Design and Deployment of a Cloud Monitoring System for Enhanced Network Security

With the increasing adoption of cloud computing and the growing reliance on networked infrastructure, improving cloud network security has become an increasingly vital concern. One critical aspect of network security is monitoring, which involves keeping track of the connected devices to the network and detecting potential security threats such as IP and MAC address duplications. To address these challenges, this thesis focuses on providing a customized monitoring system based on the data of ARP tables of the routers in a network. The system receives the exported data of the routers in regular intervals and analyzes the IP and MAC of each line of the files. It then stores these data in a table and adds other metadata from other databases for each line, such as the department that the device is used, the type of the device, and the type of operating system. By integrating metadata from other databases, the system can provide a more comprehensive view of the network and its devices. The metadata also enables the system to group connected devices by department, which provides useful insights into the distribution of network devices across the organization. Once the data is stored, the system processes it to extract various statistics that provide a comprehensive overview of the network's status. These statistics include the total number of connected devices, the number and list of MAC and IP duplications, the number of corrupted lines in ARP tables, the number of connected devices in each department and etc. The system presents all statistics in a dashboard that offers users the ability to set alerts for significant fluctuations in the values of different parameters. The dashboard includes charts and graphs that enable users to visualize network activity over time and quickly identify potential security threats. The system's design is modular, making it easy to scale and extend. For instance, users can add new data sources, such as additional databases or logs, and customize the dashboard to their specific needs. In summary, this thesis offers a valuable contribution to improving cloud network security by providing a customized monitoring system that focuses on detecting IP and MAC duplications. The system's integration with other databases and the ability to group devices by the department provides a more comprehensive view of the network's status. Overall, this system represents a valuable tool for organizations seeking to improve their network security and reduce the risk of potential cyber threats.