Experimental Evaluation of BigData Analytics to Improve Communication Security and Privacy Enrichment using Cybersecurity Logics

The massive volume of data generated by the rapid expansion of digital communication necessitates a sufficient degree of security and privacy. Big data analytics is demonstrated to be helpful in enhancing privacy and security of communications in one such study. The aim is to use advanced analytics to identify and mitigate security risks from large databases. In processing large-scale disorganized and structured or partially organized information, the major benefits of the proposed approach, BigData enabled Communication Security Protocol (BCSP), are cross-verified against an existing approach, Secured BigData Analyzer (SBA). Enhancing utilizing big data analytics, communication security is employed to analyze data obtained from a company's network, user behavior data, or even threat-related information. The data analyzed is then utilized to improve the digital communication security of the business using the conclusions the analysis produces. This study offers an integrated approach to security and privacy, including pre-processing and feature engineering, and presents a framework for designing effective machine learning systems that integrate data collecting.