Abstract
Due to the inexorable notoriety of ubiquitous mobile devices and cloud processing, storing of data (for example photographs, recordings, messages, and texts) in the cloud has turned into a pattern among individual and hierarchical clients. Be that as it may, cloud service providers can’t be trusted entirely to guarantee the accessibility or honesty of client data re-appropriated/transferred to the cloud. Consequently, to enhance the cybersecurity level of cloud data, a new security model is introduced along with optimal key selection. In the proposed study, first cluster the secret information which we are taken using K-Mediod clustering algorithm based on a data distance measure. Then, the clustered data are encrypted using Blowfish Encryption (BE) and stored in the cloud. To improve the cybersecurity level, the optimal key is chosen based on the maximum key breaking time; for that, we presented a technique called Improved Dragonfly Algorithm (IDA). The result demonstrates that the optimal blowfish algorithm improves the accuracy of cybersecurity for all secret information compared to existing algorithms.
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Bhuvaneshwaran, A., Manickam, P., Ilayaraja, M., Sathesh Kumar, K., Shankar, K. (2019). Clustering Based Cybersecurity Model for Cloud Data. In: Hassanien, A., Elhoseny, M. (eds) Cybersecurity and Secure Information Systems. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-16837-7_11
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DOI: https://doi.org/10.1007/978-3-030-16837-7_11
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