Intrusion Detection System using Machine Learning | Live Network | Python Projects
Network Intrusion Detection System using Machine Learning
Network intrusion detection is critical for protecting systems against cyber threats. This report presents a machine learning approach for classifying network traffic as normal or attack types using the NSL-KDD dataset. The data contains records of simulated network connections with 43 features and labels for normal or 24 attack categories grouped into 4 classes - Denial of Service, Probe, User to Root, and Remote to Local.
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Software Requirements :-
• Coding Language : Python
• Implementation: Web Framework.
• Operating system : Windows 10 / 11.
• Graphical User Interface : HTML, CSS, Django
Hardware Requirement :-
• Input Devices : Keyboard, Mouse.
• System : Pentium i3 Processor.
• Hard Disk : 500 GB.
• Ram : 4 GB.
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