AIMC Topic: Computer Security

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Secret learning for lung cancer diagnosis-a study with homomorphic encryption, texture analysis and deep learning.

Biomedical physics & engineering express
Advanced lung cancer diagnoses from radiographic images include automated detection of lung cancer from CT-Scan images of the lungs. Deep learning is a popular method for decision making which can be used to classify cancerous and non-cancerous lungs...

Lightweight Multi-Class Support Vector Machine-Based Medical Diagnosis System with Privacy Preservation.

Sensors (Basel, Switzerland)
Machine learning, powered by cloud servers, has found application in medical diagnosis, enhancing the capabilities of smart healthcare services. Research literature demonstrates that the support vector machine (SVM) consistently demonstrates remarkab...

Machine intelligence and medical cyber-physical system architectures for smart healthcare: Taxonomy, challenges, opportunities, and possible solutions.

Artificial intelligence in medicine
Hospitals use medical cyber-physical systems (MCPS) more often to give patients quality continuous care. MCPS isa life-critical, context-aware, networked system of medical equipment. It has been challenging to achieve high assurance in system softwar...

Cybersecurity in neural interfaces: Survey and future trends.

Computers in biology and medicine
With the joint advancement in areas such as pervasive neural data sensing, neural computing, neuromodulation and artificial intelligence, neural interface has become a promising technology facilitating both the closed-loop neurorehabilitation for neu...

[Legal integration of artificial intelligence into internal medicine : Data protection, regulatory, reimbursement and liability questions].

Innere Medizin (Heidelberg, Germany)
Artificial intelligence (AI) opens up new opportunities to improve medical care in internal medicine; however, legal uncertainties in the application of AI impede its integration into the daily practice of internal medicine. To clarify the situation ...

Cybersecurity in Internet of Medical Vehicles: State-of-the-Art Analysis, Research Challenges and Future Perspectives.

Sensors (Basel, Switzerland)
The "Internet-of-Medical-Vehicles (IOMV)" is one of the special applications of the Internet of Things resulting from combining connected healthcare and connected vehicles. As the IOMV communicates with a variety of networks along its travel path, it...

Blockchain-Powered Healthcare Systems: Enhancing Scalability and Security with Hybrid Deep Learning.

Sensors (Basel, Switzerland)
The rapid advancements in technology have paved the way for innovative solutions in the healthcare domain, aiming to improve scalability and security while enhancing patient care. This abstract introduces a cutting-edge approach, leveraging blockchai...

A Novel Steganography Method for Infrared Image Based on Smooth Wavelet Transform and Convolutional Neural Network.

Sensors (Basel, Switzerland)
Infrared images have been widely used in many research areas, such as target detection and scene monitoring. Therefore, the copyright protection of infrared images is very important. In order to accomplish the goal of image-copyright protection, a la...

SCADA securing system using deep learning to prevent cyber infiltration.

Neural networks : the official journal of the International Neural Network Society
Supervisory Control and Data Acquisition (SCADA) systems are computer-based control architectures specifically engineered for the operation of industrial machinery via hardware and software models. These systems are used to project, monitor, and auto...

Swarm-FHE: Fully Homomorphic Encryption-based Swarm Learning for Malicious Clients.

International journal of neural systems
Swarm Learning (SL) is a promising approach to perform the distributed and collaborative model training without any central server. However, data sensitivity is the main concern for privacy when collaborative training requires data sharing. A neural ...