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» Anomaly detection in data represented as graphs
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CIDM
2009
IEEE
13 years 11 months ago
Mining for insider threats in business transactions and processes
—Protecting and securing sensitive information are critical challenges for businesses. Deliberate and intended actions such as malicious exploitation, theft or destruction of dat...
William Eberle, Lawrence B. Holder
KDD
2004
ACM
124views Data Mining» more  KDD 2004»
14 years 5 months ago
Eigenspace-based anomaly detection in computer systems
We report on an automated runtime anomaly detection method at the application layer of multi-node computer systems. Although several network management systems are available in th...
Hisashi Kashima, Tsuyoshi Idé
KDD
2003
ACM
155views Data Mining» more  KDD 2003»
14 years 5 months ago
Graph-based anomaly detection
Anomaly detection is an area that has received much attention in recent years. It has a wide variety of applications, including fraud detection and network intrusion detection. A ...
Caleb C. Noble, Diane J. Cook
IAT
2008
IEEE
13 years 11 months ago
Link-Based Anomaly Detection in Communication Networks
Communication networks, such as networks formed by phone calls and email communications, can be modeled as dynamic graphs with vertices representing agents and edges representing ...
Xiaomeng Wan, Evangelos E. Milios, Nauzer Kalyaniw...
FLAIRS
2010
13 years 7 months ago
Using a Graph-Based Approach for Discovering Cybercrime
The ability to mine data represented as a graph has become important in several domains for detecting various structural patterns. One important area of data mining is anomaly det...
William Eberle, Lawrence B. Holder, Jeffrey Graves