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» Utilizing Neural Networks For Effective Intrusion Detection
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ICML
2002
IEEE
14 years 8 months ago
Learning to Share Distributed Probabilistic Beliefs
In this paper, we present a general machine learning approach to the problem of deciding when to share probabilistic beliefs between agents for distributed monitoring. Our approac...
Christopher Leckie, Kotagiri Ramamohanarao
ISI
2008
Springer
13 years 6 months ago
Anomaly detection in high-dimensional network data streams: A case study
In this paper, we study the problem of anomaly detection in high-dimensional network streams. We have developed a new technique, called Stream Projected Ouliter deTector (SPOT), t...
Ji Zhang, Qigang Gao, Hai H. Wang
FLAIRS
2003
13 years 9 months ago
LIDS: Learning Intrusion Detection System
The detection of attacks against computer networks is becoming a harder problem to solve in the field of network security. The dexterity of the attackers, the developing technolog...
Mayukh Dass, James Cannady, Walter D. Potter
DSN
2005
IEEE
14 years 1 months ago
The Effects of Algorithmic Diversity on Anomaly Detector Performance
Common practice in anomaly-based intrusion detection assumes that one size fits all: a single anomaly detector should detect all anomalies. Compensation for any performance short...
Kymie M. C. Tan, Roy A. Maxion
ESORICS
2006
Springer
13 years 11 months ago
Towards an Information-Theoretic Framework for Analyzing Intrusion Detection Systems
IDS research still needs to strengthen mathematical foundations and theoretic guidelines. In this paper, we build a formal framework, based on information theory, for analyzing and...
Guofei Gu, Prahlad Fogla, David Dagon, Wenke Lee, ...