Naslov
Estimating real world privacy risk scenarios

Autori
Vuković, Marin ; Skočir, Pavle ; Katušić, Damjan ; Jevtić, Dragan ; Trutin, Daniela ; Delonga, Luka

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 13th International Conference on Telecommunications / Plank, Thomas - Graz : Graz University of Technology, 2015, 1-7

ISBN
978-1-4799-8971-3

Skup
The 13th International Conference on Telecommunications

Mjesto i datum
Graz, Austrija, 13.07.2015. - 15.07.2015

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
user privacy; risk scenario; privacy risk calculator

Sažetak
User privacy is becoming an issue on the Internet due to common data breaches and various security threats. Services tend to require private user data in order to provide more personalized content and users are typically unaware of potential risks to their privacy. This paper continues our work on the proposed user privacy risk calculator based on a feedforward neural network. Along with risk estimation, we provide the users with real world example scenarios that depict privacy threats according to selected input parameters. In this paper, we present a model for selecting the most probable real world scenario, presented as a comic, and thus avoid overwhelming the user with lots of information that he/she may find confusing. Most probable scenario estimations are performed by artificial neural network that is trained with real world scenarios and estimated probabilities from real world occurrences. Additionally, we group real world scenarios into categories that are presented to the user as further reading regarding privacy risks.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

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