tailieunhanh - Báo cáo hóa học: " Research Article Multilayer Statistical Intrusion Detection in Wireless Networks"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Multilayer Statistical Intrusion Detection in Wireless Networks | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2009 Article ID 368589 13 pages doi 2009 368589 Research Article Multilayer Statistical Intrusion Detection in Wireless Networks Mohamed Hamdi Amel Meddeb-Makhlouf and Noureddine Boudriga Communication Networks and Security Research Laboratory School of Communication Engineering University of 7th of November at Carthage 2083 Ariana Tunisia Correspondence should be addressed to Mohamed Hamdi mmh@ Received 6 September 2007 Revised 15 May 2008 Accepted 16 September 2008 Recommended by Polly Huang The rapid proliferation of mobile applications and services has introduced new vulnerabilities that do not exist in fixed wired networks. Traditional security mechanisms such as access control and encryption turn out to be inefficient in modern wireless networks. Given the shortcomings of the protection mechanisms an important research focuses in intrusion detection systems IDSs . This paper proposes a multilayer statistical intrusion detection framework for wireless networks. The architecture is adequate to wireless networks because the underlying detection models rely on radio parameters and traffic models. Accurate correlation between radio and traffic anomalies allows enhancing the efficiency of the IDS. A radio signal fingerprinting technique based on the maximal overlap discrete wavelet transform MODWT is developed. Moreover a geometric clustering algorithm is presented. Depending on the characteristics of the fingerprinting technique the clustering algorithm permits to control the false positive and false negative rates. Finally simulation experiments have been carried out to validate the proposed IDS. Copyright 2009 Mohamed Hamdi et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. Introduction .

TÀI LIỆU LIÊN QUAN
crossorigin="anonymous">
Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.