Picture of boy being examining by doctor at a tuberculosis sanatorium

Understanding our future through Open Access research about our past...

Strathprints makes available scholarly Open Access content by researchers in the Centre for the Social History of Health & Healthcare (CSHHH), based within the School of Humanities, and considered Scotland's leading centre for the history of health and medicine.

Research at CSHHH explores the modern world since 1800 in locations as diverse as the UK, Asia, Africa, North America, and Europe. Areas of specialism include contraception and sexuality; family health and medical services; occupational health and medicine; disability; the history of psychiatry; conflict and warfare; and, drugs, pharmaceuticals and intoxicants.

Explore the Open Access research of the Centre for the Social History of Health and Healthcare. Or explore all of Strathclyde's Open Access research...

Image: Heart of England NHS Foundation Trust. Wellcome Collection - CC-BY.

Strathprints

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

Albladi, Samar Muslah and Weir, George 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. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11055 . Springer-Verlag, Cham, pp. 146-156. ISBN 9783319984421

[img]
Preview
 Text (Albladi-Weir-LNCS-2018-A-semi-automated-security-advisory-system-to-resist-cyber-attack-in-social-networks)
Albladi_Weir_LNCS_2018_A_semi_automated_security_advisory_system_to_resist_cyber_attack_in_social_networks.pdf
Accepted Author Manuscript
Download (326kB) | Preview

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.

Item type: Book Section
ID code: 65715
Notes: The final version is available online at https://doi.org/10.1007/978-3-319-98443-8_14
Keywords: advisory system, social engineering, social networks, cyber security, cyber attacks, Electronic computers. Computer science, Theoretical Computer Science, Computer Science(all)
Subjects: Science > Mathematics > Electronic computers. Computer science
Department: Faculty of Science > Computer and Information Sciences
Depositing user: Pure Administrator
Date deposited: 09 Oct 2018 02:43
Last modified: 27 Mar 2019 20:31
Related URLs:
URI: https://strathprints.strath.ac.uk/id/eprint/65715
Export data:
CORE (COnnecting REpositories)