Phillip Rieger

According to our database, Phillip Rieger authored at least 13 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Don't Buy the Pig in a Poke: Benchmarking DNNs Inference Performance before Development.

Constantin Völter, Timo Koppe, Phillip Rieger

Proceedings of the 57th Hawaii International Conference on System Sciences, 2024

2023

FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning.

Hossein Fereidooni, Alessandro Pegoraro, Phillip Rieger, Alexandra Dmitrienko, Ahmad-Reza Sadeghi

CoRR, 2023

ARGUS: Context-Based Detection of Stealthy IoT Infiltration Attacks.

Phillip Rieger, Marco Chilese, Reham Mohamed, Markus Miettinen, Hossein Fereidooni, Ahmad-Reza Sadeghi

Proceedings of the 32nd USENIX Security Symposium, 2023

BayBFed: Bayesian Backdoor Defense for Federated Learning.

Kavita Kumari, Phillip Rieger, Hossein Fereidooni, Murtuza Jadliwala, Ahmad-Reza Sadeghi

Proceedings of the 44th IEEE Symposium on Security and Privacy, 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

Proceedings of the 30th Annual Network and Distributed System Security Symposium, 2023

FLAIRS: FPGA-Accelerated Inference-Resistant & Secure Federated Learning.

Huimin Li, Phillip Rieger, Shaza Zeitouni, Stjepan Picek, Ahmad-Reza Sadeghi

Proceedings of the 33rd International Conference on Field-Programmable Logic and Applications, 2023

FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks.

Jorge Castillo, Phillip Rieger, Hossein Fereidooni, Qian Chen, Ahmad-Reza Sadeghi

Proceedings of the Annual Computer Security Applications Conference, 2023

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

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, Thomas Schneider

Proceedings of the 31st USENIX Security Symposium, 2022

DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection.

Phillip Rieger, Thien Duc Nguyen, Markus Miettinen, Ahmad-Reza Sadeghi

Proceedings of the 29th Annual Network and Distributed System Security Symposium, 2022

FedCRI: Federated Mobile Cyber-Risk Intelligence.

Hossein Fereidooni, Alexandra Dmitrienko, Phillip Rieger, Markus Miettinen, Ahmad-Reza Sadeghi, Felix Madlener

Proceedings of the 29th Annual Network and Distributed System Security Symposium, 2022

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, Shaza Zeitouni

IACR Cryptol. ePrint Arch., 2021

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, Hossein Yalame, Shaza Zeitouni

IACR Cryptol. ePrint Arch., 2021