Enhancing Machine Learning Model Security in Private Cloud Environments through Cryptographic Techniques
Keywords:
Machine learning, Cloud Computing, Cryptography Algorithms, ClassifierAbstract
Cloud-based systems frequently encounter more serious security issues, especially when trying to secure stored information from harm. We present a model that acts as a barrier between users and cloud services, making use of modern techniques in machine learning for enhanced protection. Such a model is able to stop network attacks, identify different types of data and safeguard users’ information by applying various encryption algorithms based on its relevance. The Random Forest and Decision Tree methods are very accurate at identifying attacks with a score of over 98% and Logistic Regression also reaches or surpasses 98%. Important classified data in the cloud is secured using methods such as Twofish, Blowfish and the Advanced Encryption Standard (AES).
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Published on: 11-12-2025
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Copyright (c) 2025 Ayesha Siddiqui, Mohd Naved Ul Haq, Mohd Nafees
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