15 Secure Crowdsensing Platforms Through Device Behavior Fingerprinting
Crowdsensing platforms allow sharing data, collected by devices of individuals, to achieve common objectives based on the analysis of shared information. Despite their benefits, these platforms also bring security threats that must be addressed to provide secure data and reliable services. In this c...
| Autores: | , , , , |
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| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universidad de Castilla-La Mancha |
| Repositorio: | RUIdeRA. Repositorio Institucional de la UCLM |
| OAI Identifier: | oai:ruidera.uclm.es:10578/28619 |
| Acceso en línea: | http://doi.org/10.18239/jornadas_2021.34.15 http://hdl.handle.net/10578/28619 |
| Access Level: | acceso abierto |
| Palabra clave: | Crowdsensing Device Behavior cybersegurity Attack Detection |
| Sumario: | Crowdsensing platforms allow sharing data, collected by devices of individuals, to achieve common objectives based on the analysis of shared information. Despite their benefits, these platforms also bring security threats that must be addressed to provide secure data and reliable services. In this context, device behavior fingerprinting becomes a key technique to detect and mitigate possible cyberattacks affecting resourceconstrained devices. This work presents the most relevant research questions in the field of behavior fingerprinting to identify devices and detect anomalies produced by cyberattacks. In addition, it also introduces the main goals and current status of two research projects dealing with such research questions. |
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