Consumer-facing technology fraud: Economics, attack methods and potential solutions
Journal article
Authors | Mohammed Aamir, Ali, Muhammad AJmal, Azad, Mario Parreno, Centeno, Feng, Hao and Aad Van, Moorsel |
---|---|
Abstract | The emerging use of modern technologies has not only benefited society but also attracted fraudsters and criminals to misuse the technology for financial benefits. Fraud over the Internet has increased dramatically, resulting in an annual loss of billions of dollars to customers and service providers worldwide. Much of such fraud directly impacts individuals, both in the case of browser-based and mobile-based Internet services, as well as when using traditional telephony services, either through landline phones or mobiles. It is important that users of the technology should be both informed of fraud, as well as protected from frauds through fraud detection and prevention systems. In this paper, we present the anatomy of frauds for different consumer-facing technologies from three broad perspectives - we discuss Internet, mobile and traditional telecommunication, from the perspectives of losses through frauds over the technology, fraud attack mechanisms and systems used for detecting and preventing frauds. The paper also provides recommendations for securing emerging technologies from fraud and attacks. |
Keywords | Consumer fraud; Car payment fraud; Fraud economics |
Year | 2019 |
Journal | Future Generation Computer Systems |
Publisher | Elsevier |
ISSN | 0167739X |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.future.2019.03.041 |
Web address (URL) | http://hdl.handle.net/10545/623788 |
hdl:10545/623788 | |
Publication dates | 11 May 2019 |
Publication process dates | |
Deposited | 28 May 2019, 10:06 |
Accepted | 18 Mar 2019 |
Contributors | Newcastle University, Derby University and University of Warwick |
File | File Access Level Open |
File |
https://repository.derby.ac.uk/item/95278/consumer-facing-technology-fraud-economics-attack-methods-and-potential-solutions
Download files
850
total views443
total downloads23
views this month3
downloads this month
Export as
Related outputs

Large-scale Data Integration Using Graph Probabilistic Dependencies (GPDs)
Zada, Muhammad Sadiq Hassan, Yuan, Bo, Anjum, Ashiq, Azad, Muhammad Ajmal, Khan, Wajahat Ali and Reiff-Marganiec, Stephan 2020. Large-scale Data Integration Using Graph Probabilistic Dependencies (GPDs). IEEE. https://doi.org/10.1109/bdcat50828.2020.00028
Persation: an IoT based personal safety prediction model aided solution
Alofe, Olasunkanmi Matthew, Fatema, Kaniz, Azad, Muhammad Ajmal and Kurugollu, Fatih 2020. Persation: an IoT based personal safety prediction model aided solution. International Journal of Computing and Digital Systems.
Privacy-preserving crowd-sensed trust aggregation in the user-centeric internet of people networks
Azad, Muhammad, Perera, Charith, Bag, Samiran, Barhamgi, Mahmoud and Hao, Feng 2020. Privacy-preserving crowd-sensed trust aggregation in the user-centeric internet of people networks. ACM Transactions on Cyber-Physical Systems. https://doi.org/10.1145/3446431
Designing privacy-aware internet of things applications
Perera, Charith, Barhamgi, Mahmoud, Bandara, Arosha K., Ajmal, Muhammad, Price, Blaine and Nuseibeh, Bashar 2019. Designing privacy-aware internet of things applications. Elsevier Information Sciences. https://doi.org/10.1016/j.ins.2019.09.061
Authentic-caller: Self-enforcing authentication in a next generation network
Azad, Muhammad Ajmal, Bag, Samiran, Perera, Charith, Barhamgi, Mahmoud and Hao, Feng 2019. Authentic-caller: Self-enforcing authentication in a next generation network. IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/tii.2019.2941724
CRT-BIoV: A cognitive radio technique for blockchain-enabled internet of vehicles
Rathee, Geetanjali, Ahmad, F., Kurugollu, Fatih, Azad, Muhammad, Iqbal, Razi and Imran, Muhammad 2020. CRT-BIoV: A cognitive radio technique for blockchain-enabled internet of vehicles. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/TITS.2020.3004718
A first look at privacy analysis of COVID-19 contact tracing mobile applications
Azad, Muhammad Ajmal, Arshad, Junaid, Akmal, Syed Muhammad Ali, Riaz, Farhan, Abdullah, Sidrah, Imran, Muhammad and Ahmad, F. 2020. A first look at privacy analysis of COVID-19 contact tracing mobile applications. IEEE Internet of Things Journal. https://doi.org/10.1109/JIOT.2020.3024180
PriVeto: a fully private two round veto protocol.
Samiran, Bag, Muhammad Ajmal, Azad and Feng, Hao 2018. PriVeto: a fully private two round veto protocol. IET Information Security. https://doi.org/10.1049/iet-ifs.2018.5115
M2M-REP: Reputation system for machines in the internet of things.
Azad, Muhammad Ajmal, Bag, Samiran, Hao, Feng and Salah, Khaled 2018. M2M-REP: Reputation system for machines in the internet of things. Computers & Security. 79, pp. 1-16. https://doi.org/10.1016/j.cose.2018.07.014
TrustVote: Privacy-preserving node ranking in vehicular networks
Muhammad AJmal, Azad, Samiran, Bag, Simon, Parkinson and Feng, Hao 2018. TrustVote: Privacy-preserving node ranking in vehicular networks. IEEE Internet of Things Journal. https://doi.org/10.1109/JIOT.2018.2880839