Detection of app collusion potential using logic programming
- Submitting institution
-
Swansea University / Prifysgol Abertawe
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 37676
- Type
- D - Journal article
- DOI
-
10.1016/j.jnca.2017.12.008
- Title of journal
- Journal of Network and Computer Applications
- Article number
- -
- First page
- 88
- Volume
- 105
- Issue
- -
- ISSN
- 1084-8045
- Open access status
- Compliant
- Month of publication
- March
- Year of publication
- 2018
- 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
-
-
- Research group(s)
-
-
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Warnings about the possibility of app collusion appeared as early as 2011. However, industry had no detection mechanisms. Thus, McAfee invited us to collaborate on the development of detection tools. The one reported here was the first to detect app collusion in the wild and adopted by McAfee: "After deployment in September 2017, this app collusion filter is now up and running as part of McAfee's global threat monitoring system on a permanent basis" (letter to MR by Irfan Asrar, McAfee, September 2017).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -