Abstract
Cloud computing is defined as the distribution of computing including hardware and software to the consumer through the Internet. In the era of ICT, cloud computing has been influenced by many industries including technology, business, management, logistics and numerous other industry. But some new kinds of risks and vulnerabilities exist in cloud environment. Users of cloud services are under constant threat. Hence, security-related risks are the main disadvantage of cloud computing. The aim of this paper is to enhance the cloud security by designing a secure cryptosystem based on AI. We have emphasized on secure key generation algorithm based on coupled artificial neural network with Mealy machine, genetic algorithm and weight vector-based authentication mechanism. We have used coupled multilayer feedforward neural network, Mealy machine and genetic algorithm for key generation. Machine learning is done ‘n’ times between two ANNs, and after several steps, we have generated a secret key for encryption. A novel key wrapping protocol has also been introduced using one-way function. For encryption and decryption, we have used the concept of isomorphism in vector space and XOR operation with double encryption key. Thus, our paper is equipped with different types of new concepts. Varieties of experimental results and analysis prove the efficiency and robustness of our technique in the field of cryptography.
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References
Michalski R, Carbonell J, Mitchell T (2013) Machine learning: an artificial intelligence approach. Springer Science & Business Media, Cham
Dhamija A, Dhaka V (2015) A novel cryptographic and steganographic approach for secure cloud data migration. In: International conference green computing and internet of things (ICGCIoT). pp 346–351
Haykin S (2009) Neural networks: a comprehensive foundation, 2nd edn. Prentice Hall, New Jersey
Dhivya R, Dharshana R, Divya V (2019) Security attacks detection in cloud using machine learning algorithms. Int Res J Eng Technol (IRJET) 6(2):223–230
Kaur K, Zandu V (2016) A secure data classification model in cloud computing using machine learning approach. Int J Grid Distrib Comput 9(8):13–22. https://doi.org/10.14257/ijgdc.2016.9.8.02
Goswani B, Singh DS (2012) Enhancing security in cloud computing using public key cryptography with matrices. Int J Eng Res Appl 2(4):339–344
Tebaa M, Hajii SE (2013) Secure cloud computing through homomorphic encryption. Int J Adv Comput Technol (IJACT) 5
Gander M, Katt B, Felderer M, Tolbaru A, Breu R, Moschitti A (2012) Anomaly detection in the cloud: detecting security incidents via machine learning
Jegadeeswari S, Dinadayalan P, Gnanambigai N (2016) Enhanced data security using neural network in cloud Environment. 11:278-285
Pallavi DB, Shaikh MZ (2019) Machine learning: survey, types and challenges. Int Res J Eng Technol (IRJET) 06(3)
Moghaddam FF, Vala M, Ahmadi M, Khodadadi T, Madadipouya K (2015) A reliable data protection model based on Encryption Concepts in cloud environments. In: 2015 IEEE 6th control and system graduate research colloquium (ICSGRC). pp 11–16
Yang C, Huang Q, Li Z, Liu K, Fei Hu (2017) Big data and cloud computing: innovation opportunities and challenges. Int J Digit Earth 10(1):13–53. https://doi.org/10.1080/17538947.2016.1239771
Sharma S (2017) Enhance data security in cloud computing using machine learning and hybrid cryptography techniques. Int J Adv Res Comput Sci IJARCS 8(9):393–397
Sun Y, Zhang J, Xiong Y, Zhu G (2014) Data security and privacy in cloud computing. Int J Distrib Sens Netw. https://doi.org/10.1155/2014/190903
Sundharakumar KB, Dhivya S, Mohanavalli S, Vinob Chander R (2015) Cloud based fuzzy healthcare system. Procedia Comput Sci. https://doi.org/10.1016/j.procs.2015.04.076
Verma OP, Nitn J, Saibal KP, Bharti M (2015) Artificial intelligence and network security. In: Bilingual international conference on information technology. DRDO, India, ISBN: 9678-81-86514-73-3, pp 92–96 © DESIDOC
Hariss K, Noura H, Samhat AE (2020) An efficient fully homomorphic symmetric encryption algorithm. Multimed Tools Appl 79:12139–12164. https://doi.org/10.1007/s11042-019-08511-2
Li S, Zhou S, Dou J et al (2020) Polynomial AND homomorphic cryptosystem and applications. Sci China Inf Sci 63:112105. https://doi.org/10.1007/s11432-018-9789-y
Smart NP, Vercauteren F (2014) Fully homomorphic SIMD operations. Des Codes Cryptogr 71(1):57–81
Al-Khateeb B, Mahmood M, Alwash WM (2019) Review of neural networks contribution in network security. J Adv Res Dyn Control Syst
Gentry C, Halevi S (2011) Implementing Gentry’s fully homomorphic encryption scheme. In: Paterson K (ed) EURO-CRYPT2011. LNCS, Springer, Cham
Ducas L, Micciancio D (2015) FHEW: bootstrapping homomorphic encryption in less than a second. In: Oswald E, Fischlin M (ed.), Advances in cryptology - EUROCRYPT 2015 - 34th annual international conference on the theory and applications of cryptographic techniques, So a, Bulgaria, April 26–30, 2015, Proceedings, Part I, volume 9056 of Lecture Notes in Computer Science. Springer, pp 617–640
Hitaswi N, Chandrasekaran K (2016) A bio-inspired model to provide data security in cloud storage. 203–208. https://doi.org/10.1109/INCITE.2016.7857617
Srimani P, Nasir S (2007) A textbook on automata theory. Foundation Books, West Conshohocken
Almorsy M, Grundy J, Ibrahim AS (2011) Collaboration- based cloud computing security management framework. In: IEEE conference of cloud computing, Washington (DC), pp 364–371
Wu Y, Noonan JP, Yang G, Jin H (2012) Image encryption using the two-dimensional logistic chaotic map. J Electron Imaging 21(1):013014. https://doi.org/10.1117/1.JEI.21.1.013014
Ghosh P, Hasan M, Atik S, Jabiullah MdI (2019) A variable length key based cryptographic approach on cloud data. 285–290. https://doi.org/10.1109/ICIT48102.2019.00057
Ganesan P, Priyanka BR, Sheikh M, Murthy DHR, Patra GK (2017) A secure key exchange protocol using link weights and dynamic tree parity machine (TPM). ACCENTS Trans Inf Secur 2(8):78–81. https://doi.org/10.19101/TIS.2017.28001
Chakravorty JG, Ghosh PR (2018) Advanced higher algebra. U.N. Dhur and Sons Private Ltd., Kolkata
Harfoushi O, Obiedat R (2018) Security in cloud computing using hash algorithm: a neural cloud data security model. Mod Appl Sci 12:143. https://doi.org/10.5539/mas.v12n6p143
Hassan W, Chou TS, Tamer O, Pickard J, Appiah-Kubi P, Pagliari L (2020) Cloud Computing survey on services, enhancements and challenges in the era of machine learning and data science. Int J Inf Commun Technol (IJ-ICT) 9(2):117–139. https://doi.org/10.11591/ijict.v9i2.pp117-139
Omotunde AA, Awodele O, Kuyoro SO, Ajaegbu C (2013) Survey of cloud computing issues at implementation level. J Emerg Trends Comput Inf Sci 4(1):91–96
Sharma R, Gourisaria MK, Patra SS (2021) Cloud computing—security, issues, and solutions. In: Satapathy SC, Bhateja V, Ramakrishna Murty M, Gia Nhu N, Jayasri K (eds) Communication software and networks. Lecture notes in networks and systems. Springer, Singapore
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Bhowmik, A., Karforma, S. Isomorphic encryption and coupled ANN with Mealy machine: a cutting edge data security model for cloud computing environment. Knowl Inf Syst 65, 133–162 (2023). https://doi.org/10.1007/s10115-022-01760-y
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DOI: https://doi.org/10.1007/s10115-022-01760-y