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» Utilizing Neural Networks For Effective Intrusion Detection
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NPL
2006
113views more  NPL 2006»
13 years 7 months ago
A Back-propagation Neural Network Landmine Detector Using the Delta-technique and S-statistic
Landmines are a major problem facing the world today; there are millions of these deadly weapons still buried in various countries around the world. Humanitarian organizations dedi...
Taskin Koçak, Matthew Draper
ICC
2009
IEEE
164views Communications» more  ICC 2009»
13 years 5 months ago
Policy-Based Security Configuration Management, Application to Intrusion Detection and Prevention
Intrusion Detection and/or Prevention Systems (IDPS) represent an important line of defense against the variety of attacks that can compromise the security and well functioning of...
Khalid Alsubhi, Issam Aib, Jérôme Fra...
ACSW
2006
13 years 9 months ago
Experiences in passively detecting session hijacking attacks in IEEE 802.11 networks
Current IEEE 802.11 wireless networks are vulnerable to session hijacking attacks as the existing standards fail to address the lack of authentication of management frames and net...
Rupinder Gill, Jason Smith, Andrew Clark
BSN
2009
IEEE
189views Sensor Networks» more  BSN 2009»
13 years 5 months ago
Neural Network Gait Classification for On-Body Inertial Sensors
Clinicians have determined that continuous ambulatory monitoring provides significant preventative and diagnostic benefit, especially to the aged population. In this paper we descr...
Mark A. Hanson, Harry C. Powell Jr., Adam T. Barth...
ACSAC
2006
IEEE
14 years 1 months ago
Backtracking Algorithmic Complexity Attacks against a NIDS
Network Intrusion Detection Systems (NIDS) have become crucial to securing modern networks. To be effective, a NIDS must be able to counter evasion attempts and operate at or near...
Randy Smith, Cristian Estan, Somesh Jha