Deep learning in the fast lane: A survey on advanced intrusion detection systems for intelligent vehicle networks

M Almehdhar, A Albaseer, MA Khan… - IEEE Open Journal …, 2024‏ - ieeexplore.ieee.org
The rapid evolution of modern automobiles into intelligent and interconnected entities
presents new challenges in cybersecurity, particularly in Intrusion Detection Systems (IDS) …

Blockchain-based federated learning with enhanced privacy and security using homomorphic encryption and reputation

R Yang, T Zhao, FR Yu, M Li, D Zhang… - IEEE Internet of Things …, 2024‏ - ieeexplore.ieee.org
Federated learning, leveraging distributed data from multiple nodes to train a common
model, allows for the use of more data to improve the model while also protecting the privacy …

Integrating Explainable AI with Federated Learning for Next-Generation IoT: A comprehensive review and prospective insights

P Dubey, M Kumar - Computer Science Review, 2025‏ - Elsevier
The emergence of the Internet of Things (IoT) signifies a transformative wave of innovation,
establishing a network of devices designed to enrich everyday experiences. Develo** …

Leveraging network data analytics function and machine learning for data collection, resource optimization, security and privacy in 6G networks

PK Gkonis, N Nomikos, P Trakadas, L Sarakis… - IEEE …, 2024‏ - ieeexplore.ieee.org
The full deployment of sixth-generation (6G) networks is inextricably connected with a
holistic network redesign able to deal with various emerging challenges, such as integration …

Efficiency of federated learning and blockchain in preserving privacy and enhancing the performance of credit card fraud detection (CCFD) systems

T Baabdullah, A Alzahrani, DB Rawat, C Liu - Future Internet, 2024‏ - mdpi.com
Increasing global credit card usage has elevated it to a preferred payment method for daily
transactions, underscoring its significance in global financial cybersecurity. This paper …

Fedsbs: Federated-learning participant-selection method for intrusion detection systems

HNC Neto, J Hribar, I Dusparic, NC Fernandes… - Computer Networks, 2024‏ - Elsevier
Federated Learning (FL) is a decentralized machine learning approach in which multiple
participants collaboratively train a model. Participants keep data locally, train their local …

A multifaceted survey on federated learning: Fundamentals, paradigm shifts, practical issues, recent developments, partnerships, trade-offs, trustworthiness, and ways …

A Majeed, SO Hwang - IEEE Access, 2024‏ - ieeexplore.ieee.org
Federated learning (FL) is considered a de facto standard for privacy preservation in AI
environments because it does not require data to be aggregated in some central place to …

Fortifying federated learning in IIoT: Leveraging blockchain and digital twin innovations for enhanced security and resilience

SB Prathiba, Y Govindarajan, VPA Ganesan… - IEEE …, 2024‏ - ieeexplore.ieee.org
Ensuring robustness against adversarial attacks is imperative for Machine Learning (ML)
systems within the critical infrastructures of the Industrial Internet of Things (IIoT). This paper …

Prediction and Detection of Terminal Diseases Using Internet of Medical Things: A Review

AT Otapo, A Othmani, G Khodabandelou… - arxiv preprint arxiv …, 2024‏ - arxiv.org
The integration of Artificial Intelligence (AI) and the Internet of Medical Things (IoMT) in
healthcare, through Machine Learning (ML) and Deep Learning (DL) techniques, has …

Privacy-Preserving Federated Learning for Intrusion Detection in IoT Environments: A Survey

A Vyas, PC Lin, RH Hwang, M Tripathi - IEEE Access, 2024‏ - ieeexplore.ieee.org
With the rapid development of artificial intelligence and a new generation of network
technologies, the Internet of Things (IoT) is expanding worldwide. Malicious agents …