@inproceedings{dc2495f92a2346f5b51cac9fdbd3c8e9,
title = "Decision Tree with Sensitive Pruning in Network-based Intrusion Detection System",
abstract = "Machine learning techniques have been extensively adopted in the domain of Network-based Intrusion Detection System (NIDS) especially in the task of network traffics classification. A decision tree model with its kinship terminology is very suitable in this application. The merit of its straightforward and simple “if-else” rules makes the interpretation of network traffics easier. Despite its powerful classification and interpretation capacities, the visibility of its tree rules is introducing a new privacy risk to NIDS where it reveals the network posture of the owner. In this paper, we propose a sensitive pruning-based decision tree to tackle the privacy issues in this domain. The proposed pruning algorithm is modified based on C4.8 decision tree (better known as J48 in Weka package). The proposed model is tested with the 6 percent GureKDDCup NIDS dataset.",
keywords = "Decision Tree, GureKDDCup, Network-based Intrusion Detection System (NIDS), Privacy, Sensitive Pruning, Weka J48",
author = "Chew, {Yee Jian} and Ooi, {Shih Yin} and Wong, {Kok Seng} and Pang, {Ying Han}",
year = "2020",
month = jan,
day = "1",
doi = "10.1007/978-981-15-0058-9_1",
language = "English",
isbn = "9789811500572",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "1--10",
editor = "Rayner Alfred and Yuto Lim and Haviluddin Haviluddin and On, {Chin Kim}",
booktitle = "Computational Science and Technology - 6th ICCST 2019",
address = "Germany",
note = "6th International Conference on Computational Science and Technology, ICCST 2019 ; Conference date: 29-08-2019 Through 30-08-2019",
}