A Systematic Mapping review to Remote Data Integrity Verification Systems for Cloud Computing

Authors

  • Bassam Hindy Hameed Computer Department, Collage of science, University of Diyala, Iraq
  • Ghassan Sabeeh Mahmood Computer Department, Collage of science, University of Diyala, Iraq

DOI:

https://doi.org/10.58564/IJSER.2.4.2023.118

Keywords:

Cloud computing, Remote data integrity verification, RDIV systems, Data security, Cryptographic techniques, Merkle trees, Verification mechanisms, Cloud-based IoT, Systematic mapping, Data integrity, Cloud storage.

Abstract

Cloud computing has totally changed the way information is put away and gotten to. However, it has moreover raised concerns, approximately the security and astuteness of that information. In arrange to address these concerns and make beyond any doubt that information put away on untrusted cloud servers remains solid and unaltered Remote Data Integrity Verification (RDIV) frameworks have ended up significant. This term paper presents a mapping think about of Inaccessible Data Integrity Confirmation frameworks within the setting of cloud computing. Its objective is to distinguish existing investigate categorize it reveal patterns and shed light on regions for inquire about.

In the digital landscape, the Internet of Things (IoT) has created new opportunities and challenges as everyday objects are becoming interconnected, collecting large volumes of data. We interact with our surroundings and manage data in a whole new way thanks to cloud computing and IoT, which work in symbiotic harmony. Data generated by IoT devices can be harnessed and processed using cloud computing's robust infrastructure. Furthermore, IoT expands the reach of cloud computing to include a myriad of smart devices, sensors, and actuators that are all interconnected.

By conducting a search handle, we have assembled a collection of inquire about papers and scholarly articles that particularly center on RDIV frameworks in cloud computing. These distributions were carefully analyzed utilizing incorporation and prohibition criteria to classify the Remote Data Integrity Verification frameworks based on their fundamental methods cryptographic strategies utilized, confirmation instruments utilized and sending models connected.

By synthesizing the comes about, this paper highlights current investigate trends and gives experiences into potential inquire about crevices within the field of Remote Data Integrity Verification frameworks for cloud computing. We talk about the require for upgraded scalability and execution optimization to bolster large-scale cloud arrangements successfully. Besides, we recognize the require for assist investigation of privacy-preserving Remote Data Integrity Verification procedures to ensure sensitive information from unauthorized introduction.

References

Zhang, W., Bai, Y., & Feng, J. (2022). Tiia: A blockchain-enabled threat intelligence integrity audit scheme for iiot. Future Generation Computer Systems, 132, 254-265.

Barakat, M., Saeed, R. A., & Edam, S. (2023, May). A Comparative Study on Cloud and Edgeb Computing: A Survey on Current Research Activities and Applications. In 2023 IEEE 3rd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA) (pp. 679-684). IEEE.

KN, R. P. (2023, April). The Intelligent Information Integrity Model to Ensure the Database Protection Using Blockchain in Cloud Networking. In 2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) (pp. 1-7). IEEE.

Xu, H. (2023, April). Check for Cybersecurity and Data Quality in Cloud Computing: A Research Framework Hongjiang Xu School of Business, Butler University, 4600 Sunset Avenue, Indianapolis, IN 46208, USA. In Information Systems: 19th European, Mediterranean, and Middle Eastern Conference, EMCIS 2022, Virtual Event, December 21–22, 2022, Proceedings (Vol. 464, p. 201). Springer Nature.

Rani, J., & Nath, R. (2022). Data Integrity Verification Schemes in Cloud Computing Environment: A Survey. Information and Communication Technology for Competitive Strategies (ICTCS 2021) Intelligent Strategies for ICT, 641-651.

S. R. Pujar, S. S. Chaudhari and R. Aparna, "Survey on Data Integrity and Verification for Cloud Storage," 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Kharagpur, India, 2020, pp. 1-7, doi: 10.1109/ICCCNT49239.2020.9225594.

R. Kumar and M. P. S. Bhatia, "A Systematic Review of the Security in Cloud Computing: Data Integrity, Confidentiality and Availability," 2020 IEEE International Conference on Computing, Power and Communication Technologies (GUCON), Greater Noida, India, 2020, pp. 334-337, doi: 10.1109/GUCON48875.2020.9231255.

Iankoulova, I., & Daneva, M. (2012, May). Cloud computing security requirements: A systematic review. In 2012 Sixth International Conference on Research Challenges in Information Science (RCIS) (pp. 1-7). IEEE.

https://www.elsevier.com

https://dl.acm.org/.

https://www.proquest.com/.

https://ieeexplore.ieee.org/Xplore/home.jsp.

https://www.sciencedirect.com/

Lopez-Herrejon, R. E., Linsbauer, L., & Egyed, A. (2015). A systematic mapping study of search-based software engineering for software product lines. Information and software technology, 61, 33-51.‏

Abbas, A. K., Fleh, S. Q., & Safi, H. H. (2015). SYSTEMATIC MAPPING STUDY ON MANAGING VARIABILITY IN SOFTWARE PRODUCT LINE ENGINEERING: Communication. Diyala Journal of Engineering Sciences, 511-520.

Aromataris, E., Fernandez, R., Godfrey, C. M., Holly, C., Khalil, H., & Tungpunkom, P. (2015). Summarizing systematic reviews: methodological development, conduct and reporting of an umbrella review approach. JBI Evidence Implementation, 13(3), 132-140.‏

Xie, Gaopeng & Liu, Yuling & Xin, Guojiang & Yang, Qiuwei. (2021). Blockchain-Based Cloud Data Integrity Verification Scheme with High Efficiency. Security and Communication Networks. 2021. 1-15. 10.1155/2021/9921209.

Ping, Y.; Zhan, Y.; Lu, K.; Wang, B. Public Data Integrity Verification Scheme for Secure Cloud Storage. Information 2020, 11, 409. https://doi.org/10.3390/info11090409

Karumanchi, M. D., Sheeba, J. I., & Devaneyan, S. P. (2022). Integrated Internet of Things with cloud developed for data integrity problems on supply chain management. Measurement: Sensors, 24, 100445.

Zhou, Z., Luo, X., Bai, Y., Wang, X., Liu, F., Liu, G., & Xu, Y. (2022). A Scalable Blockchain-Based Integrity Verification Scheme. Wireless Communications and Mobile Computing, 2022.

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Published

2023-12-01

How to Cite

Hindy Hameed, B., & Sabeeh Mahmood, G. (2023). A Systematic Mapping review to Remote Data Integrity Verification Systems for Cloud Computing. Al-Iraqia Journal for Scientific Engineering Research, 2(4), 38–50. https://doi.org/10.58564/IJSER.2.4.2023.118

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Articles