A semi-automated security advisory system to resist cyber-attack in social networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

Social networking sites often witness various types of social engineering (SE) attacks. Yet, limited research has addressed the most severe types of social engineering in social networks (SNs). The present study investigates the extent to which people respond differently to different types of attack in a social network context and how we can segment users based on their vulnerability. In turn, this leads to the prospect of a personalised security advisory system. 316 participants have completed an online-questionnaire that includes a scenario-based experiment. The study result reveals that people respond to cyber-attacks differently based on their demographics. Furthermore, people’s competence, social network experience, and their limited connections with strangers in social networks can decrease their likelihood of falling victim to some types of attacks more than others.

LanguageEnglish
Title of host publicationComputational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings
Place of PublicationCham
PublisherSpringer-Verlag
Pages146-156
Number of pages11
Volume11055
ISBN (Print)9783319984421
DOIs
Publication statusPublished - 8 Aug 2018
Event10th International Conference on Computational Collective Intelligence, ICCCI 2018 - Bristol, United Kingdom
Duration: 5 Sep 20187 Sep 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11055 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Computational Collective Intelligence, ICCCI 2018
CountryUnited Kingdom
CityBristol
Period5/09/187/09/18

Fingerprint

Security systems
Resist
Social Networks
Attack
Engineering
Social Networking
Vulnerability
Questionnaire
Likelihood
Experiments
Decrease
Scenarios
Experiment

Keywords

  • advisory system
  • social engineering
  • social networks
  • cyber security
  • cyber attacks

Cite this

Albladi, S. M., & Weir, G. R. S. (2018). A semi-automated security advisory system to resist cyber-attack in social networks. In Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings (Vol. 11055, pp. 146-156). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11055 LNAI). Cham: Springer-Verlag. https://doi.org/10.1007/978-3-319-98443-8_14
Albladi, Samar Muslah ; Weir, George R.S. / A semi-automated security advisory system to resist cyber-attack in social networks. Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings. Vol. 11055 Cham : Springer-Verlag, 2018. pp. 146-156 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Albladi, SM & Weir, GRS 2018, A semi-automated security advisory system to resist cyber-attack in social networks. in Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings. vol. 11055, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11055 LNAI, Springer-Verlag, Cham, pp. 146-156, 10th International Conference on Computational Collective Intelligence, ICCCI 2018, Bristol, United Kingdom, 5/09/18. https://doi.org/10.1007/978-3-319-98443-8_14

A semi-automated security advisory system to resist cyber-attack in social networks. / Albladi, Samar Muslah; Weir, George R.S.

Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings. Vol. 11055 Cham : Springer-Verlag, 2018. p. 146-156 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11055 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Albladi SM, Weir GRS. A semi-automated security advisory system to resist cyber-attack in social networks. In Computational Collective Intelligence - 10th International Conference, ICCCI 2018, Proceedings. Vol. 11055. Cham: Springer-Verlag. 2018. p. 146-156. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-98443-8_14