Enhancing Data Security in Cloud Computing Environments

Cloud computing has emerged as a pillar of the contemporary digital infrastructure, with the capacity to scale, low costs, and the ability to access data and services everywhere. Nevertheless, the sheer embrace of cloud platforms has come with a major challenge pertaining to the issue of data security, privacy and trust. The current paper outlines a more detailed method of how to improve data protection in the cloud computing setting, entailing the combination of sophisticated cryptographic algorithms, intelligent access control systems, and the use of AI and detector models. The framework proposed covers such key security issues as unauthorized access, data leakage, data breaches, and insider threats. The paper identifies encryption schemes such as symmetric and asymmetric cryptography, homomorphic encryption and secure multi-party computation, as the means to maintain the confidentiality of data stored and relayed. Also, the role-based access control (RBAC) and attribute-based access control (ABAC) models are included to implement fine-grained authorization policies. To build on this added protection, blockchain is proposed to audit data using secure and tamper-proof demonstrations, increasing transparency and accountability to the cloud systems. An important work in this regard is the incorporation of machine learning and artificial intelligence algorithms in real- time threat detection and tracking of anomalies. These models process high-traffic volumes of network traffic and user behavior patterns in order to proactively predict potential security threats and prevent attacks including the Distributed Denial of Service (DDoS), phishing and malware injections. The data integrity verification based on the use of hashing techniques and digital signatures is also a priority in the proposed system. The experimental findings indicate that the proposed scheme is significantly effective in enhancing the metrics of data security, such as low chances of breach, improved detection rates, and less time taken to respond to threats as compared to the traditional methods of security. Also, the framework will guarantee the adherence to data protection policies and assist in achieving cloud security on the multi-cloud environment data sharing. Finally, this study suggests that a multi-layered security approach that uses a combination of encryption, access control, blockchain, and AI-based monitoring are essential in protecting Identify applicable funding agency here. If none, delete this. sensitive data in cloud computing. The next-generation work will aim to enhance computational overhead optimization, scalability, and investigate quantum-resistant cryptographic methods to meet new security demands in the next-generation cloud infrastruc- ture.