Closing the Gap: Achieving Better Accuracy-Robustness Tradeoffs against Query-Based Attacks

no code implementations • 15 Dec 2023 • Pascal Zimmer, Sébastien Andreina, Giorgia Azzurra Marson, Ghassan Karame

Although promising, existing defenses against query-based attacks share a common limitation: they offer increased robustness against attacks at the price of a considerable accuracy drop on clean samples.

BaFFLe: Backdoor detection via Feedback-based Federated Learning

no code implementations • 4 Nov 2020 • Sebastien Andreina, Giorgia Azzurra Marson, Helen Möllering, Ghassan Karame

In this paper, we propose Backdoor detection via Feedback-based Federated Learning (BAFFLE), a novel defense to secure FL against backdoor attacks.

Federated Learning Model Poisoning

ReplicaTEE: Enabling Seamless Replication of SGX Enclaves in the Cloud

no code implementations • 13 Sep 2018 • Claudio Soriente, Ghassan Karame, Wenting Li, Sergey Fedorov

With the proliferation of Trusted Execution Environments (TEEs) such as Intel SGX, a number of cloud providers will soon introduce TEE capabilities within their offering (e. g., Microsoft Azure).

Cryptography and Security