Proposing a Cluster-Based Method to Compose Privacy-Aware Cloud Services

Reza Khandan, Sima Emadi


Protecting data and providing the users’ security, which is presented in the cloud services environments, is crucial for organizations and people because some of the organizations consider transferring their important applications and sensitive data to the simple cloud environment as a big risk. Because of these concerns, a cloud provider has to create certainty that the clients are able to maintain their security and control over privacy in important applications. While cloud calculations have some advantages, they have many disadvantages too. One of them is threats, which jeopardize it in terms of security and serves as a major barrier for users to adapt to cloud systems. In this research, security, which is one of the most important challenges in cloud, and its threats, such as physical security, information security, data retrieval, controlling user accessibility by the provider, and interval in servicing, as well as strategies to encounter each of them, such as safe infrastructures, and other challenges have been taken into consideration. In this research, we propose a new method, 2 Steps Clustering-Combining Method (2SCCM), which resulted in drop in the number of migrations. This method, which uses two-step clustering and data classification, is able to reduce the number of migrations, conceal the services by combining, and improve the quality of medical information extracted from the web services. In terms of medical data, this not only increases productivity, but also enhances the security and privacy in cloud services as much as possible.


Web Services, Web services combining, Privatization, Privacy, Clustering, Migration

Full Text:



Achananuparp, P., Han, H., Nasraoui, O., & Johnson, R. (2007, March). Semantically enhanced user modeling. In Proceedings of the 2007 ACM symposium on Applied computing (pp. 1335-1339). ACM.

Mehrazarin, S., Alyoubi, Y., & Alyoubi, A. (2015). EnaCloud: An Energy-saving Application Live Placement Approach for Cloud Computing Environments.

Mahtab, A. (2013). Privacy Preserving Data-as-a-Service Mashups (Doctoral dissertation, Concordia University).

Zhao, F., Li, C., & Liu, C. F. (2014, February). A cloud computing security solution based on fully homomorphic encryption. In Advanced Communication Technology (ICACT), 2014 16th International Conference on (pp. 485-488). IEEE.

Katz, J., Sahai, A., & Waters, B. (2008). Predicate encryption supporting disjunctions, polynomial equations, and inner products. Advances in Cryptology–EUROCRYPT 2008, 146-162.

Zhou, M., Mu, Y., Susilo, W., Au, M. H., & Yan, J. (2011, November). Privacy-preserved access control for cloud computing. In Trust, Security and Privacy in Computing and Communications (TrustCom), 2011 IEEE 10th International Conference on (pp. 83-90). IEEE.

Dinadayalan, P., Jegadeeswari, S., & Gnanambigai, D. (2014, February). Data security issues in cloud environment and solutions. In Computing and Communication Technologies (WCCCT), 2014 World Congress on (pp. 88-91). IEEE.

Li, W., & Ping, L. (2009). Trust model to enhance security and interoperability of cloud environment. Cloud Computing, 69-79.

Cao, N., Wang, C., Li, M., Ren, K., & Lou, W. (2014). Privacy-preserving multi-keyword ranked search over encrypted cloud data. IEEE Transactions on parallel and distributed systems, 25(1), 222-233.

Kurdi, H., Al-Anazi, A., Campbell, C., & Al Faries, A. (2015). A combinatorial optimization algorithm for multiple cloud service composition. Computers & Electrical Engineering, 42, 107-113.

Hmood, A., Fung, B. C., & Iqbal, F. (2014, March). Privacy-Preserving Medical Reports Publishing for Cluster Analysis. In New Technologies, Mobility and Security (NTMS), 2014 6th International Conference on (pp. 1-8). IEEE.

Beloglazov, A., Abawajy, J., & Buyya, R. (2012). Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future generation computer systems, 28(5), 755-768.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.





Copyright © 2014 Penerbit UTM Press. Universiti Teknologi Malaysia. All rights reserved.

Mailing Address: Penerbit UTM Press, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia.