Technology is growing very fast. We can now access everything using internet anywhere and anytime. That is why it is important to have internet security since we are always open to an online fraud, property damage and theft. IDS (Intrusion Detection System) can be used to detect any system or network attack. In this empirical study, we use dataset from KDD Cup 1999, which consist of five classes: normal, probe, dos, u2r and r2l. There is some classifier method for IDS, but in this study, we will use Fuzzy Robust Kernel C-Means (FRKCM) with Polynomial kernel and Fuzzy Entropy Kernel C-Means (FEKCM) with RBF kernel to find a better result that increase accuracy of the network attacks. There will be an accuracy comparison between FRKCM method and FEKCM method. The accuracy result from this study is 99% with time execution faster.
|Journal||IOP Conference Series: Materials Science and Engineering|
|Publication status||Published - 1 Jul 2019|
|Event||9th Annual Basic Science International Conference 2019, BaSIC 2019 - Malang, Indonesia|
Duration: 20 Mar 2019 → 21 Mar 2019