PROVIDING SECURITY AND CLUSTERING FOR BIG DATA IN CLOUD

Managing big data in cloud environments requires a combination of strong security measures and efficientclustering techniques. With the increasing volume of sensitive data being processed, ensuring securestorage, retrieval, and management is essential. Advanced cryptographic methods can protect data fromunauthorized access, while machine learning algorithms improve clustering accuracy and efficiency. Byintegrating these technologies, cloud infrastructures can enhance both security and performance, reducingvulnerabilities and optimizing resource allocation. Businesses and organizations relying on cloud platformsneed robust mechanisms to safeguard their data while maintaining operational efficiency. Efficientclustering techniques help in organizing and processing large datasets, making data management moreeffective. Secure cloud based operations ensure compliance with regulatory standards and protect againstcyber threats. Implementing scalable security frameworks strengthens data confidentiality, integrity, andavailability. Leveraging AI-driven models for anomaly detection further enhances security within cloudenvironments. The proposed system will integrate security and clustering by using encrypted data storagecombined with machine learning-based data clustering within a cloud environment.