The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles(IoV)*** functional advantages of IoV include online communication services,accident preventi...
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The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles(IoV)*** functional advantages of IoV include online communication services,accident prevention,cost reduction,and enhanced traffic *** these benefits,IoV technology is susceptible to cyber-attacks,which can exploit vulnerabilities in the vehicle network,leading to perturbations,disturbances,non-recognition of traffic signs,accidents,and vehicle *** paper reviews the state-of-the-art achievements and developments in applying Deep Transfer Learning(DTL)models for Intrusion Detection Systems in the Internet of Vehicles(IDS-IoV)based on anomaly ***-IoV leverages anomaly detection through machine learning and DTL techniques to mitigate the risks posed by *** systems can autonomously create specific models based on network data to differentiate between regular traffic and *** these techniques,transfer learning models are particularly promising due to their efficacy with tagged data,reduced training time,lower memory usage,and decreased computational *** evaluate DTL models against criteria including the ability to transfer knowledge,detection rate,accurate analysis of complex data,and *** review highlights the significant progress made in the field,showcasing how DTL models enhance the performance and reliability of IDS-IoV *** examining recent advancements,we provide insights into how DTL can effectively address cyber-attack challenges in IoV environments,ensuring safer and more efficient transportation networks.
Sophisticated cyber threats are seen on Online Social Networks (OSNs) social media accounts automated to imitate human behaviours has an impactful effect on distorting public thoughts and opinions. OSNs are weaponized...
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This study utilized MobileN et to surpass the accuracy of previous research in the field of Balinese mask image classification. Balinese masks as one of the objects of Balinese cultural heritage must be preserved. Bas...
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Following a pilot project, which concluded in 2016, the replacement of old energy consuming Traffic Light Systems (TLS) of Nicosia Municipality were the subject of an investigation with regards to the energy saving po...
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In this paper, we performed an analysis of the outage probability (Pout) at the output of the receiver with selection combination (SC) with L branches of the wireless communication system in the presence of Beaulieu-X...
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The fast proliferation of edge devices for the Internet of Things(IoT)has led to massive volumes of data *** generated data is collected and shared using edge-based IoT structures at a considerably high ***,the data-s...
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The fast proliferation of edge devices for the Internet of Things(IoT)has led to massive volumes of data *** generated data is collected and shared using edge-based IoT structures at a considerably high ***,the data-sharing privacy exposure issue is increasingly intimidating when IoT devices make malicious requests for filching sensitive information from a cloud storage system through edge *** address the identified issue,we present evolutionary privacy preservation learning strategies for an edge computing-based IoT data sharing *** particular,we introduce evolutionary game theory and construct a payoff matrix to symbolize intercommunication between IoT devices and edge nodes,where IoT devices and edge nodes are two parties of the *** devices may make malicious requests to achieve their goals of stealing ***,edge nodes should deny malicious IoT device requests to prevent IoT data from being *** dynamically adjust their own strategies according to the opponent's strategy and finally maximize the *** upon a developed application framework to illustrate the concrete data sharing architecture,a novel algorithm is proposed that can derive the optimal evolutionary learning ***,we numerically simulate evolutionarily stable strategies,and the final results experimentally verify the correctness of the IoT data sharing privacy preservation ***,the proposed model can effectively defeat malicious invasion and protect sensitive information from leaking when IoT data is shared.
A high-stakes event is an extreme risk with a low probability of occurring, but severe consequences (e.g., life-threatening conditions or economic collapse). The accompanying lack of information is a source of high-st...
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Robot swarm navigation faces challenges in coordi-nation in dynamic environments with limited information, since each robot only has local access, making optimal paths difficult to achieve. Increasing the number of ro...
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Hate speech and abusive language on social media can spread massively and escalate into conflict between two or more individuals or parties. Previous studies about multi-label classification to identify whether the tw...
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