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» Detecting Anomalies and Intruders
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BMCBI
2005
120views more  BMCBI 2005»
13 years 7 months ago
Robust detection of periodic time series measured from biological systems
Background: Periodic phenomena are widespread in biology. The problem of finding periodicity in biological time series can be viewed as a multiple hypothesis testing of the spectr...
Miika Ahdesmäki, Harri Lähdesmäki, ...
ASPLOS
2010
ACM
14 years 2 months ago
Accelerating the local outlier factor algorithm on a GPU for intrusion detection systems
The Local Outlier Factor (LOF) is a very powerful anomaly detection method available in machine learning and classification. The algorithm defines the notion of local outlier in...
Malak Alshawabkeh, Byunghyun Jang, David R. Kaeli
TRIDENTCOM
2005
IEEE
14 years 1 months ago
TBI: End-to-End Network Performance Measurement Testbed for Empirical Bottleneck Detection
— Recent advances in networking include new bandwidth-intensive applications, sophisticated protocols that enable real-time data and multimedia delivery and aspects of network se...
Prasad Calyam, Dima Krymskiy, Mukundan Sridharan, ...
ICNP
2009
IEEE
14 years 2 months ago
Attack-Tolerant Distributed Sensing for Dynamic Spectrum Access Networks
—Accurate sensing of the spectrum condition is of crucial importance to the mitigation of the spectrum scarcity problem in dynamic spectrum access (DSA) networks. Specifically, ...
Alexander W. Min, Kang G. Shin, Xin Hu
LCN
2007
IEEE
14 years 1 months ago
Efficient Multi-Dimensional Flow Correlation
—Flow correlation algorithms compare flows to determine similarity, and are especially useful and well studied for detecting flow chains through “stepping stone” hosts. Most ...
W. Timothy Strayer, Christine E. Jones, Beverly Sc...