Securing Cloud Systems With Smart Authentication And Adaptive Encryption
DOI:
https://doi.org/10.63665/d67tnj81Keywords:
Cloud Computing, Multi-Factor Authentication, Hybrid Cryptography, Intrusion Detection System, Data Security, Fingerprint-Based AuthenticationAbstract
This study addresses the growing need for stronger security in cloud computing by proposing an advanced authentication framework. It combines multi-factor authentication—using passwords, conditional attributes, and fingerprint-based key generation—with a hybrid cryptographic system that dynamically changes encryption algorithms. The model integrates an intrusion detection system based on data mining to predict and classify threats. It employs multiple dual-encryption algorithm pairs to enhance security. The framework demonstrates strong resistance to various attacks, including brute force, spoofing, phishing, guessing, and impersonation. Overall, the approach improves data confidentiality and prevents unauthorized access in cloud environments through the integration of adaptive cryptography and multi-factor authentication.
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[1]. K. L. Chiew and B. Hui, “An Improved Network Intrusion Detection Method Based on CNN-LSTM-SA,” IEEE Access, vol. 13, pp. 14567–14579, 2025.
[2]. K. Latha and T. Sheela, “Block Based Data Security and Data Distribution on Multi Cloud Environment,” International Journal of Cloud Computing and Services Science, vol. 13, no. 2, pp. 95–104, 2024.
[3]. K. Rajeshkumar, S. Dhanasekaran, and V. Vasudevan, “A Novel Three-Factor Authentication and Optimal MapReduce Frameworks for Secure Medical Big Data Transmission Over the Cloud with SHAX-ECC,” Journal of Information Security and Applications, vol. 78, pp. 103621, 2024.
[4]. S. Khan and A. Mailewa, “Predicting Anomalies in Computer Networks Using Autoencoder-Based Representation Learning,” Computer Networks, vol. 245, pp. 110345, 2024.
[5]. D. Carrillo-Torres, J. A. Pérez-Díaz, J. A. Cantoral-Ceballos, and C. Vargas-Rosales, “A Novel Multi-Factor Authentication Algorithm Based on Image Recognition and User Established Relations,” IEEE Access, vol. 11, pp. 88754–88766, 2023.
[6]. D. V. K. Vengala, D. Kavitha, and A. S. Kumar, “Three Factor Authentication System with Modified ECC Based Secured Data Transfer: Untrusted Cloud Environment,” International Journal of Information Security and Privacy, vol. 17, no. 3, pp. 1–18, 2023.
[7]. G. Ramesh, J. Logeshwaran, and V. Aravindarajan, “A secured database monitoring method to improve data backup and recovery operations in cloud computing,” BOHR Int. J. Comput. Sci., vol. 2, no. 1, pp. 1–7, 2022, doi: 10.54646/bijcs.019.
[8]. B. T. Rao, “A study on data storage security issues in cloud computing,” Procedia Comput. Sci., vol. 92, pp. 128–135, 2016, doi: 10.1016/j.procs.2016.07.335.
[9]. K. Latha and T. Sheela, “Block based data security and data distribution on multi cloud environment,” J. Ambient Intell. Humanized Comput., vol. 15, 2024, Art. no. 53, doi: 10.1007/s12652-019-01395-y.
[10]. K. Raju and M. Chinnadurai, “An identity-based secure and optimal authentication scheme for the cloud computing environment,” Comput., Mater. Continua, vol. 69, no. 1, pp. 1057–1072, 2021, doi: 10.32604/cmc.2021.016068.
[11]. A. Ometov, S. Bezzateev, N. Mäkitalo, S. Andreev, T. Mikkonen, and Y. Koucheryavy, “Multi-factor authentication: A survey,” Cryptogr., vol. 2, no. 1, pp. 1–31, 2018, doi: 10.3390/cryptography2010001. [6] S. Sudha and S. S. Manikandasaran, “A survey on different authentication schemes in cloud computing environment,” Int. J. Manage., IT Eng., vol. 9, no. 1, pp. 359–375, 2019.
[12]. A. Alhothaily, C. Hu, A. Alrawais, T. Song, X. Cheng, and D. Chen, “A secure and practical authentication scheme using personal devices,” IEEE Access, vol. 5, pp. 11677–11687, 2017, doi: 10.1109/ACCESS.2017.2717862.
[13]. N. Anusha and N. R. Suma, “A review on secured file system using multi-factor authentication with visual cryptography for cloud environment,” Int. Res. J. Modernization Eng. Technol. Sci., vol. 4, no. 6, pp. 4433–4436, 2012.
[14]. Cybersecurity, “What is password encryption and how does it work,” Accessed: Jun. 15, 2023. [Online]. Available: https://teampassword. com/blog/what-is-password-encryption-and-how-much-is-enough
[15]. M. Hazratifard, F. Gebali, and M. Mamun, “Using machine learning for dynamic authentication in telehealth: A tutorial,” Sensors, vol. 22, no. 19, 2022, Art. no. 7655, doi: 10.3390/s22197655.
[16]. N. Siddiqui, L. Pryor, and R. Dave, “User authentication schemes using machine learning methods—A review,” in Proc. Int. Conf. Commun. Comput. Technol., Singapore, 2021, pp. 703–723, doi: 10.1007/ 978-981-16-3246-4_54.
[17]. T. N. Tan and H. Lee, “High-secure fingerprint authentication system using ring-LWE cryptography,” IEEE Access, vol. 7, pp. 23379–23387, 2019, doi: 10.1109/ACCESS.2019.2899359.
[18]. C. Singh and D. Singh, “A 3-level multifactor authentication scheme for cloud computing,” Int. J. Comput. Eng. Technol., vol. 10, no. 1, pp. 184–195, 2019. [Online]. Available: https://ssrn.com/abstract= 3537621
[19]. S. A. Sagar, O. Bhat, M. Raina, and S. Patil, “Authentication system using cryptographic secure password storage,” Int. J. Innov. Res. Eng. Multidisciplinary Phys. Sci., vol. 6, no. 6, pp. 76–78, 2018.
[20]. V. Kakkad, M. Patel, and M. Shah, “Biometric authentication and image encryption for image security in cloud framework,” Multiscale Multidisciplinary Model., Exp. Des., vol. 2, no. 4, pp. 233–248, 2019, doi: 10.1007/s41939-019-00049-y.
[21]. M. Obaidat, J. Brown, S. Obeidat, and M. Rawashdeh, “A hybrid dynamic encryption scheme for multi-factor verification: A novel paradigm for remote authentication,” Sensors, vol. 20, no. 5, 2020, Art. no. 4212, doi: 10.3390/s20154212.
[22]. M. A. Khan, M. T. Quasim, N. S. Alghamdi, and M. Y. Khan, “A secure framework for authentication and encryption using improved ECC for IoT-based medical sensor data,” IEEE Access, vol. 8, pp. 52018–52027, 2020, doi: 10.1109/ACCESS.2020.2980739.
[23]. K. DeviPriya and S. Lingamgunta, “Multi factor two-way hash-based authentication in cloud computing,” Int. J. Cloud Appl. Comput., vol. 10, no. 2, 2020, Art. no. 21, doi: 10.4018/IJCAC.2020040104.
[24]. K. M. Prabha and P. V. Saraswathi, “Suppressed K-anonymity multifactor authentication based Schmidt-Samoa cryptography for privacy preserved data access in cloud computing,” Comput. Commun., vol. 158, pp. 85–94, 2020, doi: 10.1016/j.comcom.2020.04.057.
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