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» Utilizing Neural Networks For Effective Intrusion Detection
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ICML
2002
IEEE
16 years 19 days 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
14 years 10 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
15 years 1 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
15 years 5 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
15 years 3 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, ...