Machine learning and blockchain technologies for cybersecurity in connected vehicles
Future connected and autonomous vehicles (CAVs) must be secured against cyberattacks
for their everyday functions on the road so that safety of passengers and vehicles can be …
for their everyday functions on the road so that safety of passengers and vehicles can be …
Enhancing Internet of Medical Things security with artificial intelligence: A comprehensive review
S Messinis, N Temenos, NE Protonotarios… - Computers in Biology …, 2024 - Elsevier
Over the past five years, interest in the literature regarding the security of the Internet of
Medical Things (IoMT) has increased. Due to the enhanced interconnectedness of IoMT …
Medical Things (IoMT) has increased. Due to the enhanced interconnectedness of IoMT …
[HTML][HTML] Attribute-Centric and Synthetic Data Based Privacy Preserving Methods: A Systematic Review
A Majeed - Journal of Cybersecurity and Privacy, 2023 - mdpi.com
Anonymization techniques are widely used to make personal data broadly available for
analytics/data-mining purposes while preserving the privacy of the personal information …
analytics/data-mining purposes while preserving the privacy of the personal information …
Privacy-preserving deep learning in medical informatics: applications, challenges, and solutions
Deep Learning (DL) has already shown tremendous potential in designing intelligent clinical
support systems in biomedicine. Data privacy plays a significant role while training and …
support systems in biomedicine. Data privacy plays a significant role while training and …
Enhancing security and privacy preservation of sensitive information in e-Health datasets using FCA approach
Advances in data collection, storage, and processing in e-Health systems have recently
increased the importance and popularity of data mining in the health care field. However, the …
increased the importance and popularity of data mining in the health care field. However, the …
Managing Distributed Machine Learning Lifecycle for Healthcare Data in the Cloud
The main objective of this paper is to highlight the research directions and explain the main
roles of current Artificial Intelligence (AI)/Machine Learning (ML) frameworks and available …
roles of current Artificial Intelligence (AI)/Machine Learning (ML) frameworks and available …
Evaluating Factors Influencing Learner Satisfaction in Massive Open Online Course Selection: A Data-Driven Approach Using Machine Learning
A Alghamdi - Arabian Journal for Science and Engineering, 2024 - Springer
Massive open online course (MOOC) platforms have seen a significant increase in the
number of participants in recent years. MOOCs are at the forefront of an educational …
number of participants in recent years. MOOCs are at the forefront of an educational …
FLASH: Federated Learning-Based LLMs for Advanced Query Processing in Social Networks through RAG
Our paper introduces a novel approach to social network information retrieval and user
engagement through a personalized chatbot system empowered by Federated Learning …
engagement through a personalized chatbot system empowered by Federated Learning …
Investigating Security and Privacy Concerns in Deep-Learning-based Pervasive Health Monitoring Architectures
A Boulemtafes, A Amira, MS Derki… - 2023 5th International …, 2023 - ieeexplore.ieee.org
Pervasive Health Monitoring (PHM) uses sensors and wearable devices and data analytics
for real-time health monitoring. It enables early detection and personalized care …
for real-time health monitoring. It enables early detection and personalized care …
[HTML][HTML] Getting ready for the European Health Data Space (EHDS): IDERHA's plan to align with the latest EHDS requirements for the secondary use of health data
Objective The European Health Data Space (EHDS) shapes the digital transformation of
healthcare in Europe. The EHDS regulation will also accelerate the use of health data for …
healthcare in Europe. The EHDS regulation will also accelerate the use of health data for …