditor (TTPA). Data owner can also perform the verification task, but it leads to computation cost and communication costs in huge amount. This survey gives a brief on public auditing schemes to explore what are all the system models designed by various researchers.

Sign in / Sign up

Export Citation Format

Share Document