Panning for gold : automatically analysing online social engineering attack surfaces
- Submitting institution
-
The University of Lancaster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 154337956
- Type
- D - Journal article
- DOI
-
10.1016/j.cose.2016.12.013
- Title of journal
- Computers and Security
- Article number
- -
- First page
- 18
- Volume
- 69
- Issue
- -
- ISSN
- 0167-4048
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
B - Data Science
- Citation count
- 13
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents a new method for analysing organisational vulnerability to social engineering attacks through employees on social media. The approach is demonstrated through a comprehensive analysis of critical national infrastructure companies. The paper was published in a leading Cyber Security journal, and has been highly cited in an active multidisciplinary field. The research was funded by an EPSRC Impact Acceleration Award with Xyone Cyber Security, and was informed by consultation with a range of industry and government stakeholders, including interviews with expert social engineering penetration testers, and evaluation of the resulting open source software with a range of organisations.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
