AIMC Topic: Computer Security

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DKiS: Decay weight invertible image steganography with private key.

Neural networks : the official journal of the International Neural Network Society
Image steganography, defined as the practice of concealing information within another image. In this paper, we propose decay weight invertible image steganography with private key (DKiS). This model introduces two major advancements into current inve...

Reimbursement and Regulatory Landscape for Artificial Intelligence in Medical Technology.

Gastrointestinal endoscopy clinics of North America
Integration of artificial intelligence (AI) into medical devices and services promises significant improvements in the diagnosis and treatment of disease. This article reviews current payment pathways for AI medical technology and the regulatory issu...

An intelligent attention based deep convoluted learning (IADCL) model for smart healthcare security.

Scientific reports
In recent times, there has been rapid growth of technologies that have enabled smart infrastructures-IoT-powered smart grids, cities, and healthcare systems. But these resource-constrained IoT devices cannot be protected by existing security mechanis...

Deep learning-based encryption scheme for medical images using DCGAN and virtual planet domain.

Scientific reports
The motivation for this article stems from the fact that medical image security is crucial for maintaining patient confidentiality and protecting against unauthorized access or manipulation. This paper presents a novel encryption technique that integ...

mDARTS: Searching ML-Based ECG Classifiers Against Membership Inference Attacks.

IEEE journal of biomedical and health informatics
This paper addresses the critical need for elctrocardiogram (ECG) classifier architectures that balance high classification performance with robust privacy protection against membership inference attacks (MIA). We introduce a comprehensive approach t...

Managing emergency crises using secure information through educational awareness: COVID-19 case study.

Computers in biology and medicine
Social networks are increasingly taking over daily life, creating a volume of unsecured data and making it very difficult to capture safe data, especially in times of crisis. This study aims to use a Convolutional Neural Network (CNN)-Long Short-Term...

Spectral adversarial attack on graph via node injection.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have shown remarkable achievements and have been extensively applied in various downstream tasks, such as node classification and community detection. However, recent studies have demonstrated that GNNs are vulnerable to ...

Feature efficiency in IoMT security: A comprehensive framework for threat detection with DNN and ML.

Computers in biology and medicine
BACKGROUND: To address critical security challenges in the Internet of Medical Things (IoMT), this study develops a feature selection framework to improve detection accuracy and computational efficiency in IoMT cybersecurity. By optimizing feature se...

Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges.

International journal of medical informatics
INTRODUCTION: Artificial Intelligence is in the phase of health care, with transformative innovations in diagnostics, personalized treatment, and operational efficiency. While having potential, critical challenges are apparent in areas of safety, tru...

Utilizing Artificial neural networks (ANN) to regulate Smart cities for sustainable Urban Development and Safeguarding Citizen rights.

Scientific reports
The advent of smart cities has brought about a paradigm shift in urban management and citizen engagement. By leveraging technological advancements, cities are now able to collect and analyze extensive data to optimize service delivery, allocate resou...