Cybersecurity research from Austria

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Gesponserter Beitrag

Austrian security research is growing. The new Kybernet-Pass programme focuses on cyber security and supports research, companies and authorities in making Austria’s digital future more secure.

Threats coming from the digital world are now part of everyday life. Anyone can become a victim – companies are blackmailed digitally and citizens receive calls from fraudsters. In order to better protect the population and to raise awareness, the national security research funding framework named Austrian Safety Pin was created, consisting of the civil security research programme KIRAS, the defence research programme FORTE, and will be completed in 2024 by the cyber security research programme Kybernet- Pass (K-PASS). Together they fund research projects with an average of 19 million euros per year to keep Austria ready for the future in terms of security policy in unstable times.

Forschen für die Sicherheit
Be it the constantly growing field of cyber security, the support of first responders, the protection of critical infrastructures or concepts for securing the supply chains that ensure the supply of the Austrian population with staple foods as well as the most important raw materials – it is crucial that the research projects contribute to preparing the actual but also the economic security and well-being of Austrians for future challenges. An essential means to this end is to make the research results usable. Only if findings are applied in a timely manner can they unfold their full benefit and help in overcoming current crises or even prevent the emergence of future crisis. Successful solutions such as cybersecurity from Austria can strengthen the domestic economy, not least if they are exported as concepts to other countries by means of technology transfer and thus contribute to increasing value creation and securing jobs in Austria. To provide some examples in addition to theory and figures, we would like to present some Austrian- led projects we supported recently.

KIRAS projects with added value SINBAD
SINBAD
Security and prevention of organised online order fraud for users through digital forensics measures. The SINBAD project is researching the automated detection of fake shops in order to pro-actively protect consumers from internet fraud.
Prevention and speed are key instruments to protect consumers from fraudulent offers in e-commerce. However, reports from affected consumers come in too late and often the damage is done before a warning can be published. The Austrian initiative Watchlist Internet of the ÖIAT is working on intensifying the technological applicability of integrated procedures of automatic detection based on machine learning. Significant successes have already been achieved in preliminary projects with consortium partners under the leadership of the AIT’s Center for Digital Safety and Security: These include the classification of fake shops by fingerprints in the source code with machine learning detection rates of over 90% and the publication of a comprehensive corpus data set.

Safe space: Online violence against women in (former) relationships
With the increasing digitisation of all areas of social life, the number of abusive uses or increasingly disappearing. Thus, even a spatial separation – such as fleeing to a women’s shelter – cannot exclude that the affected women will not continue to be exposed to online violence. The current situation for women who are affected by online violence from their (ex-)partner shows that despite high estimates in prevalence figures, there is a lack of social science knowledge to be able to develop handling strategies in relevant fields of practice (social work, police, justice) that meet the need of the affected women for security in their private sphere.
Those affected often do not find a safe space where they could protect themselves from the permanent threat and control. Previous research results show that the sphere of violence is increased by technological means. Spaces that can potentially offer protection for the affected women are thus increasingly increasingly disappearing. Thus, even a spatial separation – such as fleeing to a women’s shelter – cannot exclude that the affected women will not continue to be exposed to online violence. The current situation for women who are affected by online violence from their (ex-)partner shows that despite high estimates in prevalence figures, there is a lack of social science knowledge to be able to develop handling strategies in relevant fields of practice (social work, police, justice) that meet the need of the affected women for security in their private sphere. This reveals a gap between the current state of knowledge and the current state of technology.

Defalsif-AI
Detection of false information by means of artificial intelligence. Defalsif-AI addresses in the context of media-forensic tools (hybrid threats / fake news) in particular politically motivated disinformation, which weakens or threatens political and state institutions of our democracy – e.g. influencing elections – and thus ultimately public trust in political and state institutions. The research focuses on audiovisual media forensics, text analysis and their multimodal fusion with the help of artificial intelligence (AI). The focus is on the comprehensible and interpretable presentation of the results in order to reach and optimally support the broadest possible user base. The aim of the project is to demonstrate a proof-of-concept tool for the analysis of digital content on the internet, which enables an initial assessment of the content (text, image, video, audio) for credibility/authenticity and thus creates the basis for further recommendations for action. A comprehensive analysis and assessment of the media forensic tool from a legal and social science perspective, the derivation of application- oriented, technological and organisational measures as well as an exploitation plan for the future operation of disinformation analysis platforms that conform to the rule of law round off the project.