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Identity theft risk quantification for social media users

Thesis (MEng)--Stellenbosch University, 2017.

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Main Author: Michau, Nicola
Other Authors: Bekker, James
Format: Thesis
Language:en_ZA
Published: Stellenbosch : Stellenbosch University 2017
Subjects:
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access_status_str Open Access
author Michau, Nicola
author2 Bekker, James
author_browse Bekker, James
Michau, Nicola
author_facet Bekker, James
Michau, Nicola
author_sort Michau, Nicola
collection Thesis
dc_rights_str_mv Stellenbosch University
description Thesis (MEng)--Stellenbosch University, 2017.
format Thesis
id oai:scholar.sun.ac.za:10019.1/101149
institution Stellenbosch University (South Africa)
language en_ZA
last_indexed 2026-06-10T12:44:25.612Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2017
publishDateRange 2017
publishDateSort 2017
publisher Stellenbosch : Stellenbosch University
publisherStr Stellenbosch : Stellenbosch University
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/101149 Identity theft risk quantification for social media users Michau, Nicola Bekker, James Bekker, James Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering. Identity theft UCTD Social media Data mining Thesis (MEng)--Stellenbosch University, 2017. ENGLISH ABSTRACT: The information era has made it di cult to protect and secure one's personal information. One such struggle is that of identity theft, a crime that has caused great su ering to its victims. O enders guilty of the crime use the identities of their victims for the purpose of entertainment or fraud. Social media has extended the capability of people to interact and share information, but without the appropriate guidelines to protect individuals from becoming victims of identity theft. There is a lack of studies on identity theft and its determinants. The purpose of the research is therefore to assist with the prevention of identity theft by determining the effect that information-sharing on social media has on the risk of individuals becoming identity theft victims. The details of reported identity theft victims were collected from the South African Fraud Prevention Services. Data on individuals' information-sharing habits on social media networks, like Facebook and LinkedIn, was collected via surveys that were sent to a relevant group at the Stellenbosch University. It was found that the two variables, Age and Gender, were the greatest predictors of identity theft victims. A prediction model was developed that serves as a tool to score individuals as high-risk or low-risk victims according to their attributes and social media information-sharing habits. The findings benefit research on the prevention of identity theft, by raising awareness of the potential risks the sharing of sensitive data on social media has. AFRIKAANSE OPSOMMING: Die tegnologiese era het dit moeilik gemaak vir individue om hulle persoonlike inligting te beskerm. Identiteitsdiefstal is 'n voorbeeld hiervan en veroorsaak lyding onder slagoffers. Oortreders, skuldig aan hierdie misdaad, gebruik die identiteite van hulle slagoffers bloot vir vermaak of bedrog. Die vooruitgaan van tegnologie en die totstandkoming van sosiale media het dit vir die mens vergemaklik, om persoonlike inligting te deel sonder die gepaste voorsorgmaatreëls. Daar is 'n tekort aan inligting rakende studies oor identiteitsdiefstal en die bepalers daarvan. Die doel van hierdie navorsing is om by te dra tot die voorkoming van identiteitsdiefstal, deur die tendense te bepaal in die persoonlike inligting wat sosiale media gebruikers op die netwerke verskaf, vir beide die wat al slagoffers was of nie. Inligting van verklaarde identiteitsdiefstal slagoffers is verkry vanaf die South African Fraud Prevention Services. Steekproefopnames is uitgestuur na relevante groepe in die Stellenbosch Universiteit rekenaar netwerk. Die inligting rakende individue se gewoontes om persoonlike inligting op sosiale media netwerke, soos Facebook en LinkedIn te deel, is verkry van die bogenoemde steekproefopnames. Ouderdom en Geslag is gevind as die kernbepalers van identiteitsdiefstal slagoffers. 'n Model is ontwikkel wat gedien het as 'n instrument, om individue as hoë- of lae-risiko slagoffers te bepunt, volgens hulle kenmerke en die persoonlike inligting wat hul op sosiale media deel. Die bevindinge dra by tot die navorsing rakende die voorkoming van identiteitsdiefstal deur die bewusmaking van die potensiële risikos, wat gepaard gaan daarmee om sensitiewe inligting op sosiale media te deel. 2017-02-17T16:39:38Z 2017-03-29T12:14:02Z 2017-02-17T16:39:38Z 2017-03-29T12:14:02Z 2017-03 Thesis http://hdl.handle.net/10019.1/101149 en_ZA Stellenbosch University 215 pages application/pdf Stellenbosch : Stellenbosch University
spellingShingle Identity theft
UCTD
Social media
Data mining
Michau, Nicola
Identity theft risk quantification for social media users
title Identity theft risk quantification for social media users
title_full Identity theft risk quantification for social media users
title_fullStr Identity theft risk quantification for social media users
title_full_unstemmed Identity theft risk quantification for social media users
title_short Identity theft risk quantification for social media users
title_sort identity theft risk quantification for social media users
topic Identity theft
UCTD
Social media
Data mining
url http://hdl.handle.net/10019.1/101149
work_keys_str_mv AT michaunicola identitytheftriskquantificationforsocialmediausers