Intrusion detection for cyber–physical systems using generative adversarial networks in fog environment
PF de Araujo-Filho, G Kaddoum… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Cyber-attacks cyber-physical systems (CPSs) can lead to sensing and actuation
misbehavior, severe damages to physical objects, and safety risks. Machine learning …
misbehavior, severe damages to physical objects, and safety risks. Machine learning …
AI-based resource provisioning of IoE services in 6G: A deep reinforcement learning approach
Currently, researchers have motivated a vision of 6G for empowering the new generation of
the Internet of Everything (IoE) services that are not supported by 5G. In the context of 6G …
the Internet of Everything (IoE) services that are not supported by 5G. In the context of 6G …
Ad Hoc Vehicular Fog Enabling Cooperative Low-Latency Intrusion Detection
Internet of Vehicles and vehicular networks have been compelling targets for malicious
security attacks where several intrusion detection solutions have been proposed for …
security attacks where several intrusion detection solutions have been proposed for …
Demand-driven deep reinforcement learning for scalable fog and service placement
The increasing number of Internet of Things (IoT) devices necessitates the need for a more
substantial fog computing infrastructure to support the users' demand for services. In this …
substantial fog computing infrastructure to support the users' demand for services. In this …
FoGMatch: An intelligent multi-criteria IoT-fog scheduling approach using game theory
Cloud computing has long been the main backbone that Internet of Things (IoT) devices rely
on to accommodate their storage and analytical needs. However, the fact that cloud systems …
on to accommodate their storage and analytical needs. However, the fact that cloud systems …
A service pricing-based two-stage incentive algorithm for socially aware networks
X Zenggang, L Xiang, Z Xueming, Z Sanyuan… - Journal of Signal …, 2022 - Springer
In socially aware networks, data forwarding is usually performed based on opportunistic
peer-to-peer connections and using a store-and-forward method. This method requires …
peer-to-peer connections and using a store-and-forward method. This method requires …
Trust-based cloud machine learning model selection for industrial IoT and smart city services
With machine learning (ML) services now used in a number of mission-critical human-facing
domains, ensuring the integrity and trustworthiness of ML models becomes all important. In …
domains, ensuring the integrity and trustworthiness of ML models becomes all important. In …
Stable federated fog formation: An evolutionary game theoretical approach
Instability within fog federations is considered as a serious problem that degrades the
performance of the provided services. The latter may affect the service availability due to fog …
performance of the provided services. The latter may affect the service availability due to fog …
CRAS-FL: Clustered resource-aware scheme for federated learning in vehicular networks
As a promising distributed learning paradigm, Federated Learning (FL) is expected to meet
the ever-increasing needs of Machine Learning (ML) based applications in Intelligent …
the ever-increasing needs of Machine Learning (ML) based applications in Intelligent …
A blockchain-enabled relay selection for QoS-OLSR in urban VANET: A Stackelberg game model
In this paper, a blockchain-enabled Stackelberg game model is proposed for the Quality-of-
Service Optimized Link State Routing (QoS-OLSR) protocol in urban VANET. While QoS …
Service Optimized Link State Routing (QoS-OLSR) protocol in urban VANET. While QoS …