Mitigating Cyber-Security Risks using Cyber-Analytics

Cybercrime is a global issue that has taken over the digital space. Data is sent over networks every second, information is compromised, and systems are exposed to multiple threats. This paper on Cyber Security Analytics aims to deliver real-time analytics and operational intelligence in a simple format. Cyber Security Analytics includes real-time data collection, continuous monitoring of security controls, log processing and analysis, and immediate flagging of suspicious activity. This research study provides a fundamental platform for cybersecurity enthusiasts by detailing how to mitigate cybersecurity risks by utilizing a whole new and different perspective of AI and ML. This paper also focuses on IT issues that affect the real world. It also discusses potential vulnerabilities in an organization's IT infrastructure, networks, hardware, and software and reports on hacking attempts to develop more robust security procedures. This paper begins by understanding the various cybersecurity problems and challenges and how machine learning shapes cybersecurity analysis. This paper also considers multiple data science and predictive modeling applications in cybersecurity. This paper is expected to aid in developing predictive as well as detective modeling products and counter-cyber-attack solutions.