AI Based Decision Support System for Cyber Forensics Investigations

The increasing sophistication and frequency of cyber attacks have made advanced solutions necessary to safeguard critical systems from threats. data. AI-Based Decision Support Systems (DSS) offer a transformative approach to cyber security by leveraging artificial intelligence and machine learning to identify, assess, and mitigate risks in real time. These systems enhance decision-making processes by automating threat detection, analyzing vast datasets for anomalies, and predicting potential vulnerabilities with high precision. This essay looks at how AI-based DSS can be used in cyber security, focusing on how they can adapt to new attack vectors and offer proactive defenses. By combining advanced analytics, monitoring in real time, and smart threat response, these systems make digital infrastructures more resilient and cut down on the time it takes to respond. Key applications include intrusion detection, fraud prevention, malware analysis, and secure network management. The study also highlights the challenges of implementing AI in cyber security, such as ethical concerns, data privacy, and the need for robust training datasets.AI-based DSS represent a critical advancement in cyber security, empowering organizations to stay ahead of adversaries and establish a secure digital environment. Their potential for scalability and continual learning positions them as essential tools in addressing the dynamic and complex nature of modern cyber threats. This paper presents a case study of a real-world medical information system.