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IMC
2009
ACM
14 years 2 months ago
ANTIDOTE: understanding and defending against poisoning of anomaly detectors
Statistical machine learning techniques have recently garnered increased popularity as a means to improve network design and security. For intrusion detection, such methods build ...
Benjamin I. P. Rubinstein, Blaine Nelson, Ling Hua...
AI
2008
Springer
14 years 2 months ago
Using Unsupervised Learning for Network Alert Correlation
Alert correlation systems are post-processing modules that enable intrusion analysts to find important alerts and filter false positives efficiently from the output of Intrusion...
Reuben Smith, Nathalie Japkowicz, Maxwell Dondo, P...
IPPS
2010
IEEE
13 years 5 months ago
Distributed monitoring of conditional entropy for anomaly detection in streams
In this work we consider the problem of monitoring information streams for anomalies in a scalable and efficient manner. We study the problem in the context of network streams wher...
Chrisil Arackaparambil, Sergey Bratus, Joshua Brod...
INFOCOM
2012
IEEE
11 years 10 months ago
Di-Sec: A distributed security framework for heterogeneous Wireless Sensor Networks
Wireless Sensor Networks (WSNs) are no longer a nascent technology and today, they are actively deployed as a viable technology in many diverse application domains such as health ...
Marco Valero, Sang Shin Jung, A. Selcuk Uluagac, Y...
CN
2004
256views more  CN 2004»
13 years 7 months ago
A line in the sand: a wireless sensor network for target detection, classification, and tracking
Intrusion detection is a surveillance problem of practical import that is well suited to wireless sensor networks. In this paper, we study the application of sensor networks to the...
Anish Arora, Prabal Dutta, Sandip Bapat, Vinod Kul...