Exploring Privacy-Preserving Strategies: A Comprehensive Analysis of Group-Based Anonymization and Hybrid ECC Encryption Algorithm for Effective Performance Evaluation in Data Security
Keywords:
Privacy Preserving, Data Security, Anonymization, CryptographyAbstract
As data security continues to change quickly, protecting privacy has become more important than ever. This paper explores privacy-preserving tactics and provides a thorough examination of two essential methods: Encryption Algorithm for Hybrid Elliptic Curve Cryptography (ECC) with Group-Based Anonymization. Presenting a useful framework for data security performance evaluation is the main objective. Group-Based Anonymization preserves anonymity while retaining data utility by grouping individuals together under the tenet of collective identity preservation. The programme uses an advanced grouping technique to provide the best possible trade-off between data usability and privacy protection. The paper focus on strong cryptographic solution that combines the advantages of symmetric and asymmetric encryption is the Hybrid ECC Encryption Algorithm. This hybrid solution solves the computational issues related to conventional ECC methods while simultaneously improving data transfer security. Important parameters including attack resistance, communication overhead, and computational efficiency are included in the performance evaluation. The paper aims to provide insights into the advantages and disadvantages of each technique by carefully examining these factors. This study adds to the current conversation about privacy and data security by offering a sophisticated insight into the complex interactions between hybrid ECC encryption and group-based anonymization. Adopting such extensive privacy-preserving methods becomes essential for protecting sensitive information in numerous fields, as data remains a crucial asset in the digital world.
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