Sciweavers

765 search results - page 127 / 153
» Detecting Anomalies and Intruders
Sort
View
AAAI
2006
13 years 8 months ago
When Gossip is Good: Distributed Probabilistic Inference for Detection of Slow Network Intrusions
Intrusion attempts due to self-propagating code are becoming an increasingly urgent problem, in part due to the homogeneous makeup of the internet. Recent advances in anomalybased...
Denver Dash, Branislav Kveton, John Mark Agosta, E...
KDD
2009
ACM
167views Data Mining» more  KDD 2009»
14 years 8 months ago
SNARE: a link analytic system for graph labeling and risk detection
Classifying nodes in networks is a task with a wide range of applications. It can be particularly useful in anomaly and fraud detection. Many resources are invested in the task of...
Mary McGlohon, Stephen Bay, Markus G. Anderle, Dav...
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
14 years 7 months ago
Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage
We present and empirically analyze a machine-learning approach for detecting intrusions on individual computers. Our Winnowbased algorithm continually monitors user and system beh...
Jude W. Shavlik, Mark Shavlik
ICDM
2009
IEEE
148views Data Mining» more  ICDM 2009»
14 years 2 months ago
Online System Problem Detection by Mining Patterns of Console Logs
Abstract—We describe a novel application of using data mining and statistical learning methods to automatically monitor and detect abnormal execution traces from console logs in ...
Wei Xu, Ling Huang, Armando Fox, David Patterson, ...
JPDC
2006
253views more  JPDC 2006»
13 years 7 months ago
Collaborative detection and filtering of shrew DDoS attacks using spectral analysis
This paper presents a new spectral template-matching approach to countering shrew distributed denial-of-service (DDoS) attacks. These attacks are stealthy, periodic, pulsing, and ...
Yu Chen, Kai Hwang