Published Paper Details:

The shift toward remote work environments has significantly increased the risk of cybersecurity threats, exposing organizational assets to malicious activities such as phishing, unauthorized access, and malware infiltration. Many small to medium- sized enterprises (SMEs) lack the resources or technical capacity to implement complex Security Information and Event Management (SIEM) systems or automated orchestration frame- works. This paper presents the design and implementation of a simplified, rule-based Intelligent Incident Response System (IIRS) tailored for remote work environments. The pro- posed system focuses on real-time system monitoring, severity- based incident categorization, and email-based alerting. By leveraging lightweight technologies such as Python, psutil for resource monitoring, and smtplib for alert dissemination, the tool ensures efficient detection of anomalies based on CPU us- age, memory spikes, and suspicious processes. Detected events are classified into low, medium, or high-risk categories, triggering appropriate logging or notification actions. Incident data is stored in a local SQLite database for audit and analysis. The system is designed for ease of deployment, minimal dependencies, and adaptability to evolving organizational needs. This work aims to bridge the gap between minimal-resource environments and the need for actionable cybersecurity response mechanisms, making incident handling accessible and scalable for distributed workforces.