AIMC Topic: Computer Security

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Federated learning with bilateral defense via blockchain.

Neural networks : the official journal of the International Neural Network Society
Federated Learning (FL) offers benefits in protecting client data privacy but also faces multiple security challenges, such as privacy breaches from unencrypted data transmission and poisoning attacks that compromise model performance, however, most ...

Intelligent classification of computer vulnerabilities and network security management system: Combining memristor neural network and improved TCNN model.

PloS one
To enhance the intelligent classification of computer vulnerabilities and improve the efficiency and accuracy of network security management, this study delves into the application of a comprehensive classification system that integrates the Memristo...

Distributed Denial of Services (DDoS) attack detection in SDN using Optimizer-equipped CNN-MLP.

PloS one
Software-Defined Networks (SDN) provides more control and network operation over a network infrastructure as an emerging and revolutionary paradigm in networking. Operating the many network applications and preserving the network services and functio...

Optimized Adaboost Support Vector Machine-Based Encryption for Securing IoT-Cloud Healthcare Data.

Sensors (Basel, Switzerland)
The Internet of Things (IoT) connects various medical devices that enable remote monitoring, which can improve patient outcomes and help healthcare providers deliver precise diagnoses and better service to patients. However, IoT-based healthcare mana...

Generative adversarial local density-based unsupervised anomaly detection.

PloS one
Anomaly detection is crucial in areas such as financial fraud identification, cybersecurity defense, and health monitoring, as it directly affects the accuracy and security of decision-making. Existing generative adversarial nets (GANs)-based anomaly...

Artificial intelligence and blockchain in clinical trials: enhancing data governance efficiency, integrity, and transparency.

Bioanalysis
This article examines the transformative potential of blockchain technology and its integration with artificial intelligence (AI) in clinical trials, focusing on their combined ability to enhance integrity, operational efficiency, and transparency in...

Stacking Ensemble Deep Learning for Real-Time Intrusion Detection in IoMT Environments.

Sensors (Basel, Switzerland)
The Internet of Medical Things (IoMT) is revolutionizing healthcare by enabling advanced patient care through interconnected medical devices and systems. However, its critical role and sensitive data make it a prime target for cyber threats, requirin...

Towards practical and privacy-preserving CNN inference service for cloud-based medical imaging analysis: A homomorphic encryption-based approach.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cloud-based Deep Learning as a Service (DLaaS) has transformed biomedicine by enabling healthcare systems to harness the power of deep learning for biomedical data analysis. However, privacy concerns emerge when sensitive us...

Investigating the performance of multivariate LSTM models to predict the occurrence of Distributed Denial of Service (DDoS) attack.

PloS one
In the current cybersecurity landscape, Distributed Denial of Service (DDoS) attacks have become a prevalent form of cybercrime. These attacks are relatively easy to execute but can cause significant disruption and damage to targeted systems and netw...

GAN-based data reconstruction attacks in split learning.

Neural networks : the official journal of the International Neural Network Society
Due to the distinctive distributed privacy-preserving architecture, split learning has found widespread application in scenarios where computational resources on the client side are limited. Unlike clients in federated learning retaining the whole mo...