Paper Info
Title
Interactive Visualization of Normal Behavioral Models and Expert Rules for Maritime Anomaly Detection
Abstract
Maritime surveillance systems analyze vast amounts of heterogeneous sensor data from a large number of objects. In order to support the operator while monitoring such systems, the identification of anomalous vessels or situations that might need further investigation may reduce the operator's cognitive load. While it is worth acknowledging that many existing mining applications support identification of anomalous behavior, autonomous anomaly detection systems are rarely used in the real world, since the detection of anomalous behavior is normally not a well-defined problem and therefore, human expert knowledge is needed. This calls for the development of interaction components that can support the user in the detection process.In order to support the comprehension of the knowledge embedded in the system, we propose an interactive way of visualizing expert rules and normal behavioral models built from the data. The overall goal is to facilitate the validation and update of these models and signatures, supporting the insertion of human expert knowledge while improving confidence and trust in the system.
Year
DOI
Venue
2009
10.1109/CGIV.2009.54
CGIV
Keywords
Field
DocType
cognitive load,anomalous behavior,existing mining applications support,detection process,maritime surveillance system,normal behavioral models,expert rules,visualizing expert rule,human expert knowledge,anomalous vessel,maritime anomaly detection,interactive visualization,heterogeneous sensor data,autonomous anomaly detection system,expert systems,association rules,behavior modeling,anomaly detection,data analysis,computer and information science,data models,visual analytics,technology,data visualization,situation awareness,embedded system,marine engineering,data mining,embedded systems,data visualisation
Data mining,Data modeling,Anomaly detection,Computer science,Visual analytics,Human–computer interaction,Artificial intelligence,Data visualization,Pattern recognition,Expert system,Association rule learning,Interactive visualization,Cognitive load
Conference
Citations 
PageRank 
References 
5
0.45
22
Authors
2
Name
Order
Citations
PageRank
Maria Riveiro113318.64
Goran Falkman215511.57