Spam detection using linear genetic programming
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F19%3A63522860" target="_blank" >RIV/70883521:28140/19:63522860 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-97888-8_7" target="_blank" >http://dx.doi.org/10.1007/978-3-319-97888-8_7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-97888-8_7" target="_blank" >10.1007/978-3-319-97888-8_7</a>
Alternative languages
Result language
angličtina
Original language name
Spam detection using linear genetic programming
Original language description
Spam refers to unsolicited bulk email. Many algorithms have been applied to the spam detection problem and many programs have been developed. The problem is an adversarial one and an ongoing fight against spammers. We prove that reliable Spam detection is an NP-complete problem, by mapping email spams to metamorphic viruses and applying Spinellis’s [30] proof of NP-completeness of metamorphic viruses. Using a number of features extracted from the SpamAssassin Data set, a linear genetic programming (LGP) system called Gagenes LGP (or GLGP) has been implemented. The system has been shown to give 99.83% accuracy, higher than Awad et al.’s [3] result with the Naïve Bayes algorithm. GLGP’s recall and precision are higher than Awad et al.’s, and GLGP’s Accuracy is also higher than the reported results by Lai and Tsai [19].
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Intelligent Systems and Computing, Volume 837
ISBN
978-331997887-1
ISSN
21945357
e-ISSN
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Number of pages
12
Pages from-to
80-92
Publisher name
Springer Verlag
Place of publication
Berlín
Event location
Brno
Event date
Jun 20, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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