scholarly journals Privacy-Preserving Outsourced Auditing Scheme for Dynamic Data Storage in Cloud

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Tengfei Tu ◽  
Lu Rao ◽  
Hua Zhang ◽  
Qiaoyan Wen ◽  
Jia Xiao
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Data Privacy ◽  
Computational Cost ◽  
Security Analysis ◽  
Data Encryption ◽  
Third Party ◽  
User Data ◽  
Data Auditing ◽  
User Focus

As information technology develops, cloud storage has been widely accepted for keeping volumes of data. Remote data auditing scheme enables cloud user to confirm the integrity of her outsourced file via the auditing against cloud storage, without downloading the file from cloud. In view of the significant computational cost caused by the auditing process, outsourced auditing model is proposed to make user outsource the heavy auditing task to third party auditor (TPA). Although the first outsourced auditing scheme can protect against the malicious TPA, this scheme enables TPA to have read access right over user’s outsourced data, which is a potential risk for user data privacy. In this paper, we introduce the notion of User Focus for outsourced auditing, which emphasizes the idea that lets user dominate her own data. Based on User Focus, our proposed scheme not only can prevent user’s data from leaking to TPA without depending on data encryption but also can avoid the use of additional independent random source that is very difficult to meet in practice. We also describe how to make our scheme support dynamic updates. According to the security analysis and experimental evaluations, our proposed scheme is provably secure and significantly efficient.

scholarly journals A New Hybrid Automated Security Framework to Cloud Storage System

Cryptography ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 37
Author(s):  
Noha E. El-Attar ◽  
Doaa S. El-Morshedy ◽  
Wael A. Awad
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Data Privacy ◽  
High Performance ◽  
Storage System ◽  
Third Party ◽  
File Size ◽  
Cloud Data ◽  
Security Issues ◽  
User Data

The need for cloud storage grows day after day due to its reliable and scalable nature. The storage and maintenance of user data at a remote location are severe issues due to the difficulty of ensuring data privacy and confidentiality. Some security issues within current cloud systems are managed by a cloud third party (CTP), who may turn into an untrustworthy insider part. This paper presents an automated Encryption/Decryption System for Cloud Data Storage (AEDS) based on hybrid cryptography algorithms to improve data security and ensure confidentiality without interference from CTP. Three encryption approaches are implemented to achieve high performance and efficiency: Automated Sequential Cryptography (ASC), Automated Random Cryptography (ARC), and Improved Automated Random Cryptography (IARC) for data blocks. In the IARC approach, we have presented a novel encryption strategy by converting the static S-box in the AES algorithm to a dynamic S-box. Furthermore, the algorithms RSA and Twofish are used to encrypt the generated keys to enhance privacy issues. We have evaluated our approaches with other existing symmetrical key algorithms such as DES, 3DES, and RC2. Although the two proposed ARC and ASC approaches are more complicated, they take less time than DES, DES3, and RC2 in processing the data and obtaining better performance in data throughput and confidentiality. ARC outperformed all of the other algorithms in the comparison. The ARC’s encrypting process has saved time compared with other algorithms, where its encryption time has been recorded as 22.58 s for a 500 MB file size, while the DES, 3DES, and RC2 have completed the encryption process in 44.43, 135.65, and 66.91 s, respectively, for the same file size. Nevertheless, when the file sizes increased to 2.2 GB, the ASC proved its efficiency in completing the encryption process in less time.

scholarly journals An enhanced security tree to secure cloud data

2017 ◽  
Vol 7 (1.1) ◽  
pp. 64 ◽  
Author(s):  
S. Renu ◽  
S.H. Krishna Veni
Keyword(s):  
Data Storage ◽  
Binary Tree ◽  
Data Encryption ◽  
Third Party ◽  
Data Outsourcing ◽  
Cloud Data ◽  
Security Issues ◽  
Security Services ◽  
Computing Services ◽  
User Data

The Cloud computing services and security issues are growing exponentially with time. All the CSPs provide utmost security but the issues still exist. Number of technologies and methods are emerged and futile day by day. In order to overcome this situation, we have also proposed a data storage security system using a binary tree approach. Entire services of the binary tree are provided by a Trusted Third Party (TTP) .TTP is a government or reputed organization which facilitates to protect user data from unauthorized access and disclosure. The security services are designed and implemented by the TTP and are executed at the user side. Data classification, Data Encryption and Data Storage are the three vital stages of the security services. An automated file classifier classify unorganized files into four different categories such as Sensitive, Private, Protected and Public. Applied cryptographic techniques are used for data encryption. File splitting and multiple cloud storage techniques are used for data outsourcing which reduces security risks considerably. This technique offers  file protection even when the CSPs compromise. 

scholarly journals Research on Data Security Audit in Cloud Computing for Big Data Environment

CONVERTER ◽  
2021 ◽  
pp. 659-668
Author(s):  
Li Shuanbao
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Cloud Storage ◽  
Data Privacy ◽  
Data Encryption ◽  
Third Party ◽  
Certification Authority ◽  
Data Types ◽  
The Impact ◽  
Data Audit

The modernization of industrial industry cannot be separated from the development of big data.In order to meet this challenge, cloud data integrity audit has been proposed in recent years and received extensive attention. Based on the in-depth study of the impact of different cloud storage data types on the audit scheme, this paper proposes an audit scheme based on Dynamic Hash table.Based on this, this paper explores a variety of cloud storage audit algorithms for different data types to deal with different security challenges.Facing a series of data security problems brought by cloud computing, this paper analyzes the concept, working principle and characteristics of cloud computing, and discusses the data security risks brought by cloud computing from four aspects. At the same time, this paper elaborates the data security strategy from five aspects: data transmission, data privacy, data isolation, data residue and data audit. In this paper, we propose to adopt end-to-end data encryption technology, build private cloud or hybrid cloud, share table architecture, destroy encrypted data related media, and introduce third-party certification authority for data audit.

scholarly journals Data Privacy Preservation using AES-GCM Encryption in Heroku Cloud

2019 ◽  
Vol 8 (3) ◽  
pp. 7544-7548
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Privacy ◽  
Privacy Preservation ◽  
Service Industry ◽  
Computational Cost ◽  
Cloud Service ◽  
Third Party ◽  
Sensitive Information ◽  
Cloud Data

The increasing popularity of cloud data storage and its ever-rising versatility, shows that cloud computing is one of the most widely excepted phenomena. It not only helps with powerful computing facilities but also reduce a huge amount of computational cost. And with such high demand for storage has raised the growth of the cloud service industry that provides an affordable, easy-to-use and remotely-accessible services. But like every other emerging technology it carries some inherent security risks associated and cloud storage is no exception. The prime reason behind it is that users have to blindly trust the third parties while storing the useful information, which may not work in the best of interest. Hence, to ensure the privacy of sensitive information is primarily important for any public, third-party cloud. In this paper, we mainly focus on proposing a secure cloud framework with encrypting sensitive data’s using AES-GCM cryptographic techniques in HEROKU cloud platform. Here we tried to implement Heroku as a cloud computing platform, used the AES-GCM algorithm and evaluate the performance of the said algorithm. Moreover, analyses the performance of AES/GCM execution time with respect to given inputs of data

scholarly journals Attribute-Based User Revocable Data Integrity Audit for Internet-of-Things Devices in Cloud Storage

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yaowei Wang ◽  
Chen Chen ◽  
Zhenwei Chen ◽  
Jiangyong He
Keyword(s):  
Internet Of Things ◽  
Cloud Storage ◽  
Security Analysis ◽  
Data Integrity ◽  
Third Party ◽  
Iot Devices ◽  
And Performance ◽  
Data Auditing ◽  
Cloud Storage Environment ◽  
Access To Data

Mobile crowdsensing (MCS) is a sensing paradigm exploiting the capabilities of mobile devices (Internet-of-Things devices, smartphones, etc.) to gather large volume of data. MCS has been widely used in cloud storage environment. However, MCS often faces the challenge of data integrity and user revocation issues. To solve these challenges, this paper uses attribute-based revocable signature mechanisms to construct a data integrity auditing scheme for IoT devices in the cloud storage environment. Users use attribute private keys to generate attribute signatures, and limit the user’s permission to use shared data through access policy control. Only when the user attribute is included in the global attribute set, and the attribute threshold is not less than the specified number, the user can use the attribute key for the data to generate a valid signature that can be authenticated under the control of the signature strategy. At the same time, the group manager (GM) can send secret information to a third-party auditor (TPA) to track the creator of the signature, to withdraw the user’s access to data when the business changes, and realize the safe revocation of user group membership. Formal security analysis and experimental results show that the proposed data-auditing solution is suitable for IoT devices in the cloud storage environment with respect to security and performance.

A New User-controlled and Efficient Encrypted Data Sharing Model in Cloud Storage

2019 ◽  
Vol 13 (4) ◽  
pp. 356-363
Author(s):  
Yuezhong Wu ◽  
Wei Chen ◽  
Shuhong Chen ◽  
Guojun Wang ◽  
Changyun Li
Keyword(s):  
Data Sharing ◽  
Data Security ◽  
Cloud Storage ◽  
Screening Program ◽  
Original Data ◽  
Third Party ◽  
Active System ◽  
Encrypted Data ◽  
Active User ◽  
User Data

Background: Cloud storage is generally used to provide on-demand services with sufficient scalability in an efficient network environment, and various encryption algorithms are typically applied to protect the data in the cloud. However, it is non-trivial to obtain the original data after encryption and efficient methods are needed to access the original data. Methods: In this paper, we propose a new user-controlled and efficient encrypted data sharing model in cloud storage. It preprocesses user data to ensure the confidentiality and integrity based on triple encryption scheme of CP-ABE ciphertext access control mechanism and integrity verification. Moreover, it adopts secondary screening program to achieve efficient ciphertext retrieval by using distributed Lucene technology and fine-grained decision tree. In this way, when a trustworthy third party is introduced, the security and reliability of data sharing can be guaranteed. To provide data security and efficient retrieval, we also combine active user with active system. Results: Experimental results show that the proposed model can ensure data security in cloud storage services platform as well as enhance the operational performance of data sharing. Conclusion: The proposed security sharing mechanism works well in an actual cloud storage environment.

scholarly journals Study of privacy-preserving framework for cloud storage

2011 ◽  
Vol 8 (3) ◽  
pp. 801-819 ◽  
Author(s):  
Huang Ruwei ◽  
Gui Xiaolin ◽  
Yu Si ◽  
Zhuang Wei
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Security Analysis ◽  
Bloom Filter ◽  
Data Access ◽  
Data Retrieval ◽  
Privacy Preserving ◽  
Index Structure ◽  
Structure Generation ◽  
Access Right

In order to implement privacy-preserving, efficient and secure data storage and access environment of cloud storage, the following problems must be considered: data index structure, generation and management of keys, data retrieval, treatments of change of users? access right and dynamic operations on data, and interactions among participants. To solve those problems, the interactive protocol among participants is introduced, an extirpation-based key derivation algorithm (EKDA) is designed to manage the keys, a double hashed and weighted Bloom Filter (DWBF) is proposed to retrieve the encrypted keywords, which are combined with lazy revocation, multi-tree structure, asymmetric and symmetric encryptions, which form a privacypreserving, efficient and secure framework for cloud storage. The experiment and security analysis show that EKDA can reduce the communication and storage overheads efficiently, DWBF supports ciphertext retrieval and can reduce communication, storage and computation overhead as well, and the proposed framework is privacy preserving while supporting data access efficiently.

scholarly journals Enhanced Integrity Checking for Preserve Data Owner and User Level Privacy Using Dual Cryptography Approach

2019 ◽  
pp. 138-146
Author(s):  
Poovizhi. M ◽  
Raja. G
Keyword(s):  
Data Storage ◽  
Data Privacy ◽  
Capital Expenditure ◽  
Data Access ◽  
Third Party ◽  
Configurable Computing ◽  
Local Data ◽  
Cloud Data ◽  
On Demand ◽  
Integrity Checking

Using Cloud Storage, users can tenuously store their data and enjoy the on-demand great quality applications and facilities from a shared pool of configurable computing resources, without the problem of local data storage and maintenance. However, the fact that users no longer have physical possession of the outsourced data makes the data integrity protection in Cloud Computing a formidable task, especially for users with constrained dividing resources. From users’ perspective, including both individuals and IT systems, storing data remotely into the cloud in a flexible on-demand manner brings tempting benefits: relief of the burden for storage management, universal data access with independent geographical locations, and avoidance of capital expenditure on hardware, software, and personnel maintenances, etc. To securely introduce an effective Sanitizer and third party auditor (TPA), the following two fundamental requirements have to be met: 1) TPA should be able to capably audit the cloud data storage without demanding the local copy of data, and introduce no additional on-line burden to the cloud user; 2) The third party auditing process should take in no new vulnerabilities towards user data privacy. In this project, utilize and uniquely combine the public auditing protocols with double encryption approach to achieve the privacy-preserving public cloud data auditing system, which meets all integrity checking without any leakage of data. To support efficient handling of multiple auditing tasks, we further explore the technique of online signature to extend our main result into a multi-user setting, where TPA can perform multiple auditing tasks simultaneously. We can implement double encryption algorithm to encrypt the data twice and stored cloud server in Electronic Health Record applications.

Security Analysis on a Public POR Scheme in Cloud Storage

2014 ◽  
Vol 556-562 ◽  
pp. 5395-5399
Author(s):  
Jian Hong Zhang ◽  
Wen Jing Tang
Keyword(s):  
Data Storage ◽  
Cloud Storage ◽  
Security Analysis ◽  
Data Integrity ◽  
Data File ◽  
Cloud Data ◽  
Security Proof ◽  
Cloud Server ◽  
Cloud Data Storage ◽  
Active Attack

Data integrity is one of the biggest concerns with cloud data storage for cloud user. Besides, the cloud user’s constrained computing capabilities make the task of data integrity auditing expensive and even formidable. Recently, a proof-of-retrievability scheme proposed by Yuan et al. has addressed the issue, and security proof of the scheme was provided. Unfortunately, in this work we show that the scheme is insecure. Namely, the cloud server who maliciously modifies the data file can pass the verification, and the client who executes the cloud storage auditing can recover the whole data file through the interactive process. Furthermore, we also show that the protocol is vulnerable to an efficient active attack, which means that the active attacker is able to arbitrarily modify the cloud data without being detected by the auditor in the auditing process. After giving the corresponding attacks to Yuan et al.’s scheme, we suggest a solution to fix the problems.

Data Storage Scheme of Sensor Network Based on HDFS

2014 ◽  
Vol 926-930 ◽  
pp. 2462-2465 ◽  
Author(s):  
Hui Xiang Zhou ◽  
Qiao Yan Wen
Keyword(s):  
Sensor Network ◽  
Data Storage ◽  
Cloud Storage ◽  
High Reliability ◽  
Storage System ◽  
Security Analysis ◽  
Storage Security ◽  
Mass Data ◽  
Storage Scheme ◽  
Multiple Copies

In order to solve the problem of growing massive of data in sensor network, we propose a new scheme of data storage for sensor network based on HDFS which is a cloud-based storage platform, it effectively alleviate the pressure of mass data storage on sensor network, and improved the scalability of storage system and part of the enhanced the data storage security on sensor network. And this scheme is based on cloud storage platform, storage the data which collected by sensors to each data node using a distributed architecture solution, and keep multiple copies of data in order to maintain its high reliability of data. As reducing the pressure of data storage, but also protects the security of stored data as shown by security analysis.

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