Propagation Delays and Data Integrity of Cellular and WiFi Networks from IOT devices to cloud storage

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.

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Data Integrity Techniques in Cloud Computing: An Analysis

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i8.36 ◽

2017 ◽

Vol 7 (8) ◽

pp. 121 ◽

Cited By ~ 1

Author(s):

Neha Thakur ◽

Aman Kumar Sharma

Keyword(s):

Cloud Computing ◽

Cloud Storage ◽

Data Integrity ◽

Advantages And Disadvantages ◽

Security Models ◽

Cloud Storage Service ◽

Storage Service ◽

Cloud Users ◽

It Enterprises

Cloud computing has been envisioned as the definite and concerning solution to the rising storage costs of IT Enterprises. There are many cloud computing initiatives from IT giants such as Google, Amazon, Microsoft, IBM. Integrity monitoring is essential in cloud storage for the same reasons that data integrity is critical for any data centre. Data integrity is defined as the accuracy and consistency of stored data, in absence of any alteration to the data between two updates of a file or record. In order to ensure the integrity and availability of data in Cloud and enforce the quality of cloud storage service, efficient methods that enable on-demand data correctness verification on behalf of cloud users have to be designed. To overcome data integrity problem, many techniques are proposed under different systems and security models. This paper will focus on some of the integrity proving techniques in detail along with their advantages and disadvantages.

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Data Integrity Auditing for Secure Cloud Storage using User Behavior Prediction

Computers & Security ◽

10.1016/j.cose.2021.102245 ◽

2021 ◽

pp. 102245

Author(s):

Junfeng Tian ◽

Haoning Wang ◽

Meng Wang

Keyword(s):

Cloud Storage ◽

User Behavior ◽

Data Integrity ◽

Behavior Prediction ◽

Secure Cloud Storage

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Blockchain Processing Technique Based on Multiple Hash Chains for Minimizing Integrity Errors of IoT Data in Cloud Environments

Sensors ◽

10.3390/s21144679 ◽

2021 ◽

Vol 21 (14) ◽

pp. 4679

Author(s):

Yoon-Su Jeong

Keyword(s):

Distributed Processing ◽

Data Integrity ◽

Processing Technique ◽

Code Length ◽

Process Data ◽

Secure Storage ◽

Hash Code ◽

Linkage Information ◽

Cloud Environments ◽

Iot Devices

As IoT (Internet of Things) devices are diversified in the fields of use (manufacturing, health, medical, energy, home, automobile, transportation, etc.), it is becoming important to analyze and process data sent and received from IoT devices connected to the Internet. Data collected from IoT devices is highly dependent on secure storage in databases located in cloud environments. However, storing directly in a database located in a cloud environment makes it not only difficult to directly control IoT data, but also does not guarantee the integrity of IoT data due to a number of hazards (error and error handling, security attacks, etc.) that can arise from natural disasters and management neglect. In this paper, we propose an optimized hash processing technique that enables hierarchical distributed processing with an n-bit-size blockchain to minimize the loss of data generated from IoT devices deployed in distributed cloud environments. The proposed technique minimizes IoT data integrity errors as well as strengthening the role of intermediate media acting as gateways by interactively authenticating blockchains of n bits into n + 1 and n − 1 layers to normally validate IoT data sent and received from IoT data integrity errors. In particular, the proposed technique ensures the reliability of IoT information by validating hash values of IoT data in the process of storing index information of IoT data distributed in different locations in a blockchain in order to maintain the integrity of the data. Furthermore, the proposed technique ensures the linkage of IoT data by allowing minimal errors in the collected IoT data while simultaneously grouping their linkage information, thus optimizing the load balance after hash processing. In performance evaluation, the proposed technique reduced IoT data processing time by an average of 2.54 times. Blockchain generation time improved on average by 17.3% when linking IoT data. The asymmetric storage efficiency of IoT data according to hash code length is improved by 6.9% on average over existing techniques. Asymmetric storage speed according to the hash code length of the IoT data block was shown to be 10.3% faster on average than existing techniques. Integrity accuracy of IoT data is improved by 18.3% on average over existing techniques.

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Data integrity checking with reliable data transfer for secure cloud storage

International Journal of Web and Grid Services ◽

10.1504/ijwgs.2018.088396 ◽

2018 ◽

Vol 14 (1) ◽

pp. 106 ◽

Cited By ~ 9

Author(s):

Yong Wang ◽

Xiaoling Tao ◽

Jianbing Ni ◽

Yong Yu

Keyword(s):

Cloud Storage ◽

Data Transfer ◽

Data Integrity ◽

Reliable Data ◽

Integrity Checking ◽

Data Integrity Checking ◽

Secure Cloud Storage ◽

Reliable Data Transfer

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

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v10i2.pp2011-2022 ◽

2020 ◽

Vol 10 (2) ◽

pp. 2011

Author(s):

Anil Kumar G. ◽

Shantala C. P.

Keyword(s):

Cloud Storage ◽

Data Privacy ◽

Storage System ◽

Data Integrity ◽

Data Deduplication ◽

Research Issues ◽

Existing Problems ◽

Research Survey ◽

Challenging Tasks ◽

Future Direction

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.

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Cloud Data Integrity Verification Algorithm for Sustainable Accounting Informatization

Mathematical Problems in Engineering ◽

10.1155/2021/2330502 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Lin Yang

Keyword(s):

Big Data ◽

Execution Time ◽

Cloud Storage ◽

Computing Time ◽

Data Integrity ◽

Cloud Data ◽

Integrity Verification ◽

Verification Algorithm ◽

Advantages And Disadvantages ◽

Better Than

In recent years, people have paid more and more attention to cloud data. However, because users do not have absolute control over the data stored on the cloud server, it is necessary for the cloud storage server to provide evidence that the data are completely saved to maintain their control over the data. Give users all management rights, users can independently install operating systems and applications and can choose self-service platforms and various remote management tools to manage and control the host according to personal habits. This paper mainly introduces the cloud data integrity verification algorithm of sustainable computing accounting informatization and studies the advantages and disadvantages of the existing data integrity proof mechanism and the new requirements under the cloud storage environment. In this paper, an LBT-based big data integrity proof mechanism is proposed, which introduces a multibranch path tree as the data structure used in the data integrity proof mechanism and proposes a multibranch path structure with rank and data integrity detection algorithm. In this paper, the proposed data integrity verification algorithm and two other integrity verification algorithms are used for simulation experiments. The experimental results show that the proposed scheme is about 10% better than scheme 1 and about 5% better than scheme 2 in computing time of 500 data blocks; in the change of operation data block time, the execution time of scheme 1 and scheme 2 increases with the increase of data blocks. The execution time of the proposed scheme remains unchanged, and the computational cost of the proposed scheme is also better than that of scheme 1 and scheme 2. The scheme in this paper not only can verify the integrity of cloud storage data but also has certain verification advantages, which has a certain significance in the application of big data integrity verification.

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