DETECTION OF MAC SPOOFING IN MOBILE HOTSPOT USING RANDOM FOREST

ADITHYA IRAWAN, Drs. Bambang Nurcahyo Prastowo, M. Sc.

2020 | Skripsi | S1 ILMU KOMPUTER

In computer network, the authentication of each user in the network is essential to the business corporation (Bourgeois and Bourgeois, 2014). One of those authentication problem is mac spoofing. Previous research by Alotaibi and Elleithy (2016) have attempted to formulate a detection technique using RSS data with random forest based on their accuracy. This research attempted to use that technique with the help of feature importance technique as a way of detecting the mac spoofing in mobile hotspot. The implementation used RSS data, random forest, python library and feature importance technique. The RSS that already process by the feature importance shows that the top 3 most important feature of the benchmark model device that had been created cannot be mimic by other device with mac address spoofing technique.

In computer network, the authentication of each user in the network is essential to the business corporation (Bourgeois and Bourgeois, 2014). One of those authentication problem is mac spoofing. Previous research by Alotaibi and Elleithy (2016) have attempted to formulate a detection technique using RSS data with random forest based on their accuracy. This research attempted to use that technique with the help of feature importance technique as a way of detecting the mac spoofing in mobile hotspot. The implementation used RSS data, random forest, python library and feature importance technique. The RSS that already process by the feature importance shows that the top 3 most important feature of the benchmark model device that had been created cannot be mimic by other device with mac address spoofing technique.

Kata Kunci : Mac addresses, RSS, Random forest, feature importance