• N. Jayapandian



AES Algorithm, Big data, Cloud computing, Data Security, Data Storage, MHT Algorithm


Cloud computing is dealing with large amount of data during data communication. This data processing is named as big data. The big data is growth of the demand in accessing the storage, computation and communication. This big data has the major defects. A raising issue in emerging big data is cost minimization. The architecture of big data ranges over multiple machines and cluster which have sub system. The major challenge of this big data is pre-processing and analysing the data patterns. This research article is dealing with different data pre-processing and secure data storage. There are many research challenges during this data process. The possible gap and drawbacks in the technology are identified through this survey and the efficient big data service is provided through MHT and AES algorithm. The main aim of this proposed method is to provide better data security during larger data process. The proposed hybrid MHT with AES algorithm is to minimize the encryption and decryption time apart from that it reduces the attacker ratio. All these parameters automatically increase the Quality of Service.


A. Botta, W. de Donato,V. Persico, A. Pescapé, “Integration of cloud computing and internet of things: a survey,” Future Generation Computer Systems, vol. 56, issue 3, pp. 684-700, 2016.

N. Jayapandian, A. M. Z. Rahman, M. Koushikaa, S. Radhikadevi, “A novel approach to enhance multilevel security system using encryption with fingerprint in cloud,” Proceedings of the World IEEE Conference on Futuristic Trends in Research and Innovation for Social Welfare, Coimbatore, India, Feb 29, 2015, pp. 1-5.

A. Prakash, N. Navya, N. Jayapandian, “Big data preprocessing for modern world: Opportunities and challenges,” Proceedings of the International Conference on Intelligent Data Communication Technologies and Internet of Things, India, August 7, 2018, pp. 335-343.

G. Da Cunha Rodrigues, R.N. Calheiros, V.T. Guimaraes, G.L.D. Santos, M.B. De Carvalho, L.Z. Granville, L.M.R. Tarouco, R. Buyya, “Monitoring of cloud computing environments: concepts, solutions, trends, and future directions,” in Proceedings of the 31st Annual ACM Symposium on Applied Computing, April 4, 2016, pp. 378-383.

N. Jayapandian, A. M. J. Md Zubair Rahman, “Secure deduplication for cloud storage using interactive message-locked encryption with convergent encryption, to reduce storage space,” Brazilian Archives of Biology and Technology, vol. 61, issue 1, pp. 1-13, 2018.

A. Gani, A. Siddiqa, S. Shamshirband, F. Hanum, “A survey on indexing techniques for big data: taxonomy and performance evaluation,” Knowledge and information systems, vol. 46, issue 2, pp. 241-284, 2016.

M. N. Cheraghlou, A. Khadem-Zadeh, & M. Haghparast, “A survey of fault tolerance architecture in cloud computing,” Journal of Network and Computer Applications, vol. 61, issue 1, pp. 81-92, 2016.

J. Shuja, A. Gani, S. Shamshirband, R. W. Ahmad, & K. Bilal, “Sustainable cloud data centers: a survey of enabling techniques and technologies,” Renewable and Sustainable Energy Reviews, vol. 62, issue 1, pp. 195-214, 2016.

F. A. Alaba, M. Othman, I. A. T. Hashem, & F. Alotaibi, “Internet of Things security: A survey,” Journal of Network and Computer Applications, vol. 88, pp. 10-28, 2017.

M.B. Yassein, S. Aljawarneh, E. Qawasmeh, W. Mardini, & Y. Khamayseh, “Comprehensive study of symmetric key and asymmetric key encryption algorithms,” in Proceedings of the 2017 IEEE International conference on engineering and technology, Antalya, Turkey, Aug 21, 2017, pp. 1-7.

P. J. Stephenson, T. M. Brooks, S. H. Butchart, E. Fegraus, G. N. Geller, R. Hoft, L. McRae, “Priorities for big biodiversity data,” Frontiers in Ecology and the Environment, vol. 15, issue 3, pp. 124-125, 2017.

J. Wang, C. Liu, X. Fu, X. Luo, X. Li, “A three-phase approach to differentially private crucial patterns mining over data streams,” Computers & Security, vol. 82, pp. 30-48, 2019.

S. Hu, W. Bai, K. Chen, C. Tian, Y. Zhang, H. Wu, “Providing bandwidth guarantees, work conservation and low latency simultaneously in the cloud,” IEEE Transactions on Cloud Computing, 2019, doi: 10.1109/TCC.2018.2890252.

M. Du, Q. Wang, M. He, J. Weng, “Privacy-preserving indexing and query processing for secure dynamic cloud storage,” IEEE Transactions on Information Forensics and Security, vol. 13, issue 9, pp. 2320-2332, 2018.

Z. Zhang, P. Cheng, J. Wu, & J. Chen, “Secure State Estimation Using Hybrid Homomorphic Encryption Scheme,” IEEE Transactions on Control Systems Technology, 2020.

G. Bello-Orgaz, J. J. Jung, D. Camacho, “Social big data: Recent achievements and new challenges,” Information Fusion, vol. 28, pp. 45-59, 2016.

V. C. Storey, I. Y. Song, “Big data technologies and management: What conceptual modeling can do,” Data & Knowledge Engineering, vol. 108, pp. 50-67, 2017.

X. Jin, B. W. Wah, X. Cheng, Y. Wang, “Significance and challenges of big data research,” Big Data Research, vol. 2, issue 2, pp. 59-64, 2015.

E. Azhir, N. J. Navimipour, M. Hosseinzadeh, A. Sharifi, & A. Darwesh, “Query optimization mechanisms in the cloud environments: A systematic study,” International Journal of Communication Systems, vol. 32, issue 8, pp. 3940, 2019.

R. Sahal, J. G. Breslin, & M. I. Ali, “Big data and stream processing platforms for Industry 4.0 requirements mapping for a predictive maintenance use case,” Journal of Manufacturing Systems, vol. 54, pp. 138-151, 2020.

K. Hu, & G. Zeng, “Placing big graph into cloud for parallel processing with a two-phase community-aware approach,” Future Generation Computer Systems, vol. 101, pp. 1187-1200, 2019.

G. Iordache, “An Analysis of Service Level Agreement Parameters and Scheduling in Multi-Tenant Cloud Systems,” in Proceedings of the 22nd IEEE International Conference on Control Systems and Computer Science (CSCS), Bucharest, Romania, May 28-30, 2019, pp. 140-145.

N. Wang, M. Matthaiou, D. S. Nikolopoulos, & B. Varghese, “DYVERSE: DYnamic VERtical Scaling in multi-tenant Edge environments,” Future Generation Computer Systems, vol. 108, pp. 598-612, 2020.

Y. Lu, & X. Zheng, “6G: A survey on technologies, scenarios, challenges, and the related issues,” Journal of Industrial Information Integration, vol. 19, pp. 100158, 2020.

S. Farooq, & P. Chawla, “A novel approach of asymmetric key generation in symmetric AES via ECDH,” International Journal of System Assurance Engineering and Management, vol. 11, issue 5, pp. 962-971, 2020.

L. Zhou, J. Chen, Y. Zhang, C. Su, & M. A. James, “Security analysis and new models on the intelligent symmetric key encryption,” Computers & Security, vol. 80, 14-24, 2019.




How to Cite

Jayapandian, N. (2020). SECURING CLOUD DATA AGAINST CYBER-ATTACKS USING HYBRID AES WITH MHT ALGORITHM. International Journal of Computing, 19(4), 561-568.