Development of Critical Information Framework by Big Data Analytics and Artificial Intelligence to Prevent Cyber Attacks in WSN

Abstract

Sadly, we now have to deal with the phenomenon of cyber-attacks as a result of our growing dependence on internet information. As technology has evolved and gotten more complex, so have the sorts of malware used in these assaults. At current moment, CIIs including financial institutions and telecommunications are the targets of an increasing number of targeted cyberattacks. APTs are a specific kind of malware that is difficult to identify and remove due to its covert nature, intricate design, and use in targeted attacks. These computer viruses may injure and assault people (in the targeted systems). Considering how long conventional cyber security techniques take, this is rather concerning. Defense strategies fail to thwart these assaults. To make knowledge decisions and warn of imminent dangers, researchers must have a realistic understanding of this vast amount of data. This expertise can only be achieved through automation. Cyber defense is primarily based on big data analytics and artificial intelligence. Methods of big data analytics are typically used on large data sets containing a limited number of data types. It is the goal of this research to identify patterns, connections, themes, and other pertinent information.