International Journal On Cyber Situational Awareness (IJCSA)
ISSN: (Print) 2057-2182 ISSN: (Online) 2057-2182
DOI: 10.22619/IJCSA
Published Semi-annually. Est. 2014
Editor-in-Chief:
Dr Cyril Onwubiko, Chair – Cyber Security & Intelligence, E-Security Group, Research Series, London, UK; IEEE UK & Ireland Section Secretary
Associate Editors:
Professor Frank Wang, Head of School / Professor of Future Computing, Chair IEEE Computer Society, UK&RI, School of Computing, University of Kent, Canterbury, UK
Dr Thomas Owens, Senior Lecturer & Director of Quality, Department of Electronic and Computer Engineering, Brunel University, London, UK
Predicting the performance of users as human sensors of security threats in social media
Ryan Heartfield and George Loukas
Abstract:
While the human as a sensor concept has been utilised extensively for the detection of threats to safety and security in physical space, especially in emergency response and crime reporting, the concept is largely unexplored in the area of cyber security. Here, we evaluate the potential of utilising users as human sensors for the detection of cyber threats, specifically on social media. For this, we have conducted an online test and accompanying questionnaire-based survey, which was taken by 4,457 users. The test included eight realistic social media scenarios (four attack and four nonattack) in the form of screenshots, which the participants were asked to categorise as “likely attack” or “likely not attack”. We present the overall performance of human sensors in our experiment for each exhibit, and also apply logistic regression and Random Forest classifiers to evaluate the feasibility of predicting that performance based on different characteristics
of the participants. Such prediction would be useful where accuracy of human sensors in detecting and reporting social media security threats is important. We identify features that are good predictors of a human sensor’s performance and evaluate them in both a theoretical ideal case and two more realistic cases, the latter corresponding to limited access to a user’s characteristics.
Keywords: —Social media, computer security, semantic attacks, phishing, social engineering, human as a sensor.
ISSN: 2057-2182
Volume 1. No. 1
DOI: 10.22619/IJCSA.2016.100106
Date: Nov. 2016
Reference to this paper should be made as follows: Heartfield, R and Loukas, G. (2015). Predicting the Performance of Users as Human Sensors of Security Threats in Social Media. International Journal on Cyber Situational Awareness, Vol. 1, No. 1, pp110-129.