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08/09/2023
Federated Online/Offline Remote Data Inspection for Distributed Edge Computing
In edge computing environments, app vendors can cache their data to be s...
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07/01/2023
Fedward: Flexible Federated Backdoor Defense Framework with Non-IID Data
Federated learning (FL) enables multiple clients to collaboratively trai...
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03/01/2023
Efficient Routing Algorithm Design for Large DetNet
Deterministic Networking (DetNet) is a rising technology that offers det...
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12/12/2022
SRoUDA: Meta Self-training for Robust Unsupervised Domain Adaptation
As acquiring manual labels on data could be costly, unsupervised domain ...
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12/05/2022
Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning
Federated Learning (FL) is pervasive in privacy-focused IoT environments...
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12/04/2022
SoK: Fully Homomorphic Encryption Accelerators
Fully Homomorphic Encryption (FHE) is a key technology enabling privacy-...
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09/14/2022
Federated Learning based on Defending Against Data Poisoning Attacks in IoT
The rapidly expanding number of Internet of Things (IoT) devices is gene...
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08/13/2022
MaskBlock: Transferable Adversarial Examples with Bayes Approach
The transferability of adversarial examples (AEs) across diverse models ...
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05/27/2022
Evolution as a Service: A Privacy-Preserving Genetic Algorithm for Combinatorial Optimization
Evolutionary algorithms (EAs), such as the genetic algorithm (GA), offer...
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02/28/2022
Enhance transferability of adversarial examples with model architecture
Transferability of adversarial examples is of critical importance to lau...
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01/27/2022
Generation Matrix: An Embeddable Matrix Representation for Hierarchical Trees
Starting from the local structures to study hierarchical trees is a comm...
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12/01/2021
Push Stricter to Decide Better: A Class-Conditional Feature Adaptive Framework for Improving Adversarial Robustness
In response to the threat of adversarial examples, adversarial training ...
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07/03/2021
Too Expensive to Attack: Enlarge the Attack Expense through Joint Defense at the Edge
The distributed denial of service (DDoS) attack is detrimental to busine...
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05/25/2021
The Component Diagnosability of General Networks
The processor failures in a multiprocessor system have a negative impact...
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04/01/2021
Too Expensive to Attack: A Joint Defense Framework to Mitigate Distributed Attacks for the Internet of Things Grid
The distributed denial of service (DDoS) attack is detrimental to busine...
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02/20/2021
When Crowdsensing Meets Federated Learning: Privacy-Preserving Mobile Crowdsensing System
Mobile crowdsensing (MCS) is an emerging sensing data collection pattern...
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02/05/2021
Robust Single-step Adversarial Training with Regularizer
High cost of training time caused by multi-step adversarial example gene...
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09/23/2020
Pocket Diagnosis: Secure Federated Learning against Poisoning Attack in the Cloud
Federated learning has become prevalent in medical diagnosis due to its ...
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05/24/2020
Privacy-preserving Medical Treatment System through Nondeterministic Finite Automata
In this paper, we propose a privacy-preserving medical treatment system ...
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05/18/2020
VerifyTL: Secure and Verifiable Collaborative Transfer Learning
Getting access to labelled datasets in certain sensitive application dom...
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05/09/2020
Cloud-based Federated Boosting for Mobile Crowdsensing
The application of federated extreme gradient boosting to mobile crowdse...
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03/24/2020
Learn to Forget: User-Level Memorization Elimination in Federated Learning
Federated learning is a decentralized machine learning technique that ev...
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02/10/2020
Droidetec: Android Malware Detection and Malicious Code Localization through Deep Learning
Android malware detection is a critical step towards building a security...
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11/08/2019
Revocable Federated Learning: A Benchmark of Federated Forest
A learning federation is composed of multiple participants who use the f...
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09/27/2019
Lightning-Fast and Privacy-Preserving Outsourced Computation in the Cloud
In this paper, we propose a framework for lightning-fast privacy-preserv...
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07/24/2019
Boosting Privately: Privacy-Preserving Federated Extreme Boosting for Mobile Crowdsensing
The state-of-the-art federated learning brings a new direction for the d...
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02/12/2019
