A Network Intrusion Detection System (NIDS) implemented using Streamlit and TensorFlow/Keras. This system predicts whether a network connection is normal or abnormal based on various features of the connection.
The following features are used for prediction:
protocol_type: The protocol type of the connection (e.g., TCP, UDP, ICMP).flag: The status of the connection (e.g., FIN, SYN, RST).service: The network service on the destination (e.g., http, ftp, telnet).src_bytes: The number of bytes sent by the source.dst_bytes: The number of bytes sent to the destination.count: The number of connections to the same destination host.same_srv_rate: The percentage of connections to the same service.diff_srv_rate: The percentage of connections to different services.dst_host_srv_count: The number of connections to the same destination host and service.dst_host_same_srv_rate: The percentage of connections to the same service on the same destination host.dst_host_same_src_port_rate: The percentage of connections from the same source port to the same destination host.