6 papers
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…
Removing the Trigger, Not the Backdoor: Alternative Triggers and Latent Backdoors
Gorka Abad, Ermes Franch, Stefanos Koffas +1
Current backdoor defenses assume that neutralizing a known trigger removes the backdoor. We show this trigger-centric view is incomplete: \emph{alternative triggers}, patterns perc…
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…
CatBack: Universal Backdoor Attacks on Tabular Data via Categorical Encoding
Behrad Tajalli, Stefanos Koffas, Stjepan Picek
Backdoor attacks in machine learning have drawn significant attention for their potential to compromise models stealthily, yet most research has focused on homogeneous data such as…
Towards Backdoor Stealthiness in Model Parameter Space
Xiaoyun Xu, Zhuoran Liu, Stefanos Koffas +1
Recent research on backdoor stealthiness focuses mainly on indistinguishable triggers in input space and inseparable backdoor representations in feature space, aiming to circumvent…
EmoBack: Backdoor Attacks Against Speaker Identification Using Emotional Prosody
Coen Schoof, Stefanos Koffas, Mauro Conti +1
Speaker identification (SI) determines a speaker's identity based on their spoken utterances. Previous work indicates that SI deep neural networks (DNNs) are vulnerable to backdoor…