NEW IDENTIFICATION OF SECURITY CYBER METHODS USING ARTIFICIAL INTELLIGENCE

Abstract

ABSTRACT: Without substantial automation, individuals cannot manage the complexity of operations and the scale of information to be utilized to secure cyberspace. Artificial intelligence (AI) is a powerful technology that helps cyber security teams automate repetitive tasks, accelerate threat detection and response, and improve the accuracy of their actions to strengthen the security posture against various security issues and cyber-attacks. Machine learning is a powerful tool for investigating complex financial security threats that constantly evolve and can be difficult to predict. The findings contribute to a deeper understanding of AI's capabilities and limitations, providing insights that can guide the development and deployment of AI driven security systems. The surging menace of cyber-attacks got a jolt from the recent advancements in Artificial Intelligence. AI is being applied in almost every field of different sciences and engineering. The intervention of AI not only automates a particular task but also improves efficiency by many folds. Cybercriminals may now reach their targets from anywhere in the globe and at any time.  In strategic decision making, for example, comprehensive information is important, and logical decision assistance is one of the still unanswered cyber security issues. Machine learning algorithms are constantly being improved to identify anomalies in the data that might indicate a security threats. We look at real examples of AI success and consider ethics and teamwork with human experts. The findings show AI's promise in making cyber security stronger against changing cyber threats. Artificial intelligence is increasingly critical to information security since these technologies are capable of rapidly evaluating millions of data sets and identifying a broad range of cyber risks, ranging from malware attacks to suspicious behavior that may result in a phishing assault.