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Confidentiality

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Network Threat Detection Using Machine/Deep Learning in SDN-Based Platforms: A Comprehensive Analysis of State-of-the-Art Solutions, Discussion, Challenges, and Future Research Direction.

Sensors (Basel, Switzerland)
A revolution in network technology has been ushered in by software defined networking (SDN), which makes it possible to control the network from a central location and provides an overview of the network's security. Despite this, SDN has a single poi...

Deep Learning for Encrypted Traffic Classification and Unknown Data Detection.

Sensors (Basel, Switzerland)
Despite the widespread use of encryption techniques to provide confidentiality over Internet communications, mobile device users are still susceptible to privacy and security risks. In this paper, a novel Deep Neural Network (DNN) based on a user act...

Next-Generation Capabilities in Trusted Research Environments: Interview Study.

Journal of medical Internet research
BACKGROUND: A Trusted Research Environment (TRE; also known as a Safe Haven) is an environment supported by trained staff and agreed processes (principles and standards), providing access to data for research while protecting patient confidentiality....

A digital mask to safeguard patient privacy.

Nature medicine
The storage of facial images in medical records poses privacy risks due to the sensitive nature of the personal biometric information that can be extracted from such images. To minimize these risks, we developed a new technology, called the digital m...

Privacy-Preserving Multi-Class Support Vector Machine Model on Medical Diagnosis.

IEEE journal of biomedical and health informatics
With the rapid development of machine learning in the medical cloud system, cloud-assisted medical computing provides a concrete platform for remote rapid medical diagnosis services. Support vector machine (SVM), as one of the important algorithms of...

Novel Method for Safeguarding Personal Health Record in Cloud Connection Using Deep Learning Models.

Computational intelligence and neuroscience
It is a new online service paradigm that allows consumers to exchange their health data. Health information management software allows individuals to control and share their health data with other users and healthcare experts. Patient health records ...

A Federated Mining Approach on Predicting Diabetes-Related Complications: Demonstration Using Real-World Clinical Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Chronic diabetes can lead to microvascular complications, including diabetic eye disease, diabetic kidney disease, and diabetic neuropathy. However, the long-term complications often remain undetected at the early stages of diagnosis. Developing a ma...

An Intelligent Control Model of Credit Line Computing in Intelligence Health-Care Systems.

Frontiers in public health
Technologies such as machine learning and artificial intelligence have brought about a tremendous change to biomedical computing and intelligence health care. As a principal component of the intelligence healthcare system, the hospital information sy...

Legal and ethical considerations of artificial intelligence in skin cancer diagnosis.

The Australasian journal of dermatology
Artificial intelligence (AI) technology is becoming increasingly accurate and prevalent for the diagnosis of skin cancers. Commercially available AI diagnostic software is entering markets across the world posing new legal and ethical challenges for ...

Swarm Learning for decentralized and confidential clinical machine learning.

Nature
Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes. However, there is an i...