A Security and Privacy Aware Computing Approach on Data Sharing in Cloud Environment

Authors

DOI:

https://doi.org/10.21123/bsj.2022.7077

Abstract

Today, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be integrated with the texts encrypted to ensure system safety and to prevent the violation of data owners ' privacy. For this purpose, before sending the data to the cloud, it must be encrypted in such a way that operations such as max, min, etc. can be performed on it. The proposed method uses order-preserving symmetric encryption (OPES), which does not require decryption or re-encryption for mathematical operations. This process leads to a great improvement in delay. The OPES scheme allows comparison operations to be performed directly on encrypted data without decryption operands. According to the results, it is obvious that the proposed strategy is in a better position compared to the base paper in terms of the system's ability to find the malicious elements that cause the problem of leakage and in terms of system security to prevent the violation of privacy.

References

Hajibaba M, Gorgin S. A review on modern distributed computing paradigms: Cloud computing, jungle computing and fog computing. J Comput. Inf. Technol. 2014;22(2):69-84.

Fan K, Liu T, Zhang K, Li H, Yang Y. A secure and efficient outsourced computation on data sharing scheme for privacy computing. J Parallel Distrib Comput. 2020; 135: 169-76.

Abed Marwa M, Manal F Younis. Developing load balancing for IoT-cloud computing based on advanced firefly and weighted round robin algorithms. Baghdad Sci J. 2019; 16(1): 130-139.

Waters B. Ciphertext-policy attribute-based encryption: An expressive, efficient, and provably secure realizatio. In International Workshop on Public Key Cryptography Springer, Berlin, Heidelberg. 2011: pp. 53-70.

Li H, Lan C, Fu X, Wang C, Li F, Guo H. A secure and lightweight fine-grained data sharing scheme for mobile cloud computing. Sensors. 2020; 20(17): 4720.

Albu-Salih AT, Seno SA, Mohammed SJ. Dynamic routing method over hybrid SDN for flying ad hoc network. Baghdad Sci J. 2018;15(3): 361-368.

Xiong H, Zhang H, Sun J. Attribute-based privacy-preserving data sharing for dynamic groups in cloud computing. IEEE Syst J. 2018; 13(3): 2739-50.

Li Q, Tian Y, Zhang Y, Shen L, Guo J. Efficient privacy-preserving access control of mobile multimedia data in cloud computing. IEEE Access. 2019; 7: 131534-42.

Liu J, Tang H, Sun R, Du X, Guizani M. Lightweight and privacy-preserving medical services access for healthcare cloud. IEEE Access. 2019; 7: 106951-61.

Huang Q, Zhang Z, Yang Y. Privacy-preserving media sharing with scalable access control and secure deduplication in mobile cloud computing. IEEE Trans Mob Comput. 2020; 20(5): 1951-64.

Xu J, Wei L, Wu W, Wang A, Zhang Y, Zhou F. Privacy-preserving data integrity verification by using lightweight streaming authenticated data structures for healthcare cyber–physical system. Future Gener Comput. Syst. 2020; 108: 1287-96.

Li W, Cao J, Hu K, Xu J, Buyya R. A trust-based agent learning model for service composition in mobile cloud computing environments. IEEE Access. 2019; 7: 34207-26.

Rathi SR, Kolekar VK. Trust model for computing security of cloud. In 2018 Fourth international conference on computing communication control and automation (ICCUBEA). IEEE. 2018: pp. 1-5.

Wu X. Study on Trust Model for Multi-users in Cloud Computing. Int J Netw Secur. 2018; 20(4): 674-8.

Saeed O, Shaikh RA. A user-based trust model for cloud computing environment. Int J Adv Comput. 2018;9(3): 337-46.

Mohsenzadeh A, Bidgoly AJ, Farjami Y. A novel reward and penalty trust evaluation model based on confidence interval using Petri Net. J Netw Comput Appl. 2020; 154: 102533.

Sun P. Research on cloud computing service based on trust access control. Int J Eng. 2020; 12: 1847979019897444.

Kumar P, Alphonse PJ. Attribute based encryption in cloud computing: A survey, gap analysis, and future directions. J Netw Comput Appl. 2018; 108: 37-52.

Li J, Chen N, Zhang Y. Extended file hierarchy access control scheme with attribute based encryption in cloud computing. IEEE Trans Emerg Topics Comput. 2019.

Yang Y, Chen X, Chen H, Du X. Improving privacy and security in decentralizing multi-authority attribute-based encryption in cloud computing. IEEE Access. 2018; 6: 18009-21.

Zhang L, Gao X, Guo F, Hu G. Improving the Leakage Rate of Ciphertext-Policy Attribute-Based Encryption for Cloud Computing. IEEE Access. 2020; 8: 94033-42.

Liao Y, Zhang G, Chen H. Cost-efficient outsourced decryption of attribute-based encryption schemes for both users and cloud server in green cloud computing. IEEE Access. 2020; 8: 20862-9.

Roy S, Das AK, Chatterjee S, Kumar N, Chattopadhyay S, Rodrigues JJ. Provably secure fine-grained data access control over multiple cloud servers in mobile cloud computing-based healthcare applications. IEEE Trans Industr Inform. 2018; 15(1): 457-68.

Zhou L, Wang Q, Sun X, Kulicki P, Castiglione A. Quantum technique for access control in cloud computing II: Encryption and key distribution. J Netw Comput Appl. 2018; 103: 178-84.

Yang C, Tan L, Shi N, Xu B, Cao Y, Yu K. AuthPrivacyChain: A blockchain-based access control framework with privacy protection in cloud. IEEE Access. 2020; 8: 70604-15.

Xiong S, Ni Q, Wang L, Wang Q. SEM-ACSIT: secure and efficient multiauthority access control for IoT coud storage. IEEE Internet Things J. 2020;7(4):2914-27.

Gupta H, Vahid Dastjerdi A, Ghosh SK, Buyya R. iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments. Software Pract Expe. 2017;47(9):1275-96.

Downloads

Published

2022-12-05

How to Cite

1.
A Security and Privacy Aware Computing Approach on Data Sharing in Cloud Environment. Baghdad Sci.J [Internet]. 2022 Dec. 5 [cited 2024 Mar. 29];19(6(Suppl.):1572. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/7077