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ORCIDPhillip Rieger
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2020 – today
- 2024
[c12]Constantin Völter, Timo Koppe, Phillip Rieger:
Don't Buy the Pig in a Poke: Benchmarking DNNs Inference Performance before Development. HICSS 2024: 7790-7799- [c11]Hossein Fereidooni, Alessandro Pegoraro, Phillip Rieger, Alexandra Dmitrienko, Ahmad-Reza Sadeghi:
FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning. NDSS 2024 - [c10]Phillip Rieger, Torsten Krauß, Markus Miettinen, Alexandra Dmitrienko, Ahmad-Reza Sadeghi:
CrowdGuard: Federated Backdoor Detection in Federated Learning. NDSS 2024 - [i12]Jonathan Knauer, Phillip Rieger, Hossein Fereidooni, Ahmad-Reza Sadeghi:
Phantom: Untargeted Poisoning Attacks on Semi-Supervised Learning (Full Version). CoRR abs/2409.01470 (2024) - 2023
- [c9]Jorge Castillo
, Phillip Rieger, Hossein Fereidooni, Qian Chen, Ahmad-Reza Sadeghi:
FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks. ACSAC 2023: 647-661 - [c8]Huimin Li, Phillip Rieger, Shaza Zeitouni, Stjepan Picek, Ahmad-Reza Sadeghi:
FLAIRS: FPGA-Accelerated Inference-Resistant & Secure Federated Learning. FPL 2023: 271-276 - [c7]Hossein Fereidooni, Jan König, Phillip Rieger, Marco Chilese, Bora Gökbakan, Moritz Finke, Alexandra Dmitrienko, Ahmad-Reza Sadeghi:
AuthentiSense: A Scalable Behavioral Biometrics Authentication Scheme using Few-Shot Learning for Mobile Platforms. NDSS 2023 - [c6]Kavita Kumari, Phillip Rieger, Hossein Fereidooni, Murtuza Jadliwala, Ahmad-Reza Sadeghi:
BayBFed: Bayesian Backdoor Defense for Federated Learning. SP 2023: 737-754 - [c5]Phillip Rieger, Marco Chilese, Reham Mohamed, Markus Miettinen, Hossein Fereidooni, Ahmad-Reza Sadeghi:
ARGUS: Context-Based Detection of Stealthy IoT Infiltration Attacks. USENIX Security Symposium 2023: 4301-4318 - [i11]Kavita Kumari, Phillip Rieger, Hossein Fereidooni, Murtuza Jadliwala, Ahmad-Reza Sadeghi:
BayBFed: Bayesian Backdoor Defense for Federated Learning. CoRR abs/2301.09508 (2023) - [i10]Hossein Fereidooni, Jan König, Phillip Rieger, Marco Chilese, Bora Gökbakan, Moritz Finke, Alexandra Dmitrienko, Ahmad-Reza Sadeghi:
AuthentiSense: A Scalable Behavioral Biometrics Authentication Scheme using Few-Shot Learning for Mobile Platforms. CoRR abs/2302.02740 (2023) - [i9]Phillip Rieger, Marco Chilese, Reham Mohamed, Markus Miettinen, Hossein Fereidooni, Ahmad-Reza Sadeghi:
ARGUS: Context-Based Detection of Stealthy IoT Infiltration Attacks. CoRR abs/2302.07589 (2023) - [i8]Huimin Li, Phillip Rieger, Shaza Zeitouni, Stjepan Picek, Ahmad-Reza Sadeghi:
FLAIRS: FPGA-Accelerated Inference-Resistant & Secure Federated Learning. CoRR abs/2308.00553 (2023) - [i7]Jorge Castillo, Phillip Rieger, Hossein Fereidooni, Qian Chen, Ahmad-Reza Sadeghi:
FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks. CoRR abs/2310.02113 (2023) - [i6]Hossein Fereidooni, Alessandro Pegoraro, Phillip Rieger, Alexandra Dmitrienko, Ahmad-Reza Sadeghi:
FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning. CoRR abs/2312.04432 (2023) - 2022
- [c4]Hossein Fereidooni, Alexandra Dmitrienko, Phillip Rieger, Markus Miettinen, Ahmad-Reza Sadeghi, Felix Madlener:
FedCRI: Federated Mobile Cyber-Risk Intelligence. NDSS 2022 - [c3]Phillip Rieger, Thien Duc Nguyen, Markus Miettinen, Ahmad-Reza Sadeghi:
DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection. NDSS 2022 - [c2]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, Thomas Schneider:
FLAME: Taming Backdoors in Federated Learning. USENIX Security Symposium 2022: 1415-1432 - [i5]Phillip Rieger, Thien Duc Nguyen, Markus Miettinen, Ahmad-Reza Sadeghi:
DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection. CoRR abs/2201.00763 (2022) - [i4]Phillip Rieger, Torsten Krauß, Markus Miettinen, Alexandra Dmitrienko, Ahmad-Reza Sadeghi:
Close the Gate: Detecting Backdoored Models in Federated Learning based on Client-Side Deep Layer Output Analysis. CoRR abs/2210.07714 (2022) - 2021
- [c1]Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Helen Möllering, Thien Duc Nguyen, Phillip Rieger, Ahmad-Reza Sadeghi, Thomas Schneider, Hossein Yalame, Shaza Zeitouni:
SAFELearn: Secure Aggregation for private FEderated Learning. SP (Workshops) 2021: 56-62 - [i3]Thien Duc Nguyen, Phillip Rieger, Hossein Yalame, Helen Möllering, Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Ahmad-Reza Sadeghi, Thomas Schneider, Shaza Zeitouni:
FLGUARD: Secure and Private Federated Learning. CoRR abs/2101.02281 (2021) - [i2]Thien Duc Nguyen, Phillip Rieger, Hossein Yalame, Helen Möllering, Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Ahmad-Reza Sadeghi, Thomas Schneider, Shaza Zeitouni:
FLGUARD: Secure and Private Federated Learning. IACR Cryptol. ePrint Arch. 2021: 25 (2021) - [i1]Hossein Fereidooni, Samuel Marchal, Markus Miettinen, Azalia Mirhoseini, Helen Möllering, Thien Duc Nguyen, Phillip Rieger, Ahmad-Reza Sadeghi, Thomas Schneider, Hossein Yalame, Shaza Zeitouni:
SAFELearn: Secure Aggregation for private FEderated Learning. IACR Cryptol. ePrint Arch. 2021: 386 (2021)
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