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Adversarial Knowledge Discovery
November/December 2009 (vol. 24 no. 6)
pp. 54-61
ASCII Text
x 
 
David B. Skillicorn, "Adversarial Knowledge Discovery," IEEE Intelligent Systems, vol. 24, no. 6, pp. 54-61, November/December, 2009.
 
 
BibTex
x
 
@article{ 10.1109/MIS.2009.108,
author = {David B. Skillicorn},
title = {Adversarial Knowledge Discovery},
journal ={IEEE Intelligent Systems},
volume = {24},
number = {6},
issn = {1541-1672},
year = {2009},
pages = {54-61},
doi = {http://doi.ieeecomputersociety.org/10.1109/MIS.2009.108},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - IEEE Intelligent Systems
TI - Adversarial Knowledge Discovery
IS - 6
SN - 1541-1672
SP54
EP61
EPD - 54-61
A1 - David B. Skillicorn,
PY - 2009
KW - data mining
KW - law enforcement
KW - fraud
KW - counterterrorism
KW - fringe clusters
KW - predicting normality
VL - 24
JA - IEEE Intelligent Systems
ER -
 
David B. Skillicorn, Queen's University Kingston, Canada

In adversarial settings, knowledge discovery must be dynamic, adapting to both the changing face of normality and the rapidly changing properties of adversaries.

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Index Terms:
data mining, law enforcement, fraud, counterterrorism, fringe clusters, predicting normality
Citation:
David B. Skillicorn, "Adversarial Knowledge Discovery," IEEE Intelligent Systems, vol. 24, no. 6, pp. 54-61, Nov./Dec. 2009, doi:10.1109/MIS.2009.108
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