1 citations · 1 across the 8 of their papers we have counts for
8 papers
MASCing: Configurable Mixture-of-Experts Behavior via Activation Steering Masks
Jona te Lintelo, Lichao Wu, Marina Krček +2
Mixture-of-Experts (MoE) architectures in Large Language Models (LLMs) have significantly reduced inference costs through sparse activation. However, this sparse activation paradig…
Backdoor Attacks on Decentralised Post-Training
Oğuzhan Ersoy, Nikolay Blagoev, Jona te Lintelo +3
Decentralised post-training of large language models utilises data and pipeline parallelism techniques to split the data and the model. Unfortunately, decentralised post-training c…
Backdoor Directions in Vision Transformers
Sengim Karayalcin, Marina Krcek, Pin-Yu Chen +1
This paper investigates how Backdoor Attacks are represented within Vision Transformers (ViTs). By assuming knowledge of the trigger, we identify a specific ``trigger direction'' i…
SoK: The Last Line of Defense: On Backdoor Defense Evaluation
Gorka Abad, Marina Krček, Stefanos Koffas +7
Backdoor attacks pose a significant threat to deep learning models by implanting hidden vulnerabilities that can be activated by malicious inputs. While numerous defenses have been…
NoMod: A Non-modular Attack on Module Learning With Errors
Cristian Bassotto, Ermes Franch, Marina Krček +1
The advent of quantum computing threatens classical public-key cryptography, motivating NIST's adoption of post-quantum schemes such as those based on the Module Learning With Erro…
Interpreting Emergent Features in Deep Learning-based Side-channel Analysis
Sengim Karayalçin, Marina Krček, Stjepan Picek
Side-channel analysis (SCA) poses a real-world threat by exploiting unintentional physical signals to extract secret information from secure devices. Evaluation labs also use the s…
Label Inference Attacks against Node-level Vertical Federated GNNs
Marco Arazzi, Mauro Conti, Stefanos Koffas +4
Federated learning enables collaborative training of machine learning models by keeping the raw data of the involved workers private. Three of its main objectives are to improve th…
Modeling Strong Physically Unclonable Functions with Metaheuristics
Carlos Coello Coello, Marko Djurasevic, Domagoj Jakobovic +2
Evolutionary algorithms have been successfully applied to attacking Physically Unclonable Functions (PUFs). CMA-ES is recognized as the most powerful option for a type of attack ca…