3 citations · 9 across the 10 of their papers we have counts for
11 papers
Few-Shot Learning for Network Intrusion Detection: Methods, Datasets, and Performance
Arne Roszeitis, Victor Jüttner, Erik Buchmann
Anomaly-based network intrusion detection systems (NIDS) are an important first line of defense. However, training NIDS for new attack types is challenging, because labeled attack…
Simulating the Resident: Generating Executable Smart Home Schedules via LLM Personas
Victor Jüttner, Xenia Wagner, Christoph Jahn +1
Smart homes have emerged as an important domain for HCI research, including work on usable security and privacy. Ideally, studies in these areas draw on datasets collected in real…
Cybersecurity Guidance for Smart Homes: A Cross-National Review of Government Sources
Victor Jüttner, Erik Buchmann
Smart homes are increasingly targeted by cyberattacks, yet residents often lack guidance when incidents occur. Since affected residents are likely to seek help from trustworthy sou…
Actionable Cybersecurity Notifications for Smart Homes: A User Study on the Role of Length and Complexity
Victor Jüttner, Charlotte S. Löffler, Erik Buchmann
The proliferation of smart home devices has increased convenience but also introduced cybersecurity risks for everyday users, as many devices lack robust security features. Intrusi…
Does Johnny Get the Message? Evaluating Cybersecurity Notifications for Everyday Users
Victor Jüttner, Erik Buchmann
Due to the increasing presence of networked devices in everyday life, not only cybersecurity specialists but also end users benefit from security applications such as firewalls, vu…
Explainable AI in Usable Privacy and Security: Challenges and Opportunities
Vincent Freiberger, Arthur Fleig, Erik Buchmann
Large Language Models (LLMs) are increasingly being used for automated evaluations and explaining them. However, concerns about explanation quality, consistency, and hallucinations…
"You don't need a university degree to comprehend data protection this way": LLM-Powered Interactive Privacy Policy Assessment
Vincent Freiberger, Arthur Fleig, Erik Buchmann
Protecting online privacy requires users to engage with and comprehend website privacy policies, but many policies are difficult and tedious to read. We present the first qualitati…
Helping Johnny Make Sense of Privacy Policies with LLMs
Vincent Freiberger, Arthur Fleig, Erik Buchmann
Understanding and engaging with privacy policies is crucial for online privacy, yet these documents remain notoriously complex and difficult to navigate. We present PRISMe, an inte…
Assessing Privacy Policies with AI: Ethical, Legal, and Technical Challenges
Irem Aydin, Hermann Diebel-Fischer, Vincent Freiberger +5
The growing use of Machine Learning and Artificial Intelligence (AI), particularly Large Language Models (LLMs) like OpenAI's GPT series, leads to disruptive changes across organiz…
Legally Binding but Unfair? Towards Assessing Fairness of Privacy Policies
Vincent Freiberger, Erik Buchmann
Privacy policies are expected to inform data subjects about their data protection rights and should explain the data controller's data management practices. Privacy policies only f…
Fairness Certification for Natural Language Processing and Large Language Models
Vincent Freiberger, Erik Buchmann
Natural Language Processing (NLP) plays an important role in our daily lives, particularly due to the enormous progress of Large Language Models (LLM). However, NLP has many fairne…