activity
20192026
most citedUniversal Backdoor Attacks

1 citations · 1 across the 8 of their papers we have counts for

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cs.CR2026

Semantic Watermarking with Order-Robust Detection over Sub-sentence Units

Abdulrahman Diaa, Jonathan Petit, Florian Kerschbaum

Semantic watermarks tie the mark to sentence meaning rather than token choices, promising robustness to content-preserving edits. However, the detector only observes attacker-suppl…

cs.CR2026

ZipPIR: High-throughput Single-server PIR without Client-side Storage

Rasoul Akhavan Mahdavi, Abdulrahman Diaa, Florian Kerschbaum

Private Information Retrieval (PIR) allows a client to privately access a database without revealing which element is accessed. Initial PIR protocols based on Ring Learning with Er…

cs.CR2026

Backdooring Bias in Large Language Models

Anudeep Das, Prach Chantasantitam, Gurjot Singh +3

Large language models (LLMs) are increasingly deployed in settings where inducing a bias toward a certain topic can have significant consequences, and backdoor attacks can be used…

cs.CR2024

SilentWood: Private Inference Over Gradient-Boosting Decision Forests

Ronny Ko, Abdelkarim Kati, Robin Geelen +8

Gradient boosting decision forests, used by XGBoost or AdaBoost, offer higher accuracy and lower training times than decision trees for large datasets. Protocols for private infere…

cs.CR2024

FastLloyd: Federated, Accurate, Secure, and Tunable -Means Clustering with Differential Privacy

Abdulrahman Diaa, Thomas Humphries, Florian Kerschbaum

We study the problem of privacy-preserving -means clustering in the horizontally federated setting. Existing federated approaches using secure computation suffer from substantia…

cs.CR2023

PEPSI: Practically Efficient Private Set Intersection in the Unbalanced Setting

Rasoul Akhavan Mahdavi, Nils Lukas, Faezeh Ebrahimianghazani +7

Two parties with private data sets can find shared elements using a Private Set Intersection (PSI) protocol without revealing any information beyond the intersection. Circuit PSI p…