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Manipulation and Malicious Personalization: Exploring the Self-Disclosure Biases Exploited by Deceptive Attackers on Social Media

In the real world, the disclosure of private information to others often occurs after a trustworthy relationship has been established. Conversely, users of Social Network Sites (SNSs) like Facebook or Instagram often disclose large amounts of personal information prematurely to individuals which are...

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Detalles Bibliográficos
Autores principales: Aïmeur, Esma, Díaz Ferreyra, Nicolás, Hage, Hicham
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861322/
https://www.ncbi.nlm.nih.gov/pubmed/33733115
http://dx.doi.org/10.3389/frai.2019.00026
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author Aïmeur, Esma
Díaz Ferreyra, Nicolás
Hage, Hicham
author_facet Aïmeur, Esma
Díaz Ferreyra, Nicolás
Hage, Hicham
author_sort Aïmeur, Esma
collection PubMed
description In the real world, the disclosure of private information to others often occurs after a trustworthy relationship has been established. Conversely, users of Social Network Sites (SNSs) like Facebook or Instagram often disclose large amounts of personal information prematurely to individuals which are not necessarily trustworthy. Such a low privacy-preserving behavior is often exploited by deceptive attackers with harmful intentions. Basically, deceivers approach their victims in online communities using incentives that motivate them to share their private information, and ultimately, their credentials. Since motivations, such as financial or social gain vary from individual to individual, deceivers must wisely choose their incentive strategy to mislead the users. Consequently, attacks are crafted to each victim based on their particular information-sharing motivations. This work analyses, through an online survey, those motivations and cognitive biases which are frequently exploited by deceptive attackers in SNSs. We propose thereafter some countermeasures for each of these biases to provide personalized privacy protection against deceivers.
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spelling pubmed-78613222021-03-16 Manipulation and Malicious Personalization: Exploring the Self-Disclosure Biases Exploited by Deceptive Attackers on Social Media Aïmeur, Esma Díaz Ferreyra, Nicolás Hage, Hicham Front Artif Intell Artificial Intelligence In the real world, the disclosure of private information to others often occurs after a trustworthy relationship has been established. Conversely, users of Social Network Sites (SNSs) like Facebook or Instagram often disclose large amounts of personal information prematurely to individuals which are not necessarily trustworthy. Such a low privacy-preserving behavior is often exploited by deceptive attackers with harmful intentions. Basically, deceivers approach their victims in online communities using incentives that motivate them to share their private information, and ultimately, their credentials. Since motivations, such as financial or social gain vary from individual to individual, deceivers must wisely choose their incentive strategy to mislead the users. Consequently, attacks are crafted to each victim based on their particular information-sharing motivations. This work analyses, through an online survey, those motivations and cognitive biases which are frequently exploited by deceptive attackers in SNSs. We propose thereafter some countermeasures for each of these biases to provide personalized privacy protection against deceivers. Frontiers Media S.A. 2019-11-29 /pmc/articles/PMC7861322/ /pubmed/33733115 http://dx.doi.org/10.3389/frai.2019.00026 Text en Copyright © 2019 Aïmeur, Díaz Ferreyra and Hage. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Artificial Intelligence
Aïmeur, Esma
Díaz Ferreyra, Nicolás
Hage, Hicham
Manipulation and Malicious Personalization: Exploring the Self-Disclosure Biases Exploited by Deceptive Attackers on Social Media
title Manipulation and Malicious Personalization: Exploring the Self-Disclosure Biases Exploited by Deceptive Attackers on Social Media
title_full Manipulation and Malicious Personalization: Exploring the Self-Disclosure Biases Exploited by Deceptive Attackers on Social Media
title_fullStr Manipulation and Malicious Personalization: Exploring the Self-Disclosure Biases Exploited by Deceptive Attackers on Social Media
title_full_unstemmed Manipulation and Malicious Personalization: Exploring the Self-Disclosure Biases Exploited by Deceptive Attackers on Social Media
title_short Manipulation and Malicious Personalization: Exploring the Self-Disclosure Biases Exploited by Deceptive Attackers on Social Media
title_sort manipulation and malicious personalization: exploring the self-disclosure biases exploited by deceptive attackers on social media
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861322/
https://www.ncbi.nlm.nih.gov/pubmed/33733115
http://dx.doi.org/10.3389/frai.2019.00026
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