Hybrid optimization‐based privacy preservation of database publishing in cloud environment

This work intends to introduce an optimization-based privacy preservation model via selecting the optimal key matrix. Here, privacy preservation is carried out under two processes, namely, “data sanitization and restoration.” In fact, data sanitization is the data preservation method, where the data (message) are preserved using the opti-
mal key. Similarly, data restoration is the inverse rocedure of sanitization. Here, the key matrix is optimally chosen using a novel hybrid algorithm. For optimization pur- pose, this work deploys a hybrid optimization approach known as random-based grey dragon algorithm (R-GDA) that involves the concepts of both “dragonfly algorithm (DA) and grey wolf optimization (GWO) algorithm.” The novelty of the work is introduced in hybrid optimization approach R-GDA. ventually, the supremacy of the adopted method is validated over other existing approaches in terms of various measures such as privacy, utility, and so on. The privacy preservation in the cloud is achievable in the field of education, banking sector, military, and the research community.