Web Application Security through Gene Expression Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{conf/evoW/SkaruzS09,
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title = "Web Application Security through Gene Expression
Programming",
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author = "Jaroslaw Skaruz and Franciszek Seredynski",
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booktitle = "Applications of Evolutionary Computing, EvoWorkshops
2009: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES,
EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM,
EvoSTOC, EvoTRANSLOG",
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editor = "Mario Giacobini and Anthony Brabazon and
Stefano Cagnoni and Gianni A. Di Caro and
Anik{\'o} Ek{\'a}rt and Anna Esparcia-Alc{\'a}zar and Muddassar Farooq and
Andreas Fink and Penousal Machado and Jon McCormack and
Michael O'Neill and Ferrante Neri and Mike Preuss and
Franz Rothlauf and Ernesto Tarantino and
Shengxiang Yang",
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volume = "5484",
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series = "Lecture Notes in Computer Science",
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address = "Tubingen, Germany",
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year = "2009",
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pages = "1--10",
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month = apr # " 15-17",
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organisation = "EvoStar",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, gene
expression programming",
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isbn13 = "978-3-642-01128-3",
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bibdate = "2009-04-16",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/evoW/evoW2009.html#SkaruzS09",
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DOI = "doi:10.1007/978-3-642-01129-0_1",
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abstract = "In the paper we present a novel approach based on
applying a modern metaheuristic Gene Expression
Programming (GEP) to detecting web application attacks.
This class of attacks relates to malicious activity of
an intruder against applications, which use a database
for storing data. The application uses SQL to retrieve
data from the database and web server mechanisms to put
them in a web browser. A poor implementation allows an
attacker to modify SQL statements originally developed
by a programmer, which leads to stealing or modifying
data to which the attacker has not privileges.
Intrusion detection problem is transformed into
classification problem, which the objective is to
classify SQL queries between either normal or malicious
queries. GEP is used to find a function used for
classification of SQL queries. Experimental results are
presented on the basis of SQL queries of different
length. The findings show that the efficiency of
detecting SQL statements representing attacks depends
on the length of SQL statements.",
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notes = "EvoWorkshops2009 held in conjunction with EuroGP2009,
EvoCOP2009, EvoBIO2009",
- }
Genetic Programming entries for
Jaroslaw Skaruz
Franciszek Seredynski
Citations