AIMC Topic: Computer Security

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Quantum-resilient software security: A fuzzy AHP-based assessment framework in the era of quantum computing.

PloS one
The introduction of quantum computing has transformed the setting of information technology, bringing both unprecedented opportunities and significant challenges. As quantum technologies continue to evolve, addressing their implications for software ...

H control for fractional order neural networks with uncertainties subject to deception attacks via Improved memory-event-triggered scheme and Its application.

Neural networks : the official journal of the International Neural Network Society
The article discusses an improved memory-event-triggered strategy for H control class of fractional-order neural networks (FONNs) with uncertainties, which are vulnerable to deception attacks. The system under consideration is simultaneously influenc...

Preserving privacy in healthcare: A systematic review of deep learning approaches for synthetic data generation.

Computer methods and programs in biomedicine
BACKGROUND: Data sharing in healthcare is vital for advancing research and personalized medicine. However, the process is hindered by privacy, ethical, and legal challenges associated with patient data. Synthetic data generation emerges as a promisin...

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...

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 ...

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...

Unlocking Security for Comprehensive Electroencephalogram-Based User Authentication Systems.

Sensors (Basel, Switzerland)
With recent significant advancements in artificial intelligence, the necessity for more reliable recognition systems has rapidly increased to safeguard individual assets. The use of brain signals for authentication has gained substantial interest wit...

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...

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...