N. Baracaldo

发表

A Hybrid Approach to Privacy-Preserving Federated Learning

Rui Zhang, Thomas Steinke, Heiko Ludwig, 2018, Informatik Spektrum.

Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering pdf

Benjamin Edwards, Biplav Srivastava, Heiko Ludwig, 2018, SafeAI@AAAI.

TiFL: A Tier-based Federated Learning System

Heiko Ludwig, Yi Zhou, Ahsan Ali, 2020, HPDC.

Adversarial Robustness Toolbox v1.0.0

Martin Wistuba, Ian Molloy, Nathalie Baracaldo, 2018, 1807.01069.

FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data

Nathalie Baracaldo, Heiko Ludwig, Runhua Xu, 2021, AISec@CCS.

Privacy-Preserving Machine Learning: Methods, Challenges and Directions pdf

Nathalie Baracaldo, Runhua Xu, James Joshi, 2021, ArXiv.

HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning

Nathalie Baracaldo, Heiko Ludwig, Runhua Xu, 2019, AISec@CCS.

Mitigating Bias in Federated Learning pdf

Heiko Ludwig, Yi Zhou, Nathalie Baracaldo, 2020, ArXiv.

Detecting Poisoning Attacks on Machine Learning in IoT Environments

Rui Zhang, Heiko Ludwig, Nathalie Baracaldo, 2018, 2018 IEEE International Congress on Internet of Things (ICIOT).

Mitigating Poisoning Attacks on Machine Learning Models: A Data Provenance Based Approach

Heiko Ludwig, Nathalie Baracaldo, Bryant Chen, 2017, AISec@CCS.

Federated Unlearning: How to Efficiently Erase a Client in FL?

Nathalie Baracaldo, S. Kadhe, Ambrish Rawat, 2022, ArXiv.

Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach

Dian Balta, Ambrish Rawat, M. Sinn, 2022, ArXiv.

LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning

Ali Anwar, Nathalie Baracaldo, Kamala Varma, 2021, 2021 IEEE 14th International Conference on Cloud Computing (CLOUD).

IBM Federated Learning: an Enterprise Framework White Paper V0.1 pdf

Heiko Ludwig, Yi Zhou, Laura Wynter, 2020, ArXiv.

Benchmarking the Effect of Poisoning Defenses on the Security and Bias of Deep Learning Models

Kevin Eykholt, Sridevi Polavaram, S. Kadhe, 2023, 2023 IEEE Security and Privacy Workshops (SPW).

Benchmarking the Effect of Poisoning Defenses on the Security and Bias of the Final Model

Kevin Eykholt, Sridevi Polavaram, Nathalie Baracaldo, 2022 .

Privacy-Preserving Process Mining

Matthias Weidlich, Agnes Koschmider, Nathalie Baracaldo, 2019, Business & Information Systems Engineering.

LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning

Shiqiang Wang, S. Patterson, S. Kadhe, 2023, ICML.

Reconciling End-to-End Confidentiality and Data Reduction In Cloud Storage

Alessandro Sorniotti, Joseph S. Glider, Elli Androulaki, 2014, CCSW.

DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting

Heiko Ludwig, S. Kadhe, Runhua Xu, 2022, 2022 IEEE 15th International Conference on Cloud Computing (CLOUD).

User Centered and Privacy-Driven Process Mining System Design

Bernhard Rumpe, Agnes Koschmider, Judith Michael, 2019, Informatik Spektrum.

Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning

Yuan Tian, Ali Anwar, Feng Yan, 2021, AAAI.

The Design and Development of a Game to Study Backdoor Poisoning Attacks: The Backdoor Game

Heiko Ludwig, Zahra Ashktorab, Werner Geyer, 2021, IUI.

An adaptive risk management and access control framework to mitigate insider threats

James B. D. Joshi, Nathalie Baracaldo, J. Joshi, 2013, Comput. Secur..

Federated Unlearning: How to Efficiently Erase a Client in FL?

S. Kadhe, Ambrish Rawat, Anisa Halimi, 2022, ArXiv.

Simulating the effect of privacy concerns in online social networks

Mohd Anwar, Michael Lewis, Claudia A. López, 2011, 2011 IEEE International Conference on Information Reuse & Integration.

HDFL: A Heterogeneity and Client Dropout-Aware Federated Learning Framework

Feng Yan, Yi Zhou, Syed Zawad, 2023, 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid).

FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data

Runhua Xu, Heiko Ludwig, Ali Anwar, 2021, AISec@CCS.

TACKLING INSIDER THREATS USING RISK-AND-TRUST AWARE ACCESS CONTROL APPROACHES

Nathalie Baracaldo, N. Baracaldo, 2016 .

Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning pdf

Heiko Ludwig, Yi Zhou, Nathalie Baracaldo, 2020, ArXiv.