Privacy-Preserving Data-Driven Learning Models for Emerging Communication Networks: A Comprehensive Survey
With the proliferation of Beyond 5G (B5G) communication systems and heterogeneous
networks, mobile broadband users are generating massive volumes of data that undergo …
networks, mobile broadband users are generating massive volumes of data that undergo …
Sok: Secure aggregation based on cryptographic schemes for federated learning
M Mansouri, M Önen, WB Jaballah… - Proceedings on Privacy …, 2023 - petsymposium.org
Secure aggregation consists of computing the sum of data collected from multiple sources
without disclosing these individual inputs. Secure aggregation has been found useful for …
without disclosing these individual inputs. Secure aggregation has been found useful for …
{ACORN}: input validation for secure aggregation
Secure aggregation enables a server to learn the sum of client-held vectors in a privacy-
preserving way, and has been applied to distributed statistical analysis and machine …
preserving way, and has been applied to distributed statistical analysis and machine …
A survey and guideline on privacy enhancing technologies for collaborative machine learning
As machine learning and artificial intelligence (ML/AI) are becoming more popular and
advanced, there is a wish to turn sensitive data into valuable information via ML/AI …
advanced, there is a wish to turn sensitive data into valuable information via ML/AI …
Learning from failures: Secure and fault-tolerant aggregation for federated learning
M Mansouri, M Önen, W Ben Jaballah - Proceedings of the 38th Annual …, 2022 - dl.acm.org
Federated learning allows multiple parties to collaboratively train a global machine learning
(ML) model without sharing their private datasets. To make sure that these local datasets are …
(ML) model without sharing their private datasets. To make sure that these local datasets are …
A flexible and scalable malicious secure aggregation protocol for federated learning
J Tang, H Xu, M Wang, T Tang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Secure aggregation becomes a major solution to providing privacy for federated learning.
Secure aggregation for mobile devices typically relies on Shamir secret sharing (SSS) to …
Secure aggregation for mobile devices typically relies on Shamir secret sharing (SSS) to …
Detection and mitigation of label-flipping attacks in fl systems with kl divergence
L Zang, Y Li - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
The application of federated learning (FL) in the Internet of Things (IoT) is experiencing rapid
growth. FL becomes vulnerable to data poisoning attacks in the IoT environment …
growth. FL becomes vulnerable to data poisoning attacks in the IoT environment …
Optimal communication and key rate region for hierarchical secure aggregation with user collusion
Secure aggregation is concerned with the task of securely uploading the inputs of multiple
users to an aggregation server without letting the server know the inputs beyond their …
users to an aggregation server without letting the server know the inputs beyond their …
PRIDA: PRIvacy-preserving Data Aggregation with multiple data customers
B Bozdemir, BA Özdemir, M Önen - … on ICT Systems Security and Privacy …, 2024 - Springer
We propose PRIDA, a user-oriented private data aggregation solution involving multiple
data customers. While most existing solutions focus on designing an efficiency-oriented data …
data customers. While most existing solutions focus on designing an efficiency-oriented data …
Evading model poisoning attacks in federated learning by a long-short-term-memory-based approach
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Learning is designed to build a global model from a set of local learning tasks carried out by …
Learning is designed to build a global model from a set of local learning tasks carried out by …