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Found 9 papers, 1 papers with code
CAAP: Class-Dependent Automatic Data Augmentation Based On Adaptive Policies For Time Series
We propose a novel deep learning-based approach called Class-dependent Automatic Adaptive Policies (CAAP) framework to overcome the notable class-dependent bias problem while maintaining the overall improvement in time-series data augmentation.
Open Set Dandelion Network for IoT Intrusion Detection
The OSDN model performs intrusion knowledge transfer from the knowledge-rich source network intrusion domain to facilitate more accurate intrusion detection for the data-scarce target IoT intrusion domain.
Adaptive Bi-Recommendation and Self-Improving Network for Heterogeneous Domain Adaptation-Assisted IoT Intrusion Detection
The ABRSI achieves fine-grained intrusion knowledge transfer via adaptive bi-recommendation matching.
Heterogeneous Domain Adaptation for IoT Intrusion Detection: A Geometric Graph Alignment Approach
In this paper, a Geometric Graph Alignment (GGA) approach is leveraged to mask the geometric heterogeneities between domains for better intrusion knowledge transfer.
Multi-Scenario Bimetric-Balanced IoT Resource Allocation: An Evolutionary Approach
In this paper, we allocate IoT devices as resources for smart services with time-constrained resource requirements.
Joint Semantic Transfer Network for IoT Intrusion Detection
The scenario semantic endows source NI and II domain with characteristics from each other to ease the knowledge transfer process via a confused domain discriminator and categorical distribution knowledge preservation.
PECCO: A Profit and Cost-oriented Computation Offloading Scheme in Edge-Cloud Environment with Improved Moth-flame Optimisation
With the fast growing quantity of data generated by smart devices and the exponential surge of processing demand in the Internet of Things (IoT) era, the resource-rich cloud centres have been utilised to tackle these challenges.
FedDrop: Trajectory-weighted Dropout for Efficient Federated Learning
Federated learning (FL) enables edge clients to train collaboratively while preserving individual's data privacy.
TrialChain: A Blockchain-Based Platform to Validate Data Integrity in Large, Biomedical Research Studies
The TrialChain platform provides a data governance solution to audit the acquisition and analysis of biomedical research data.
Distributed, Parallel, and Cluster Computing Cryptography and Security
