DBIS

• Privacy Enhancing Technologies for Data Science (SS 2025)

• Aligning Regulatory Requirements with Industry Standards: Creating Transferable Compliance Guidelines (
  Open
  )
• The impact of privacy-enhancing technologies on the quality of services on power grid systems (
  Open
  )
• An evaluation methodology for cyber security on (smart) grid systems (
  Open
  )
• The overhead of security-by-design requirements on current power grid systems (
  Open
  )
• Instruction-Based and Human Feedback-Driven Automation of LLM-Assisted Cybersecurity Playbook Translation into a Standardized, Machine-Readable Format (
  Running
  )
• An Ontology-Based Approach for Incident Response Playbook Selection in Industrial Control Systems using multi-criteria analysis (
  Running
  )
• Generating security playbooks from attack-defense trees using Large Language Models (
  Running
  )
• LLM-Assisted Cybersecurity Playbook Generation Based on Existing Playbooks and Retrieval-Augmented Techniques (
  Finished
  )
• Enhancing Spam Email Detection via Sentiment-Modification using LLMs (
  Finished
  )
• Reasoning-based LLM enhancement for the cybersecurity playbook translation into a standardised format (
  Finished
  )
• Supervised fine-tuning LLMs for cybersecurity playbook translation (
  Finished
  )
• Prompt Engineering for Translating unstructured playbooks into CACAO standard with the help of Large Language Models (
  Finished
  )
• Towards a Data Space for Cyber Threat Intelligence (
  Finished
  )
• Estimation of Individual Privacy Risk in Data Sharing using Predictive Models (
  Finished
  )
• Anomaly detection on encrypted data in industrial control systems (
  Finished
  )
• Privacy-Preserving Federated Learning for Phishing Detection (
  Finished
  )
• Cryptographic-based Privacy-Preserving Machine Learning for URL Phishing Detection (
  Finished
  )
• Automatic Response and Recovery of Phishing Email (
  Finished
  )

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