ÖIAT Research

The Austrian Institute for Applied Telecommunications (ÖIAT) has been promoting the competent, safe and responsible use of digital media for more than 20 years. Together with our partners, we conduct research on current topics related to the digital world. On this page we provide an overview of past and current research projects.

Filter

Artificial Intelligence and Consumer Protection

2021/10 – 2022/09
Artificial Intelligence Consumer Protection

The project ‘Artificial Intelligence and Consumer Protection’ is dedicated to the overarching question of how consumer protection actors are challenged on the topic of artificial intelligence (AI).

Details

SINBAD - Security and Prevention of Fake-Shop Fraud with Measures of Digital Forensics

2020/10 – 2022/09
Fraud Fraud Detection Online Shopping

The SINBAD project deepens research into e-commerce fraud and aims to enhance multi-task machine learning models. It will proactively monitor newly registered domains within the DACH region, conducting comprehensive analyses of modular systems, pricing structures, product categories of fraudulent shops, and social media advertising tactics used by online fraudsters. The project’s objective is to safeguard consumers through evidence-based preventive measures and timely alerts.

Details

CyberSec - Cybersecurity for SME

2021/09 – 2022/03
Cybercrime Cybersecurity SME

Cybercrime is a growing threat for SMEs in Austria, against which technical protection and conventional training do not have the desired effect - because the human factor remains the greatest weakness in cybersecurity measures. The CyberSec project is therefore developing cybercrime simulation methods and tools that focus on strengthening employees' expertise.

Details

PRIMMING - Monitoring of Price Discrimination in Personalised Pricing for E-Commerce through Machine-Based Learning

2019/10 – 2022/03
Discrimination & Bias Dynamic Pricing Online Shopping

PRIMMING aims to find evidence for price discrimination and dynamic pricing by developing a framework, in which personas, their behaviour and scenarios are modelled. These are to be tested automatically in controlled measurements and the results are to be compared with a control group of real-time users. The objective is to empirically determine the forms and prevalence of dynamic pricing in Austria and to further inquire into discriminations occurring in this context such as related to gender.

Details

Identity Theft - Impacts on Victims and Pathways to Support

2021/09 – 2022/02
Consumer Protection Fraud Fraud Detection

Identity theft is on the rise, impacting both businesses and consumers. In 2019, approximately eleven percent of Austrians reported having been affected by identity theft. As stolen data is exploited for criminal activities, the repercussions for individuals can be severe. This study will examine the phenomenon of online identity theft from a consumer perspective, aiming to identify key unresolved issues and develop actionable recommendations for protection and prevention.

Details

DETECT - Real-Time Protection Against Fake Shops Through Community-Driven AI

2020/12 – 2021/11
Fraud Fraud Detection Gamification Online Shopping

The goal of the DETECT project is to transform the Fake-Shop Detector into a community-driven tool using gamification, enhancing its effectiveness in identifying online fraud. This initiative aims to test ways to engage users in key stages of the fake shop detection process, encouraging them to participate in the verification process by answering simple questions in an engaging, interactive manner.

Details

MAL2 - MAchine Learning Detection of MALicious Content

2019/01 – 2020/12
Artificial Intelligence Fraud Fraud Detection Online Shopping

In the MAL2 (MAchine Learning detection of MALicious content) project, deep neural networks and unsupervised learning are used for the automated detection of a) fraudulent fake shops and b) malicious Android apps (PHAs) and thus contribute to improving cybercrime prevention.

Details

KOSOH - Consumer Protection in e-Commerce

2018/09 – 2020/08
Artificial Intelligence Fraud Fraud Detection Online Shopping

KOSOH is an important preventive measure in the detection of fake-shops. The goal 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) 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.

Details

Online Reviews - Information on Legal Issues Relating to Review Platforms

2019/11 – 2020/06
Consumer Protection Online Shopping

More and more consumers are using review sites. They are increasingly basing their purchasing decisions on the reviews and recommendations of other consumers. At the same time, consumers are sharing their own experiences of products and services to help other consumers with their purchasing decisions. The project answers legal questions related to review platforms and provides consumers with practical tips on how to use review platforms.

Details

KMU 4.0

2018/04 – 2020/03
SME

In particular, SMEs often lack the resources to deal with the possibilities of digitization, new technologies and their exploitation possibilities. The ACR institutes can play a key role as brokers between large companies, the research community and Austrian SMEs.

Details