Predictive Analytics for Windows Server and FortiGate

الملخص

 Organizations need security solutions that are more flexible to combat cybercrime. Machine
learning (ML) provides a powerful weapon in this battle because of its remarkable capacity to
evaluate large, dynamic datasets. This project aims to strengthen the cybersecurity of vital
enterprise components such as Windows Servers and FortiGate systems by exploring the
possibilities of machine learning (ML) in log analysis.
We'll use the well-known network simulation tool GNS3 to simulate a real-world network
environment. Using GNS3, we can create a virtual network on our PCs, including a central
syslog server, Windows server, and FortiGate firewall. Thanks to this virtual environment, we
can experiment with our ML-powered log analysis solution in a secure and controlled setting
without affecting a production network.
The Windows Server and FortiGate systems will be set up to deliver their logs to the central
syslog server once our virtual network is operational. The digital traces of system activity that
these logs provide will be an incredible source of information for our machine-learning
investigation.
Take these logs to be the case files of a detective, loaded with hints on possible security
breaches. As highly skilled investigators, we will use ML algorithms to sort through the data and
find repeated patterns, anomalies, and any security issues. With the use of this active strategy, we
can identify dangers in real-time, allowing security teams to respond immediately and reduce
risks before they become serious incidents.