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Development of Blowfish Encryption Scheme for Secure Data Storage in Public and Commercial Cloud Computing Environment

Shafi’i Muhammad Abdulhamid*, Nafisat Abubakar Sadiq**, Abdullahi Mohammed ***, Nadim Rana****, Haruna Chiroma*****, Emmanuel Gbenga Dada ******

* Senior Lecturer and Head, Department of Cyber Security Science, Federal University of Technology Minna, Nigeria.

** Graduate, Department of Computer Science, Federal University of Technology (FUT), Minna, Nigeria.

*** Lecturer, Department of Computer Science, Ahmadu Bello University Zaria-Nigeria.

**** Senior Lecturer, College of Computer Science and Information Systems, Jazan University, Jazan, Kingdom of Saudi Arabia.

***** Senior Lecturer, Department of Computer Science, Federal College of Education (Technical), Gombe, Nigeria.

****** Faculty, Department of Computer Engineering, University of Maiduguri, Maiduguri, Nigeria.

Periodicity:July - December'2018
DOI : https://doi.org/10.26634/jcc.5.2.15690

Abstract

Cloud computing is defined as the delivery of on-demand computing resources ranging from infrastructure application to datacenter over the internet on a pay-per-use basis. Most cloud computing applications does not guarantee high level security, such as privacy, confidentiality, and integrity of data because of third-party transition. This brings the development of Blowfish cloud encryption system that enables them to encrypt their data before storage in the cloud. Blowfish encryption scheme is a symmetric block cipher used to encrypt and decrypt data. Microsoft Azure cloud server was used to test the proposed encryption system. Users are able to encrypt their data and obtain a unique identification to help them retrieve encrypted data from the cloud storage facility as and when needed.

Keywords

Blowfish Encryption, Cryptography, Cloud Computing, Data Storage, Encryption Scheme

How to Cite this Article?

Abdulhamid, S. M., Sadiq, N. A., Abdullahi, M., Rana, N., Chiroma, H., Dada, E.G (2018). Development of Blowfish Encryption Scheme for Secure Data Storage in Public and Commercial Cloud Computing Environment, i-manager's Journal on Cloud Computing 5(2), 1-10. https://doi.org/10.26634/jcc.5.2.15690

References

[1]. Abdullahi, M., & Ngadi, M. A. (2016). Symbiotic Organism Search optimization based task scheduling in cloud computing environment. Future Generation Computer Systems, 56, 640-650.

[2]. 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.

[3]. Chaplot, V. (2015). Databases Management Systems (DBMS). International Education and Research Journal (IERJ), 1(2), 24-25.

[4]. Curino, C., Jones, E. P., Popa, R. A., Malviya, N., Wu, E., Madden, S., & Zeldovich, N. (2011). Relational cloud: A database-as-a-service for the cloud. Information Applications, 1(1), 235-240.

[5]. Gahi, Y., Guennoun, M.., & Khatib, K. E (2000). A secure database system using Homomorphic Encryption Schemes. DBKDA 2011: The Third International Conference on Advances in Databases, Knowledge, and Data Applications (pp. 54-58).

[6]. Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Abdullah, G., & Khan, S. U. (2015). The rise of big data on cloud computing: Review and open research issues. Information Systems, 47(7), 98-115. https://doi.org/ 10.1016/j.is.2014.07.006

[7]. Hoang, V. T., Katz, J., & Malozemof, A. J. (2015). Automated analysis and synthesis of authenticated encryption schemes. IET Technology Security, 3(1), 1-31.

[8]. Itani, W., Kayssi, A., & Chehab, A. (2009). Privacy as a Service: Privacy-Aware Data Storage and Processing in Cloud Computing Architectures. IEEE International Conference on Dependable, Autonomic and Secure Computing, (Vol. 3, No. 5, pp. 711-716) https://doi.org/ 10.1109/DASC.2009.139

[9]. Kaur, M., & Singh, R. (2013). Implementing encryption algorithms to enhance data security of cloud in cloud computing. International Journal of Computer Applications, 70(18), 16-21.

[10]. Krishnamurthy, G. N., Ramaswamy, V., Leela. G. H., & Ashalatha, M. E (2008). Blow-CAST-Fish: A new 64-bit block cipher. International Journal of Computer Science and Network Security (IJCSNS), 8(4), 282-290.

[11]. Latiff, M. S. A., Abdul-Salaam, G., & Madni, S. H. H. (2016). Secure scientific applications scheduling technique for cloud computing environment using global league championship algorithm. PloS One, 11(7), 158102.

[12]. Latiff, M. S. A., Madni, S. H. H., & Abdullahi, M. (2018). Fault tolerance aware scheduling technique for cloud computing environment using dynamic clustering algorithm. Neural Computing and Applications, 29(1), 279-293.

[13]. Lee, C. C., Chung, P. S., & Hwang, M. S. (2013). A survey on attribute-based encryption schemes of access control in cloud environments. IJ Network Security, 15(4), 231-240.

[14]. Li, M., Yu, S., Cao, N., & Lou, W. (2011, June). Authorized private keyword search over encrypted data in cloud computing. In Distributed Computing Systems (ICDCS), 2011 31^stInternational Conference on (pp. 383- 392). IEEE.

[15]. Madni, S. H. H., Latiff, M. S. A., Abdullahi, M., & Usman, M. J. (2017). Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment. PloS One, 12(5), e0176321.

[16]. Madni, S. H. H., Latiff, M. S. A., & Coulibaly, Y. (2017). Recent advancements in resource allocation techniques for cloud computing environment: A systematic review. Cluster Computing, 20(3), 2489-2533.

[17]. Rittinghouse, J. W., & Ransome, J. F. (2016). Cloud Computing: Implementation, Management, and Security. CRC Press.

[18]. Said, A. (2005, September). Measuring the strength of partial encryption schemes. In Image Processing, 2005. ICIP 2005. IEEE International Conference on (Vol. 2, pp. 1126-1129). IEEE.

[19]. Schneier, B. (n.d). The Blowfish Encryption Algorithm [Blogpost]. Retrieved from https://www.schneier.com/ academic/blowfish/

[20]. Singh, P., & Singh, K. (2013). Image encryption and decr yption using blowfish algorithm in Matlab. International Journal of Scientific & Engineering Research, 4(7), 150-154.

[21]. Thakur, J., & Kumar, N. (2011). DES, AES and Blowfish: Symmetric key cryptography algorithms simulation based performance analysis. International Journal of Emerging Technology and Advanced Engineering, 1(2), 6-12.

[22]. Xia, Z., Wang, X., Sun,X., & Wang, Q (2016) A secure and dynamic multi-keyword ranked search scheme over encrypted cloud data. In IEEE Transactions on Parallel and Distributed Systems, 27(2), 340-352. doi: 10.1109/TPDS.2015.2401003

Development of Blowfish Encryption Scheme for Secure Data Storage in Public and Commercial Cloud Computing Environment

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