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Computer Security

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Effective DDoS attack detection in software-defined vehicular networks using statistical flow analysis and machine learning.

PloS one
Vehicular Networks (VN) utilizing Software Defined Networking (SDN) have garnered significant attention recently, paralleling the advancements in wireless networks. VN are deployed to optimize traffic flow, enhance the driving experience, and ensure ...

Strongly concealed adversarial attack against text classification models with limited queries.

Neural networks : the official journal of the International Neural Network Society
In black-box scenarios, adversarial attacks against text classification models face challenges in ensuring highly available adversarial samples, especially a high number of invalid queries under long texts. The existing methods select distractors by ...

Inclusive AI for radiology: Optimising ChatGPT-4 with advanced prompt engineering.

Clinical imaging
This letter responds to the article "Encouragement vs. liability: How prompt engineering influences ChatGPT-4's radiology exam performance," offering additional perspectives on optimising ChatGPT-4 for Radiology applications. While the study highligh...

Methodology for Safe and Secure AI in Diabetes Management.

Journal of diabetes science and technology
The use of artificial intelligence (AI) in diabetes management is emerging as a promising solution to improve the monitoring and personalization of therapies. However, the integration of such technologies in the clinical setting poses significant cha...

DDP-DAR: Network intrusion detection based on denoising diffusion probabilistic model and dual-attention residual network.

Neural networks : the official journal of the International Neural Network Society
Network intrusion detection (NID) is an effective manner to guarantee the security of cyberspace. However, the scale of normal network traffic is much larger than intrusion traffic (i.e., appearing data imbalance problem), which leads to the training...

FedPD: Defending federated prototype learning against backdoor attacks.

Neural networks : the official journal of the International Neural Network Society
Federated Learning (FL) is an efficient, distributed machine learning paradigm that enables multiple clients to jointly train high-performance deep learning models while maintaining training data locally. However, due to its distributed computing nat...

Cluster synchronization of fractional-order two-layer networks and application in image encryption/decryption.

Neural networks : the official journal of the International Neural Network Society
In this paper, a type of fractional-order two-layer network model is constructed, wherein each layer in the network exhibits distinct topology. Subsequently, the cluster synchronization problem of fractional-order two-layer networks is investigated t...

Advancements in exponential synchronization and encryption techniques: Quaternion-Valued Artificial Neural Networks with two-sided coefficients.

Neural networks : the official journal of the International Neural Network Society
This paper presents cutting-edge advancements in exponential synchronization and encryption techniques, focusing on Quaternion-Valued Artificial Neural Networks (QVANNs) that incorporate two-sided coefficients. The study introduces a novel approach t...

DFA-mode-dependent stability of impulsive switched memristive neural networks under channel-covert aperiodic asynchronous attacks.

Neural networks : the official journal of the International Neural Network Society
This article is concerned with the deterministic finite automaton-mode-dependent (DFAMD) exponential stability problem of impulsive switched memristive neural networks (SMNNs) with aperiodic asynchronous attacks and the network covert channel. First,...

Enhancing Privacy-Preserving Cancer Classification with Convolutional Neural Networks.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Precision medicine significantly enhances patients prognosis, offering personalized treatments. Particularly for metastatic cancer, incorporating primary tumor location into the diagnostic process greatly improves survival rates. However, traditional...