Data Encryption Algorithms and Risk Management

Abstract: In today's digital era, data is increasingly viewed as the new "green gold," making robust information security more critical than ever. This research investigates modern encryption algorithms alongside comprehensive risk management strategies to protect enterprise data. By systematically comparing symmetric, asymmetric, and hash-based encryption methods, the study reveals the inherent trade-offs between computational performance and security. A multifaceted methodology—combining literature review, algorithmic evaluation, multivariate risk assessment, and real-world case studies—is employed to examine advanced encryption techniques such as Twofish, RC6, AES, RSA, and ECC. Additionally, emerging challenges, including the threats posed by quantum computing and the energy constraints of IoT and cloud environments, are discussed. The findings underscore the necessity of a balanced encryption strategy integrated with robust risk management practices to ensure the confidentiality, integrity, and availability of sensitive information. The paper concludes with recommendations for future research and practical applications aimed at enhancing data protection in an ever-evolving digital landscape.

Data Encryption, Risk Management, Symmetric Encryption, Cryptographic Hash Functions, Advanced Encryption Algorithms, Asymmetric Encryption, Quantum Cryptography, IoT Security, Cloud Security, Multivariate Risk Assessment

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