An intruder detection approach based on infrequent rating pattern mining
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- @InProceedings{Luna:2010:ISDA,
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author = "Jose Maria Luna and Aurora Ramirez and
Jose Raul Romero and Sebastian Ventura",
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title = "An intruder detection approach based on infrequent
rating pattern mining",
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booktitle = "10th International Conference on Intelligent Systems
Design and Applications (ISDA 2010)",
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year = "2010",
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month = nov # " 29-" # dec # " 1",
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pages = "682--688",
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abstract = "This work presents a novel proposal for incremental
intruder detection in collaborative recommender
systems. We explore the use of rare association rule
mining to reveal the existence of a suspected raid of
attackers that would alter the normal behaviour of a
rating-based system. In this position paper we have
extended our previous G3PARM algorithm, which has
already proven to serve as a solid method for
extracting frequent association rules. G3PARM is an
evolutionary algorithm that uses G3P (Grammar Guided
Genetic Programming), which provides expressiveness and
flexibility enough to adapt and apply the base
context-free grammar to each specific problem or
domain. We fully outline, moreover, the complete
exploration and detection model, which includes some
further post-analysis steps. Finally, as a proof of
concept, we validate the scalability, efficiency and
accuracy of our proposal showing the results obtained
when different malicious intruders want to attack an on
line recommender system.",
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keywords = "genetic algorithms, genetic programming, G3PARM
algorithm, association rule mining, collaborative
recommender system, context free grammar, evolutionary
algorithm, grammar guided genetic programming,
incremental intruder detection, infrequent rating
pattern mining, context-free grammars, data mining,
recommender systems, security of data",
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DOI = "doi:10.1109/ISDA.2010.5687184",
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notes = "Also known as \cite{5687184}",
- }
Genetic Programming entries for
Jose Maria Luna
Aurora Ramirez Quesada
Jose Raul Romero Salguero
Sebastian Ventura
Citations