A combined negative selection algorithm-particle swarm optimization for an email spam detection system

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/62690094:18450/15:50003035

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

A combined negative selection algorithm-particle swarm optimization for an email spam detection system

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

A combined negative selection algorithm-particle swarm optimization for an email spam detection system

Popis výsledku anglicky

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

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

ISSN

0952-1976

e-ISSN

—

Svazek periodika

39

Číslo periodika v rámci svazku

March 2015

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

12

Strana od-do

33-44

Kód UT WoS článku

000349878400004

EID výsledku v databázi Scopus

2-s2.0-84921734655