International Journal of Intelligent Systems and Applications(IJISA)

ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)

Published By: MECS Press

IJISA Vol.12, No.6, Dec. 2020

Improving Cloud Data Encryption Using Customized Genetic Algorithm

Full Text (PDF, 611KB), PP.46-63

Views:1   Downloads:1


Muhammad Junaid Arshad, Muhammad Umair, Saima Munawar, Nasir Naveed, Humaira Naeem

Index Terms

Genetic Algorithm;Artificial Intelligence;Local System;Encryption Key;Customized Algorithm;Fully Homomorphic Encryption


Data Encryption is widely utilized for ensuring data privacy, integrity, and confidentiality. Nowadays, a large volume of data is uploaded to the cloud, which increases its vulnerability and adds to security breaches. These security breaches include circumstances where sensitive information is being exposed to third parties or any access to sensitive information by unauthorized personnel. The objective of this research is to propose a method for improving encryption by customizing the genetic algorithm (GA) with added steps of encryption. These added steps of encryption include the data being processed with local information (chromosome's value calculated with computer-generated random bits without human intervention). The improvement in the randomness of the key generated is based on altering the population size, number of generations, and mutation rate. The first step of encrypting is to convert sample data into binary form. Once the encryption process is complete, this binary result is converted back to get the encrypted data or cipher-text. Foremost, the GA operators (population size, number of generations, and mutation rate) are changed to determine the optimal values of each operator to bring forth a random key in the minimum possible time, then local intelligence is headed in the algorithm to further improve the outcomes. Local Intelligence consists of local information and a random bit generated in each iteration. Local Information is the current value of a parent in each iteration at the gene level. Both local information and random bit are then applied in a mathematical pattern to generate a randomized key. The local intelligence-based algorithm can operate better in terms of time with the same degree of randomness that is generated with the conventional GA technique. The result showed that the proposed method is at least 80% more efficient in terms of time while generating the secret key with the same randomness level as generated by a conventional GA. Therefore, when large data are intended to be encrypted, then using local intelligence can demonstrate to be better utilized time. 

Cite This Paper

Muhammad Junaid Arshad, Muhammad Umair, Saima Munawar, Nasir Naveed, Humaira Naeem, "Improving Cloud Data Encryption Using Customized Genetic Algorithm", International Journal of Intelligent Systems and Applications(IJISA), Vol.12, No.6, pp.46-63, 2020. DOI: 10.5815/ijisa.2020.06.04


[1]Remzi G., Mevlüt E. (2020). A New Hybrid Encryption Approach for Secure Communication: GenComPass. International Journal of Computer Network and Information Security (IJCNIS), Vol.12, No.4, pp.1-10, DOI: 10.5815/ijcnis.2020.04.01

[2]Amin R., Hamed N., Mohammad J. A. (2020). Reducing Energy Consumption in Wireless Sensor Networks Using a Routing Protocol Based on Multi-level Clustering and Genetic Algorithm. International Journal of Wireless and Microwave Technologies (IJWMT), Vol.10, No.3, pp. 1-16. DOI: 10.5815/ijwmt.2020.03.01

[3]Pavan S. D. N., Narayan H., Rajashree S., Shankru G., Umadevi V. (2020). Ferrer diagram based partitioning technique to decision tree using genetic algorithm. International Journal of Mathematical Sciences and Computing (IJMSC), Vol.6, No.1, pp.25-32, DOI: 10.5815/ijmsc.2020.01.03

[4]Abdallah, A. M., Ibrahim M. M. (2019). Text Encryption Using Genetic Algorithm. International Journal of Computer Science and Network (IJCSN), 8(1), 36-39.

[5]Agbedemnab, P. A., Baagyere, E. Y. & Daabo, M. I. (2019). A Novel Text Encryption and Decryption Scheme using the Genetic Algorithm and Residual Numbers. Proceedings of 4th International Conference on the Internet, Cyber Security and Information Systems (ICICIS), 12, 20-31.

[6]Mehdi J. M., Safaa S. M., Esraa Y. T. (2019). Intelligent Control for a Swarm of Two Wheel Mobile Robot with Presence of External Disturbance. International Journal of Modern Education and Computer Science (IJMECS), Vol.11, No.11, pp. 7-12, DOI: 10.5815/ijmecs.2019.11.02

[7]Ramli, S. N., Chuah, C. W., Foozy, C. F. (2019). Enhancing the Randomness of Symmetric Key Using Genetic Algorithm. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(8S), 327-330.

[8]Mittal, A., Gupta, R. K. (2019). Encryption and Decryption of a Message Involving Genetic Algorithm. International Journal of Engineering and Advanced Technology (IJEAT), 9(2), 2249 – 8958.

[9]Rodríguez, J., Corredor, B. & Suárez, C. (2019). Genetic Operators Applied to Symmetric Cryptography. International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI). IP. 1. 10.9781/ijimai.2019.07.006.

[10]Ding, Y., Wang, A., & Yiu, S. (2019). An Intelligent Multiple Sieve Method Based on Genetic Algorithm and Correlation Power Analysis. IACR Cryptology ePrint Archive, 2019, 189.

[11]Ferdush, J., Mondol, G., Prapti, A. P., Begum, M., Sheikh, M. N. A., & Galib, S. M. (2019). An enhanced image encryption technique combining genetic algorithm and particle swarm optimization with chaotic function. International Journal of Computers and Applications. doi:10.1080/1206212X.2019.1662170.

[12]Malik, A. (2019). A Study of Genetic Algorithmand Crossover Techniques. International Journal of Computer Science and Mobile Computing (IJCSMC), 8(3), 335-344.

[13]Nazeer, M. I., Mallah, G. A., & Shaikh, N. A. (2018). Implication of Genetic Algorithm in Cryptography to Enhance Security. International Journal of Advanced Computer Science and Applications (IJACSA), 9(6), 375-379. 

[14]Hamdy M. M. (2019). Bat-Genetic Encryption Technique. International Journal of Intelligent Systems and Applications (IJISA), Vol.11, No.11, pp.1-15, DOI: 10.5815/ijisa.2019.11.01

[15]Alkharji, M., Al Hammoshi, M., Hu, C., & Liu, H. (2017). Genetic Algorithm based key Generation for Fully Homomorphic Encryption. In Proceedings of 16th Annual Security Conference.

[16]Dubey S., Jhaggar R., Verma, R. & Gaur D. (2017). Encryption and Decryption of Data by Genetic Algorithm. International Journal of Scientific Research in Computer Science and Engineering (IJSRCSE), 5(3), 47-52.

[17]Saini, N. (2017). Review of Selection Methods in Genetic Algorithms. International Journal Of Engineering And Computer Science (IJECS), 6(12), 22261-22263.

[18]Alkharji, M., Liu, H., & Washington, C. U. A. (2016). Homomorphic Encryption Algorithms and Schemes for Secure Computations in the Cloud. In Proceedings of 2016 International Conference on Secure Computing and Technology.

[19]Gavinho Filho, J., Silva, G. P., & Miceli, C. (2016). A public key compression method for Fully Homomorphic Encryption using Genetic Algorithms. 19th International Conference on Information Fusion (FUSION), 1991-1998.

[20]Gjøsteen, K., & Strand, M. (2016). Can there be efficient and natural FHE schemes. IACR Cryptology ePrint Archive, 2016, 105.

[21]Chowdhury, S., Das, S. K., & Das, A. (2015). Application of Genetic Algorithm in Communication Network Security. International Journal of Innovative Research in Computer and Communication Engineering, 3(1), 274-280.

[22]Jawaid, S., Saiyeda, A., & Suroor, N. (2015). Selection of Fittest Key Using Genetic Algorithm and Autocorrelation in Cryptography. Journal of Computer Sciences and Applications, 3(2), 46-51.

[23]Jhingran, R., Thada, V., & Dhaka, S. (2015). A Study on Cryptography using Genetic Algorithm. International Journal of Computer Applications. 118, 10-14, doi:10.5120/20860-3559.

[24]Dutta, S., Das, T., Jash, S., Patra, D., & Paul, P. (2014). A Cryptography Algorithm Using the Operations of Genetic Algorithm & Pseudo Random Sequence Generating Functions. International Journal of Advances in Computer Science and Technology (IJACST), 3, 325-330.

[25]Hassan, A. S. O., Shalash, A. F. & Saudy, N. F. (2014). Modifications on RSA Cryptosystem Using Genetic Optimization. International Journal of Research and Reviews in Applied Sciences (IJRRAS), 19(2), 150-155.

[26]Jawaid, S., & Jamal, A. (2014). Generating the Best Fit Key in Cryptography using Genetic Algorithm. International Journal of Computer Applications (IJCA), 98, 0975 – 8887. doi:10.5120/17301-7767

[27]Naik, P. G., & Naik G. R.  (2014). Asymmetric Key Encryption using Genetic Algorithm.  International Journal of Latest Trends in Engineering and Technology (IJLTET), 3, doi:10.13140/2.1.3621.0889

[28]Sindhuja, K., & Pramela, D. S. (2014). A Symmetric Key Encryption Technique Using Genetic Algorithm. International Journal of Computer Science and Information Technologies (IJCSIT), 5 (1), 414-416, ISSN: 0975-9646.

[29]Mishra, S., & Bali, S. (2013). Public Key Cryptography Using Genetic Algorithm.  International Journal of Recent Technology and Engineering (IJRTE), 2, 150-54.

[30]Soni, A., & Agrawal, S. (2013). Key Generation Using Genetic Algorithm for Image Encryption. International Journal of Computer Science and Mobile Computing (IJCSMC), 2, 376 – 383.

[31]Almarimi, A., KUMAR, A., ALMERHAG, I., & ELZOGHBI, N. (2012). A new approach for data encryption using genetic algorithms. Adv Intell Syst Comput, 167, 783-791.

[32]Sandeep, B., & Sriyankar, A. (2011). Image cryptography: The genetic algorithm approach. International Conference on Computer Science and Automation Engineering, Shanghai, 223-227. doi:10.1109/CSAE.2011.5952458

[33]Gentry, C., & Boneh, D. (2009). A fully homomorphic encryption scheme 20(09). Stanford: Stanford University.

[34]Gentry, C. (2009b). Fully homomorphic encryption using ideal lattices. Proceedings of the forty-first annual ACM symposium on Theory of computing Bethesda, USA, 169–178. doi:10.1145/1536414.1536440

[35]Tragha A., Omary F., Mouloudi A., (2006). ICIGA: Improved Cryptography Inspired by Genetic Algorithms. Proceedings of the International Conference on Hybrid Information Technology (ICHIT’06), 335-341.

[36]Tragha, F. Omary, A. Kriouile, (2005). Genetic Algorithms Inspired Cryptography. Association for the Advancement of Modelling & Simulation Techniques in Entreprises A.M.S.E, Series D: Computer Science and Statistics, November 2005

[37]Gong, M., & Yang, Y. (2004). Quadtree-based genetic algorithm and its applications to computer vision. Pattern Recognition, 37, 1723-1733.

[38]Westlund, H. B. (2002). NIST reports measurable success of Advanced Encryption Standard. Journal of Research of the National Institute of Standards and Technology.

[39]Mitchell, M. (1996). An Introduction to Genetic Algorithms. Cambridge, MA: MIT Press. ISBN 9780585030944.

[40]Rivest, R. L., Adleman, L. & Dertouzos, M. L. (1978). On Data Banks and Privacy Homomorphisms. Foundations of Secure Computation, Academia Press, 169-179. 

[41]Rivest R. L., Shamir A., and Adleman L., (1978). A method for obtaining digital signatures and public key cryptosystems, Communications of the ACM, 21(2), 120-126. doi:10.1145/357980.358017. 

[42]National Bureau Standards, (1977) Data Encryption Standard (DES). FIPS Publication 46.

[43]Diffie, W., Hellman, M. (1976). Multi-user cryptographic techniques. AFIPS Proceedings. 45: 109–112.