@inproceedings{fbe1973f0966458b8398b84abf460abc,
title = "A distributed neural network learning algorithm for network intrusion detection system",
abstract = "To make network intrusion detection systems can be used in Gigabit Ethernet, a distributed neural network learning algorithm (DNNL) is put forward to keep up with the increasing network throughput. The main idea of DNNL is splitting the overall traffic into subsets and several sensors learn them in parallel way. The advantage of this method is that the large data set can be split randomly thus reduce the complicacy of the splitting algorithm. The experiments are performed on the KDD'99 Data Set which is a standard intrusion detection benchmark. Comparisons with other approaches on the same benchmark show that DNNL can perform detection with high detection rate.",
keywords = "Distributed learning, Intrusion detection system, Neural network",
author = "Yanheng Liu and Daxin Tian and Xuegang Yu and Jian Wang",
year = "2006",
doi = "10.1007/11893295\_23",
language = "英语",
isbn = "3540464840",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "201--208",
booktitle = "Neural Information Processing - 13th International Conference, ICONIP 2006, Proceedings",
address = "德国",
note = "13th International Conference on Neural Information Processing, ICONIP 2006 ; Conference date: 03-10-2006 Through 06-10-2006",
}