In the Current world situation with an increase in internet speed and bandwidth, data requirement increases
with a transfer of a tremendous amount of data over a network, especially internet, wired or wireless network. This
poses a significantchallenge to network security or cyber security i.e. unauthorized access to secure data. To counter these
challenges on wireless networks is hard with its extra ordinary properties. To counter this challenge IDS (Intrusion
Detection System) is used to detect various types of attacks on a network by analyzing abnormal behavior on a
network. One common method to detectthis type of attack was signature-based, the other was an anomaly that provided
security to the network. With the introduction oremergence of AI, ML techniques can be used in IDS to detect this type
of attack with more accuracy. There are some proposed structures architectures or models to secure networks that
provide some significant results. Here we are going to use different Ml algorithms (RF, SVC, GNB) and then
XGBClaasifier to get better accuracy in IDS to detect various attacks.
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