KIRAS Security Research

F&E-Dienstleistungen > Call 2017

KOSOH

KOnsumentInnenSchutz im OnlineHandel

Online shopping has become commonplace, with 61.6% of Austrians already using this form of shopping. The turnover of the top 250 online shops in Austria in 2016 was € 2.3 billion, with a growth of nine percent compared to the previous year. Due to the popularity, also the market for so-called "fake shops" – i.e. ripping of customers with fraudulent and fake portals – has been ever growing since and is one of the largest threats for Austrian customers according to cybercrime reports. One of the most prominent examples in the media was the damage of 440k euros caused by a single Munich native who offered about 750 popular products such as coffee machines, mobile phones, game consoles in 21 different online shops - but none of the products ever got delivered. Besides counterfeit sales platforms with trademark infringed goods, one of the primarily target for fake-shops include offerings of digital goods (e.g. content streaming, navigation software, etc.). Exposing such fake offerings is an extremely difficult task especially for under-savvy online consumers (such as senior citizens). Since it is almost impossible to track down the fraudsters much less to enforce consumer rights in such situations, it is important to take preventive measures. The Internet Ombudsman was established as e-commerce service in July 2013. On its platform Austrian consumers receive regular updates, warnings and tip how to protect themselves against online fraud. In addition, a blacklist of fraudulent online shops is maintained. One hundred and fifty online shops are submitted every week for manual inspection. One of the biggest problems with fake-shops is that, as soon as they are exposed, they immediately disappear from the internet and are put back online in a slightly modified form and under new domains. Often, dozens or more of these copies exist online at the same time. Therefore, it's important to act quickly! The aim of the KOSOH project is to capture the intrinsic knowledge of ÖIAT employees in their abilities of identifying fake-shops and to provide technical methods for assisting and accelerating their work. This includes applying AITs expertise in machine learning (neural networks) technologies for automatically classifying web pages based on their structural information (such as CSS, DOM, Javascript, referenced media, etc.), as well as using image similarity tools for identifying kite marks. The model of fake shop measures which are built up and trained in KOSOH allow providing similarity and risk assessments scores for any online-shop. KOSOH is an important preventive measure in the detection of fake-shops and will be available as browser plugin for Austrian consumers. A central component of the project is the final evaluation of existing counter measures. The report takes into account existing protection mechanisms, their shortcomings the findings, quality and reliability of the given KOSOH approach and concludes with recommendations for policy makers.

ProjektleiterIn / Name und Institut/Unternehmen 
Andrew Lindley, Research Engineer, Center for Digital Safety & Security, AIT Austrian Institute of Technology GmbH 

Auflistung der weiteren Projekt? bzw. KooperationspartnerInnen
Österreichische Institut für angewandte Telekommunikation (ÖIAT)
Anahid Naghibzadeh-Jalali, AIT Austrian Institute of Technology GmbH
Louise Horvath, Österreichisches Institut für angewandte Telekommunikation ÖIAT
Thorsten Behrens, Österreichisches Institut für angewandte Telekommunikation ÖIAT
Sandra Pöheim, Österreichisches Institut für angewandte Telekommunikation ÖIAT
Jakob Kalina, Österreichisches Institut für angewandte Telekommunikation ÖIAT

Name des/der EinreicherIn und/oder ProjektleiterIn: 
Andrew Lindley
Adresse: Giefinggasse 4, 1210 Wien
Telefon +436648157848
E-Mail: andrew.lindley@ait.ac.at  

Kontakt Medienanfragen: 
Michael Mürling
Adresse: Giefinggasse 4, 1210 Wien
Telefon: +43 50550 4126
E-Mail: michael.mürling@ait.ac.at
WWW: https://www.ait.ac.at/themen/data-science/