Feature request : Intrution Detection System using Association Rule Mining

[IkkiOcean]

Description

The goal of this feature is to develop an Intrusion Detection System (IDS) Model that leverages Association Rule Mining techniques to identify unusual patterns of network activity. By applying these techniques, we aim to enhance the system's ability to detect potential security threats in real time, enabling quicker responses to incidents and improving overall network security.

Use Case

1. Real-Time Threat Detection

   • As a security analyst, I want to monitor network traffic in real time so that I can quickly identify and respond to potential threats based on established patterns.

2. Historical Data Analysis

   • As a network administrator, I want to analyze historical network activity to discover long-term trends and patterns that may indicate recurring security issues.

3. Customizable Alerting

   • As a security engineer, I want to set customizable thresholds for alerts so that I can adjust the sensitivity of the IDS according to the organization's security policies and risk tolerance.

4. Visualization of Network Patterns

   • As a system administrator, I want to visualize detected patterns and anomalies in network traffic over time, allowing me to present insights and findings to stakeholders effectively.

5. Integration with Existing Security Tools

   • As a security operations manager, I want the IDS to integrate with our existing security tools and frameworks, enhancing our overall security posture and enabling centralized monitoring.

[github-actions]

Thanks for creating the issue in ML-Nexus!🎉
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[github-actions]

Thanks for raising this issue! However, we believe a similar issue already exists. Kindly go through all the open issues and ask to be assigned to that issue.

[UppuluriKalyani]

@IkkiOcean proceed

[github-actions]

Hello @IkkiOcean! Your issue #207 has been closed. Thank you for your contribution!