A Cumulation of the Cyber Security Vulnerabilities in Latest Technologies

Abstract

Cyber security is the practice of defending computers, servers, mobile devices, electronic systems, networks, and data from malicious attacks.It's also known as information technology security or electronic information security.Different kinds of cyber attacks include Malware, Ransomware, Distributed denial of service (DDoS) attacks, Spam and Phishing, Corporate Account Takeover (CATO), Automated Teller Machine (ATM) Cash Out.Cybersecurity is a must in the digital age.Millions of people's personal information may be exposed as a result of a single security breach. These violations have a negative financial impact on the businesses as well as a loss of client confidence. Therefore, it is crucial to have cyber security to shield both persons and businesses from spammers and online crooks. This paper reviews information about the latest methodologies used to defend against potential cyber attacks in the latest technologies, critiques the current methods and provides references for future works. The review paper is a cumulation of Artificial Intelligence based detection models for cybersecurity threat analysis for modern day systems. A systematic search was performed on various electronic databases (SCOPUS, Science Direct, IEEE Xplore, Web of Science, ACM, and MDPI). This Review paper discusses artificial intelligence based detection methods for cyber threat analysis for modern day systems which include, cloud computing, connected and automated vehicles (CAVs) which include CAN (Controller Area Network) Buses, Internet of Things (IOT), Fintech (Financial Technology), Vehicle to Infrastructure Applications. The drawbacks of the three technologies under review have been underlined in the conclusion and are further explained using particular statistics. Some of the problems mentioned include the lack of adequate testing done by the manufacturers when the software is deployed in the context of smart cities. There is little to no overlap in the methodologies utilized for any of the aforementioned technologies, such as gradient boost in CAVs, and each has its own literature. There aren't enough datasets and, consequently, detection algorithms because the majority of research only addresses theoretical difficulties.Finding methods to apply a methodology from system 1 to system 2 or vice versa is one strategy to improve efficiency or wiser development.