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Found 7 papers, 2 papers with code
Genetic Algorithm-Based Dynamic Backdoor Attack on Federated Learning-Based Network Traffic Classification
In this paper, we propose GABAttack, a novel genetic algorithm-based backdoor attack against federated learning for network traffic classification.
Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection
In this work, we call the attack that manipulates several nodes in the DMG concurrently a multi-instance evasion attack.
Semi-decentralized Inference in Heterogeneous Graph Neural Networks for Traffic Demand Forecasting: An Edge-Computing Approach
This approach minimizes inter-cloudlet communication thereby alleviating the communication overhead of the decentralized approach while promoting scalability due to cloudlet-level decentralization.
Adversarial Attacks and Defenses for Social Network Text Processing Applications: Techniques, Challenges and Future Research Directions
These vulnerabilities allow adversaries to launch a diversified set of adversarial attacks on these algorithms in different applications of social media text processing.
Estimating Sparsity Level for Enabling Compressive Sensing of Wireless Channels and Spectra in 5G and Beyond
In this paper, we propose an algorithm for estimating the composite sparsity lying in multiple domains defined by learned dictionaries.
Deep Learning-Based Optimal RIS Interaction Exploiting Previously Sampled Channel Correlations
Although these works can reduce the beam training overhead, still they overlook existing correlations in the previously sampled channels.
Sparsifying Dictionary Learning for Beamspace Channel Representation and Estimation in Millimeter-Wave Massive MIMO
This beamspace transformation is equivalent to performing a Fourier transformation of the channel.
