The rapid growth of big data across industries has led to significant concerns regarding the security of sensitive information. As organizations store, transmit, and process massive volumes of data, ensuring the privacy, integrity, and confidentiality of this data becomes crucial. This paper explores scalable encryption algorithms designed to address the unique security challenges posed by big data environments. We examine various encryption techniques, including symmetric encryption algorithms such as AES, asymmetric encryption methods like RSA and ECC, as well as advanced encryption models such as homomorphic encryption and attribute-based encryption. Additionally, the paper delves into the scalability challenges associated with encrypting large datasets, focusing on computational efficiency, key management, and performance issues in big data contexts. Real-time encryption for secure transmission, as well as emerging trends like quantum-resistant encryption and AI-enhanced encryption processes, are also discussed. Through case studies, we highlight how scalable encryption is applied in sectors such as healthcare, finance, and IoT, underscoring the critical role of robust encryption in securing big data. The paper concludes with an analysis of current challenges and future directions for big data encryption, aiming to offer solutions to meet the growing demands of data security.
Asymmetric Encryption, Attribute-Based Encryption, Big Data, Scalable Encryption, Symmetric Encryption.
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