DocumentCode :
2359355
Title :
Social engineering attack detection model: SEADM
Author :
Bezuidenhout, Monique ; Mouton, Francois ; Venter, H.S.
Author_Institution :
Dept. of Psychol., Univ. of Pretoria, Pretoria, South Africa
fYear :
2010
fDate :
2-4 Aug. 2010
Firstpage :
1
Lastpage :
8
Abstract :
Social engineering is a real threat to industries in this day and age even though the severity of it is extremely downplayed. The difficulty with social engineering attacks is mostly the ability to identify them. Social engineers target call centre employees, as they are normally underpaid, under skilled workers whom have limited knowledge about the information technology infrastructure. These workers are thus easy targets for the social engineer. This paper proposes a model which can be used by these workers to detect social engineering attacks in a call centre environment. The model is a quick and effective way to determine if the requester is trying to manipulate an individual into disclosing information to which the requester does not have authorization for.
Keywords :
authorisation; call centres; personnel; authorization; call centre employee; information technology infrastructure; social engineering attack detection model; Biological system modeling; Cognition; Computational modeling; Decision making; Humans; Psychology; Utility theory; Social engineering; emotional state; information sensitivity; social psychology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Security for South Africa (ISSA), 2010
Conference_Location :
Sandton, Johannesburg
Print_ISBN :
978-1-4244-5493-8
Type :
conf
DOI :
10.1109/ISSA.2010.5588500
Filename :
5588500
Link To Document :
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