12 citations · 21 across the 14 of their papers we have counts for
6 papers · 1 filter
SoK: Privacy Attacks on Machine Learning via Explainable AI
Abdullah Caglar Oksuz, Anisa Halimi, Erman Ayday
Machine learning explanations reveal model behavior beyond predictions, creating attack surfaces for model confidentiality and data privacy. We systematize 25 studies that exploit…
Persona-Conditioned Adversarial Prompting (PCAP): Multi-Identity Red-Teaming for Enhanced Adversarial Prompt Discovery
Cristian Morasso, Anisa Halimi, Muhammad Zaid Hameed +1
Existing automated red-teaming pipelines often miss attacks that depend on attacker identity, framing, or multi-turn tactics. This under-coverage underestimates real-world risk. We…
Towards a Re-evaluation of Data Forging Attacks in Practice
Mohamed Suliman, Anisa Halimi, Swanand Kadhe +2
Data forging attacks provide counterfactual proof that a model was trained on a given dataset, when in fact, it was trained on another. These attacks work by forging (replacing) mi…
Facilitating Federated Genomic Data Analysis by Identifying Record Correlations while Ensuring Privacy
Leonard Dervishi, Xinyue Wang, Wentao Li +4
With the reduction of sequencing costs and the pervasiveness of computing devices, genomic data collection is continually growing. However, data collection is highly fragmented and…
Efficient Quantification of Profile Matching Risk in Social Networks
Anisa Halimi, Erman Ayday
Anonymous data sharing has been becoming more challenging in today's interconnected digital world, especially for individuals that have both anonymous and identified online activit…
Profile Matching Across Unstructured Online Social Networks: Threats and Countermeasures
Anisa Halimi, Erman Ayday
In this work, we propose a profile matching (or deanonymization) attack for unstructured online social networks (OSNs) in which similarity in graphical structure cannot be used for…