SAFELearn: Secure Aggregation for private FEderated Learning. - Hossein Fereidooni; Samuel Marchal; Markus Miettinen; Azalia Mirhoseini; Helen Möllering; Thien Duc Nguyen; Phillip Rieger; Ahmad-Reza Sadeghi; Thomas Schneider 003; Hossein Yalame; Shaza Zeitouni (IACR Cryptol. ePrint Arch., 2021)

FLGUARD: Secure and Private Federated Learning. - Thien Duc Nguyen; Phillip Rieger; Hossein Yalame; Helen Möllering; Hossein Fereidooni; Samuel Marchal; Markus Miettinen; Azalia Mirhoseini; Ahmad-Reza Sadeghi; Thomas Schneider 003; Shaza Zeitouni (IACR Cryptol. ePrint Arch., 2021)

FedCRI: Federated Mobile Cyber-Risk Intelligence. - Hossein Fereidooni; Alexandra Dmitrienko; Phillip Rieger; Markus Miettinen; Ahmad-Reza Sadeghi; Felix Madlener (NDSS, 2022)

DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection. - Phillip Rieger; Thien Duc Nguyen; Markus Miettinen; Ahmad-Reza Sadeghi (NDSS, 2022)

FLAME: Taming Backdoors in Federated Learning. - Thien Duc Nguyen; Phillip Rieger; Huili Chen; Hossein Yalame; Helen Möllering; Hossein Fereidooni; Samuel Marchal; Markus Miettinen; Azalia Mirhoseini; Shaza Zeitouni; Farinaz Koushanfar; Ahmad-Reza Sadeghi; et al. (USENIX Security Symposium, 2022)

Close the Gate: Detecting Backdoored Models in Federated Learning based on Client-Side Deep Layer Output Analysis. - Phillip Rieger; Torsten Krauß; Markus Miettinen; Alexandra Dmitrienko; Ahmad-Reza Sadeghi (CoRR, 2022)

FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks. - Jorge Castillo; Phillip Rieger; Hossein Fereidooni; Qian Chen 019; Ahmad-Reza Sadeghi (ACSAC, 2023)

FLAIRS: FPGA-Accelerated Inference-Resistant & Secure Federated Learning. - Huimin Li 004; Phillip Rieger; Shaza Zeitouni; Stjepan Picek; Ahmad-Reza Sadeghi (FPL, 2023)

AuthentiSense: A Scalable Behavioral Biometrics Authentication Scheme using Few-Shot Learning for Mobile Platforms. - Hossein Fereidooni; Jan König; Phillip Rieger; Marco Chilese; Bora Gökbakan; Moritz Finke; Alexandra Dmitrienko; Ahmad-Reza Sadeghi (NDSS, 2023)

BayBFed: Bayesian Backdoor Defense for Federated Learning. - Kavita Kumari; Phillip Rieger; Hossein Fereidooni; Murtuza Jadliwala; Ahmad-Reza Sadeghi (SP, 2023)

ARGUS: Context-Based Detection of Stealthy IoT Infiltration Attacks. - Phillip Rieger; Marco Chilese; Reham Mohamed 002; Markus Miettinen; Hossein Fereidooni; Ahmad-Reza Sadeghi (USENIX Security Symposium, 2023)

Phantom: Untargeted Poisoning Attacks on Semi-Supervised Learning. - Jonathan Knauer; Phillip Rieger; Hossein Fereidooni; Ahmad-Reza Sadeghi (CCS, 2024)

Don't Buy the Pig in a Poke: Benchmarking DNNs Inference Performance before Development. - Constantin Völter; Timo Koppe; Phillip Rieger (HICSS, 2024)

FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning. - Hossein Fereidooni; Alessandro Pegoraro; Phillip Rieger; Alexandra Dmitrienko; Ahmad-Reza Sadeghi (NDSS, 2024)

CrowdGuard: Federated Backdoor Detection in Federated Learning. - Phillip Rieger; Torsten Krauß; Markus Miettinen; Alexandra Dmitrienko; Ahmad-Reza Sadeghi (NDSS, 2024)

LayerDBA: Circumventing Similarity-Based Defenses in Federated Learning. - Javor Nikolov; Alessandro Pegoraro; Phillip Rieger; Ahmad-Reza Sadeghi (SP (Workshops), 2024)

Phantom: Untargeted Poisoning Attacks on Semi-Supervised Learning (Full Version). - Jonathan Knauer; Phillip Rieger; Hossein Fereidooni; Ahmad-Reza Sadeghi (CoRR, 2024)

VoiceRadar: Voice Deepfake Detection using Micro-Frequency and Compositional Analysis. - Kavita Kumari; Maryam Abbasihafshejani; Alessandro Pegoraro; Phillip Rieger; Kamyar Arshi; Murtuza Jadliwala; Ahmad-Reza Sadeghi (NDSS, 2025)

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning. - Phillip Rieger; Alessandro Pegoraro; Kavita Kumari; Tigist Abera; Jonathan Knauer; Ahmad-Reza Sadeghi (NDSS, 2025)