Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Trustworthiness of Dynamic Moving Sensors for Secure Mobile Edge Computing

Version 1 : Received: 17 September 2018 / Approved: 17 September 2018 / Online: 17 September 2018 (14:52:57 CEST)

A peer-reviewed article of this Preprint also exists.

Yoon, J. Trustworthiness of Dynamic Moving Sensors for Secure Mobile Edge Computing. Computers 2018, 7, 63. Yoon, J. Trustworthiness of Dynamic Moving Sensors for Secure Mobile Edge Computing. Computers 2018, 7, 63.

Journal reference: Computers 2018, 7, 63
DOI: 10.3390/computers7040063


Wireless Sensor Network is an emerging technology and the collaboration of wireless sensors becomes one of the active research areas to utilize sensor data. Various sensors collaborate to recognize the changes of a target environment, to identify, if occurs, any radical change. For the accuracy improvement, the calibration of sensors has been discussed, and sensor data analytics are becoming popular in research and development. However, they are not satisfactorily efficient for the situations where sensor devices are dynamically moving, abruptly appearing or disappearing. If the abrupt appearance of sensors is a zero-day attack and the disappearance of sensors is an ill-functioning comrade, then sensor data analytics of untrusted sensors will result in an indecisive artifact. The pre-defined sensor requirements or meta-data based sensors verification is not adaptive to identify dynamically moving sensors. This paper describes a deep-learning approach to verify the trustworthiness of sensors by considering the sensor data only, without having to use meta-data about sensors or to request consultation from a cloud server. The contribution of this paper includes 1) quality preservation of sensor data for mining analytics and 2) authenticity verification of dynamically moving sensors with no external consultation.


sensor collaborations; sensor trustworthiness; dynamic moving sensor collaboration; sensor calibration


MATHEMATICS & COMPUTER SCIENCE, Information Technology & Data Management

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