A Network Security Solution to Manage and Increase Effectiveness of Servers

In today's digital landscape, the proliferation of cyber threats, particularly Denial-of-Service (DoS) attacks, underscores the critical need for advanced server monitoring systems. Traditional monitoring tools, while prevalent, often lack the adaptability and proactive capabilities required to address these evolving threats effectively. This thesis introduces the Adaptive Monitoring System (AMS), an innovative solution designed to enhance network security and operational efficiency. Developed using Python and API scripting, AMS integrates with existing protocols such as Simple Network Management Protocol (SNMP), SSH, and Syslog to offer comprehensive real-time monitoring and automatic system adjustments. The primary goal of the AMS is to improve network monitoring through the automation of server configuration changes in response to detected anomalies. The system's effectiveness is demonstrated across various attack scenarios, including TCP SYN flood, UDP, ICMP, and HTTP attacks. The results indicate that the AMS not only effectively identifies and mitigates DoS attacks but also exhibits significant scalability and robustness as the attack intensity increases. One of the system’s standout features is its automatic reconfiguration capability, which allows it to restore normal operations autonomously, reducing the administrative burden and enhancing network reliability. Additionally, the AMS is equipped to generate timely alerts and notifications, enabling system administrators to take pre-emptive actions to mitigate potential impacts to system performance. This thesis details how the AMS addresses the challenges of contemporary server monitoring and provides a robust defence against network intrusions, thereby contributing to the field of cybersecurity.