Collaborative, Autonomic, and Resilient Defenses for Cyber Physical Systems

Research Article

WCPS-OSL: A Wireless Cyber-Physical System for Object Sensing and Localization

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  • @INPROCEEDINGS{10.4108/icst.collaboratecom.2011.247189,
        author={Amal AlHusseiny and Moustafa Youssef and Mohamed ELTowiessy},
        title={WCPS-OSL: A Wireless Cyber-Physical System for Object Sensing and Localization},
        proceedings={Collaborative, Autonomic, and Resilient Defenses for Cyber Physical Systems},
        publisher={IEEE},
        proceedings_a={CYPHYCARD'},
        year={2012},
        month={4},
        keywords={device-free identification traffic estimation object identification},
        doi={10.4108/icst.collaboratecom.2011.247189}
    }
    
  • Amal AlHusseiny
    Moustafa Youssef
    Mohamed ELTowiessy
    Year: 2012
    WCPS-OSL: A Wireless Cyber-Physical System for Object Sensing and Localization
    CYPHYCARD'
    ICST
    DOI: 10.4108/icst.collaboratecom.2011.247189
Amal AlHusseiny1, Moustafa Youssef1,*, Mohamed ELTowiessy2
  • 1: Egypt-Japan University of Science and Technology (E-JUST)
  • 2: Pacific Northwest National Laboratory and Virginia Tech
*Contact email: moustafa.youssef@ejust.edu.eg

Abstract

We propose a novel Cyber-Physical System for object sensing and localization based on changes in the wireless signal strength with the focus on border protection as an application scenario. Our work is based on the principle that RF signals undergo reflection or refraction when encountering physical objects leading to variations in the received signal. Our system uses access points (APs) and monitoring points (MPs) as sensing and computational nodes. The existence of an object, for example a human or a vehicle, in the area of interest affects the signal strength transmitted by the APs and received by the MPs. The system has training and operation modes. Training occurs by injecting various objects into the field of operation with varying mobility patterns and recording the respective changes in the received signal strength. This produces signal maps that are stored for future matching during the operation mode. According to the type, size, location and number of objects (or intruders) in the operation mode, the system assigns a priority to the intrusion event, so as to deal with it properly. We therefore transform the problem of intrusion detection to a signal pattern matching one. Our proposed system shows a good probability of detection of objects such as standing humans and stationary cars. In addition, the system has a good ability to differentiate between humans, cars and other objects. We also investigate the challenges and open issues related to the system.