Tabdoor: Backdoor Vulnerabilities in Transformer-based Neural Networks for Tabular Data

no code implementations • 13 Nov 2023 • Bart Pleiter, Behrad Tajalli, Stefanos Koffas, Gorka Abad, Jing Xu, Martha Larson, Stjepan Picek

Deep Neural Networks (DNNs) have shown great promise in various domains.

Backdoor Attack

On Feasibility of Server-side Backdoor Attacks on Split Learning

no code implementations • 19 Feb 2023 • Behrad Tajalli, Oguzhan Ersoy, Stjepan Picek

Recent studies demonstrate that collaborative learning models, specifically federated learning, are vulnerable to security and privacy attacks such as model inference and backdoor attacks.

Backdoor Attack Federated Learning

SoK: A Systematic Evaluation of Backdoor Trigger Characteristics in Image Classification

no code implementations • 3 Feb 2023 • Gorka Abad, Jing Xu, Stefanos Koffas, Behrad Tajalli, Stjepan Picek, Mauro Conti

Nevertheless, it is vulnerable to backdoor attacks that modify the training set to embed a secret functionality in the trained model.

Image Classification Transfer Learning