Phillip Rieger

Orcid: 0000-0001-6216-7285

According to our database1, Phillip Rieger authored at least 15 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Phantom: Untargeted Poisoning Attacks on Semi-Supervised Learning (Full Version).
CoRR, 2024

CrowdGuard: Federated Backdoor Detection in Federated Learning.
Proceedings of the 31st Annual Network and Distributed System Security Symposium, 2024

FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning.
Proceedings of the 31st Annual Network and Distributed System Security Symposium, 2024

Don't Buy the Pig in a Poke: Benchmarking DNNs Inference Performance before Development.
Proceedings of the 57th Hawaii International Conference on System Sciences, 2024

2023
ARGUS: Context-Based Detection of Stealthy IoT Infiltration Attacks.
Proceedings of the 32nd USENIX Security Symposium, 2023

BayBFed: Bayesian Backdoor Defense for Federated Learning.
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.
Proceedings of the 30th Annual Network and Distributed System Security Symposium, 2023

FLAIRS: FPGA-Accelerated Inference-Resistant & Secure Federated Learning.
Proceedings of the 33rd International Conference on Field-Programmable Logic and Applications, 2023

FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks.
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.
CoRR, 2022


DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection.
Proceedings of the 29th Annual Network and Distributed System Security Symposium, 2022

FedCRI: Federated Mobile Cyber-Risk Intelligence.
Proceedings of the 29th Annual Network and Distributed System Security Symposium, 2022

2021
FLGUARD: Secure and Private Federated Learning.
IACR Cryptol. ePrint Arch., 2021

SAFELearn: Secure Aggregation for private FEderated Learning.
IACR Cryptol. ePrint Arch., 2021


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