K-MEAN++ Applied To Solve Problems of Data Security in Data Science - Patel, Sarita (International Journal of Computer Sciences and Engineering, 2025)
In this paper, we describe an application K-MEAN++ clustering algorithm and Data Encryption Standard algorithm for security of information and large volumes data. Data are highly complex multidimensional signals, with rich and complicated information content Data science. For this reason they are difficult to analyze through a unique automated approach. However a K-MEAN++ scheme & Data Encryption Standard are helpful for the understanding of security of data content in Data science. In any system that captures, stores, analyzes, manages, and presents data that are linked to location and like Image satellite sensors acquire huge volumes of imagery to be processed and stored in big archives. Technically, a data science is a data modelling that includes mapping software and its application to data set , land surveying, aerial photography, mathematics, geography, and tools that can be implemented with Data science software Building a hierarchy is a fruitful area if one likes the challenge of having difficult technical problems to solve. Some problems have been solved in other technologies such as database management. However, Data science throws up new demands, therefore requiring new solutions. In this paper we have examine difficult problems, and to be solved and gives some security methods to solve the problem of data security using clustering algorithm.