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BIOSURVEILLANCE
2007
Springer
15 years 6 months ago
A Bayesian Biosurveillance Method That Models Unknown Outbreak Diseases
Algorithms for detecting anomalous events can be divided into those that are designed to detect specific diseases and those that are non-specific in what they detect. Specific dete...
Yanna Shen, Gregory F. Cooper
RTSS
2009
IEEE
15 years 6 months ago
Impact of Data Fusion on Real-Time Detection in Sensor Networks
—Real-time detection is an important requirement of many mission-critical wireless sensor network applications such as battlefield monitoring and security surveillance. Due to t...
Rui Tan, Guoliang Xing, Benyuan Liu, Jianping Wang
SIGMOD
2001
ACM
142views Database» more  SIGMOD 2001»
16 years 22 hour ago
Outlier Detection for High Dimensional Data
The outlier detection problem has important applications in the eld of fraud detection, network robustness analysis, and intrusion detection. Most such applications are high dimen...
Charu C. Aggarwal, Philip S. Yu
ACSAC
2004
IEEE
15 years 3 months ago
Extracting Attack Manifestations to Determine Log Data Requirements for Intrusion Detection
Log data adapted for intrusion detection is a little explored research issue despite its importance for successful and efficient detection of attacks and intrusions. This paper pr...
Emilie Lundin Barse, Erland Jonsson
IEEEVAST
2010
14 years 6 months ago
Anomaly detection in GPS data based on visual analytics
Modern machine learning techniques provide robust approaches for data-driven modeling and critical information extraction, while human experts hold the advantage of possessing hig...
Zicheng Liao, Yizhou Yu, Baoquan Chen