A combined negative selection algorithm-particle swarm optimization for an email spam detection system
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86092867" target="_blank" >RIV/61989100:27240/15:86092867 - isvavai.cz</a>
Alternative codes found
RIV/62690094:18450/15:50003035
Result on the web
<a href="http://www.sciencedirect.com/science/article/pii/S0952197614002656" target="_blank" >http://www.sciencedirect.com/science/article/pii/S0952197614002656</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.engappai.2014.11.001" target="_blank" >10.1016/j.engappai.2014.11.001</a>
Alternative languages
Result language
angličtina
Original language name
A combined negative selection algorithm-particle swarm optimization for an email spam detection system
Original language description
Email is a convenient means of communication throughout the entire world today. The increased popularity of email spam in both text and images requires a real-time protection mechanism for the media flow. The previous approach has been limited by the adaptive nature of unsolicited email spam. This research introduces an email detection system that is designed based on an improvement in the negative selection algorithm. Furthermore, particle swarm optimization (PSO) was implemented to improve the randomdetector generation in the negative selection algorithm (NSA). The algorithm generates detectors in the random detector generation phase of the negative selection algorithm. The combined NSA-PSO uses a local outlier factor (LOF) as the fitness function for the detector generation. The detector generation process is terminated when the expected spam coverage is reached. A distance measure and a threshold value are employed to enhance the distinctiveness between the non-spam and spam detec
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
ISSN
0952-1976
e-ISSN
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Volume of the periodical
39
Issue of the periodical within the volume
March 2015
Country of publishing house
GB - UNITED KINGDOM
Number of pages
12
Pages from-to
33-44
UT code for WoS article
000349878400004
EID of the result in the Scopus database
2-s2.0-84921734655