PSARE: A RL-Based Online Participant Selection Scheme Incorporating Area Coverage Ratio and Degree in Mobile Crowdsensing

Xu, Ying; Wang, Yufeng; Ma, Jianhua; Jin, Qun

doi:10.1109/tvt.2022.3183607

Cited by 9 publications

(2 citation statements)

References 29 publications

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“…The research in [18] highlights security challenges in the intelligent wireless physical layer system (WPLS) for applications like the Internet of Things (IoT), device-to-device (D2D), cognitive radio(CR) and unmanned aerial vehicles (UAV). The study in [19] explores the issue of online participant selection in urban data sensing and collection, aiming to improve coverage quality in mobile crowdsensing using RL and Q-learning approaches.…”

Section: B Existing Work In Security Involving Network Slicing and Ma...mentioning

confidence: 99%

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Security Challenges in 6G Networks: A Game Theory-based Intrusion Detection with Network Slicing and AI/ML Perspectives

Gupta,

Jha,

Sabraj

2024

Preprint

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The vast network of interconnected devices of the Internet of Things poses significant security challenges, necessitating the upgrade of current wireless networks to the 6G standard and an improved intrusion detection system for host networks. Thus this article therefore underscores a game theory concept to analyze the security impediments in wireless communication systems, where a host network bandwidth is jeopardized by the intruder while acting as a legitimate user. While game theory can help with the impending security concerns, network slicing is saliently proposed for large and complicated networks, precipitating a layer wise fragmentation of the concerned network and effectively addressing the security issues in different layers of the IoT framework. However, with increasing network complexity, network security issues incorporating traditional measures become increasingly cumbersome. Therefore, this paper also briefly mentions some of the ML techniques that can be used to classify and segregate valid users from the compromised nodes in the host network. The paper discusses the potential of incorporating intelligence into wireless communication systems to enhance the host network security. The paper further aids in analyzing existing security issues in different layers of wireless communication systems, underscoring network slicing for further classification of intruders from user nodes and training the host network using ML/AI per the user application specification.

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Section: B Existing Work In Security Involving Network Slicing and Ma...mentioning

confidence: 99%

“…It learns to predict and classify new incoming classes by training and testing network features with new data [79]. The mathematical equation for the support vector system is described in (19):…”

Section: Support Vector Matrix (Svm)mentioning

confidence: 99%

Security Challenges in 6G Networks: A Game Theory-based Intrusion Detection with Network Slicing and AI/ML Perspectives

Gupta,

Jha,

Sabraj

2024

Preprint

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Distributed versus centralized computing of coverage in mobile crowdsensing

Girolami,

Kocian,

Chessa

2024

J Ambient Intell Human Comput

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The expected spatial coverage of a crowdsensing platform is an important parameter that derives from the mobility data of the crowdsensing platform users. We tackle the challenge of estimating the anticipated coverage while adhering to privacy constraints, where the platform is restricted from accessing detailed mobility data of individual users. Specifically, we model the coverage as the probability that a user detours to a point of interest if the user is present in a certain region around that point. Following this approach, we propose and evaluate a centralized as well as a distributed implementation model. We examine real-world mobility data employed for assessing the coverage performance of the two models, and we show that the two implementation models provide different privacy requirements but are equivalent in terms of their outputs.

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Systematic survey on artificial intelligence based mobile crowd sensing and sourcing solutions: Applications and security challenges

Nasser,

Mizouni,

Singh

et al. 2024

Ad Hoc Networks

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PSARE: A RL-Based Online Participant Selection Scheme Incorporating Area Coverage Ratio and Degree in Mobile Crowdsensing

Cited by 9 publications

References 29 publications

Security Challenges in 6G Networks: A Game Theory-based Intrusion Detection with Network Slicing and AI/ML Perspectives

Security Challenges in 6G Networks: A Game Theory-based Intrusion Detection with Network Slicing and AI/ML Perspectives

Distributed versus centralized computing of coverage in mobile crowdsensing

Systematic survey on artificial intelligence based mobile crowd sensing and sourcing solutions: Applications and security challenges

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