Abstract

Wireless sensor and actuator devices with direct IPv6 Internet access with no human interaction compose the IP-connected Internet of Things (IoT). These devices are resource constrained in processing, memory, and energy—battery operated. IoT devices can have various applications. Although, when directly connected to the Internet they are susceptible to threats (e.g., malicious tamper of packet content to reduce the reliability of device data, the flood of requisitions for the devices to drain their energy). In this way, the literature shows the use of end-to-end security to provide confidentiality, authenticity, and integrity of IoT devices data. However, even with the benefit of secure IoT data, they are not enough to ensure reliable measurements. For this reason, this work presents a reliability model for IoT, focused on the identification of anomalous measurements (using multivariate statistics). In the experiments, we use spatial (proximity) and temporal (time interval variation) correlation, and datasets with true and false data. Additionally, we use an end-to-end secure scenario and analysis of energy consumption. The results prove the feasibility of the triad: reliability (within a system that identifies the type of the anomalous measurements), security, and low energy consumption.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.