A Scheduling Genetic Algorithm For Real-Time Data Freshness And Cloud Data Security Over Keywords Searching

Divya Surendran, Sasikala K


Cloud storage services allow customers to ingress data stored from any device at any time. The growth of the Internet helps the number of users who need to access online databases without a deep understanding of the schema or query. The languages have risen dramatically, allowing users to search secured data and retrieve desired data from cloud storage using keywords. On the other hand, there are fundamental difficulties such as security, which must be provided to secure user'spersonal information. A hybrid scheduling genetic algorithm (SGA) is proposed in this research. SGA technique enhances the security level and provides data freshness. For evaluation and comparison, parameters such as execution time throughputs are used. According to experimental results, the proposed technique ensures the security of user data from unauthorized parties. Furthermore, SGA is strong and more effective when compared to a set of parameters to the existing algorithm like Data Encryption Standard (DES), Blowfish, and AdvancedEncryption Standard (AES).

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