Whitty, M;
Edwards, M;
Levi, M;
Peersman, C;
Rashid, A;
Sasse, MA;
Sorell, T;
(2017)
Ethical and Social Challenges with developing Automated Methods to Detect and Warn potential victims of Mass-marketing Fraud (MMF).
In: Barrett, R and Cummings, R and Agichtein, E and Gabrilovich, E, (eds.)
WWW '17: Companion Proceedings of the 26th International Conference on World Wide Web Companion.
(pp. pp. 1311-1314).
Association for Computing Machinery (ACM): New York, NY, USA.
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Abstract
Mass-marketing frauds (MMFs) are on the increase. Given the amount of monies lost and the psychological impact of MMFs there is an urgent need to develop new and effective methods to prevent more of these crimes. This paper reports the early planning of automated methods our interdisciplinary team are developing to prevent and detect MMF. Importantly, the paper presents the ethical and social constraints involved in such a model and suggests concerns others might also consider when developing automated systems.
| Type: | Proceedings paper |
|---|---|
| Title: | Ethical and Social Challenges with developing Automated Methods to Detect and Warn potential victims of Mass-marketing Fraud (MMF) |
| Event: | 26th International Conference on World Wide Web (WWW '17) |
| Location: | Perth, Australia |
| Dates: | 03 April 2017 - 07 April 2017 |
| ISBN-13: | 9781450349147 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3041021.3053891 |
| Publisher version: | http://dx.doi.org/10.1145/3041021.3053891 |
| Language: | English |
| Additional information: | Copyright © 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License (http://dx.doi.org/10.1145/3041021.3053891). |
| Keywords: | ACM proceedings, mass-marketing fraud, online scams, cybercrime, cybersafety |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1541241 |
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