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» Detecting Anomalies and Intruders
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RTSS
2006
IEEE
14 years 1 months ago
Voice over Sensor Networks
Wireless sensor networks have traditionally focused on low duty-cycle applications where sensor data are reported periodically in the order of seconds or even longer. This is due ...
Rahul Mangharam, Anthony Rowe, Raj Rajkumar, Ryohe...
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
14 years 7 months ago
Finding tribes: identifying close-knit individuals from employment patterns
We present a family of algorithms to uncover tribes--groups of individuals who share unusual sequences of affiliations. While much work inferring community structure describes lar...
Lisa Friedland, David Jensen
KDD
2003
ACM
156views Data Mining» more  KDD 2003»
14 years 7 months ago
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
Defining outliers by their distance to neighboring examples is a popular approach to finding unusual examples in a data set. Recently, much work has been conducted with the goal o...
Stephen D. Bay, Mark Schwabacher
CHI
2010
ACM
14 years 2 months ago
Characterizing debate performance via aggregated twitter sentiment
Television broadcasters are beginning to combine social micro-blogging systems such as Twitter with television to create social video experiences around events. We looked at one s...
Nicholas Diakopoulos, David A. Shamma
ICIW
2009
IEEE
14 years 2 months ago
SS-IDS: Statistical Signature Based IDS
Security of web servers has become a sensitive subject today. Prediction of normal and abnormal request is problematic due to large number of false alarms in many anomaly based In...
Payas Gupta, Chedy Raïssi, Gérard Dray...