A taxonomy of attacks and a survey of defence mechanisms for semantic social engineering attacks
- Submitting institution
-
University of Greenwich
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 15016
- Type
- D - Journal article
- DOI
-
10.1145/2835375
- Title of journal
- ACM Computing Surveys (CSUR)
- Article number
- 37
- First page
- -
- Volume
- 48
- Issue
- 3
- ISSN
- 0360-0300
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2015
- 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
-
1
- Research group(s)
-
-
- Citation count
- 36
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is the first work that systematically identified the common underlying characteristics of cyber attacks that exploit human deception. Through this process, we were able to identify similarities between seemingly different attacks which have traditionally required different technical security systems to counter. It motivated the development of the human-as-security-sensor paradigm of providing the user the means to report attacks that humans can recognise but technical systems cannot. The corresponding PhD was nominated for BCS dissertation of the year in 2018. It also provided the framework for the social engineering attacks used in EPSRC CHAI, EPSRC COCOON and H2020 TRILLION.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
