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2017 ITU Kaleidoscope Academic Conference


















                                                                Fig. 5. Scaled down Sequence Diagram Showing relationship
                                                                among the Publisher (Sensor), Subscriber (u), Sensing Broker
                                                                           and the proposed Framework
                                                              new  subscriber is available, the broker notifies the TCPD
                                                              system to deliver the data to the subscriber along with the
            Fig. 4. High-level Implementation Architecture of the proposed   trust level of the data.
                                System
           pollution/environment sensors. The data collected from the         6. CONCLUSION
           air pollution sensors are delivered to the IoT Cloud, hosting   In this  work,  we argue that the traditional  means of trust
           the TCPD proposed in this paper. Thus, a mobile app for   computation for entities does not necessary  guarantee  the
           trusted air quality data monitoring can be developed on top   trustworthiness of data that they generate. Hence,  we
           of this framework integrating data collected from low-cost   propose a hybrid trust computational platform  which is
           environment  sensors for temperature, humidity, CO,  CO2   capable of assessing both data centric trust as  well as
           NO2, SO2, as well as compounds including benzene and lead   traditional entity based trust. Further, we provide a model to
           (VOCs), etc. The sensors’ readings will be transmitted via   compute individual DTA and the main DTM by combining
           either an  Android or IOS app to the proposed system  for   numerical models with  learning  algorithms. Afterward,  a
           assessing and predicting the trust of the data before it is sent   data trust prediction scheme based on collaborative filtering
           to the IoT Cloud. Such data can then be visualized along with   is proposed to find the data trust between trustors and data
           its trust level by interested individuals, government, city   sources who do not have prior encounters that avoids using
           administrators etc. via a web application.         data from  malicious actors. Finally, a possible

           For the above use case to profit from the proposed solution,   implementation scenario is  discussed based on a crowd
           we have proposed a  distributed publish-subscribe   sensing use case. Similarly, our algorithm  would be
           architecture  such as  CoreDX distributed publish subscribe   beneficial to filter out malicious data and data sources to
           middleware [36] whereby an interested parties can subscribe   maintain integrity and quality of the outcomes that any
           via a broker to environmental data of interest in specific   crowd sensing application produces.
           location of their choice as illustrated in Fig. 4, the   For future work, we would like to incorporate content and
           implementation architecture. TCPD section of the  figure   contextual information for data trust prediction and propose
           implements appropriate components of the framework as   a  more accurate prediction  model based on artificial
           shown in Fig. 2, for providing trusted data to the interested   intelligence concepts.  Although ITU-T has started a  new
           parties. This is a typical publish subscribe system whereby   work on trust index which is a comprehensive accumulation
           publishers publish the  sensor data to the broker and   of trust indicators to evaluate and quantify trust of entities,
           subscribers  receive  notifications  matching  their  until now, standards on trusted data are still very limited and
           subscriptions from the broker. As illustrated in the Fig. 2, the   current standards on entity or network based trust must be
           TCPD can communicate with the IoT platform via an edge   expanded for taking into consideration the data trust matters
           server  that  implements  the  IGetTrustData  and  as explained in this work.
           IProvideTrustData interfaces.  Also, the TCPD can receive
           data from the IoT platform for predicting the trust of such     ACKNOWLEDGMENT
           received data.                                     This  work  was supported by Institute for Information  &
           Finally, Fig. 5 illustrates an example of a scaled down   communications Technology Promotion(IITP) grant funded
           sequences of interactions between some important   by  the   Korea  government(MSIT).  [2015-0-00533,
           stakeholders of an implementation instance of the system.   Development of TII(Trusted Information Infrastructure)
           Anytime a new environment sensor is available, it registers   S/W Framework for Realizing Trustworthy IoT Eco-
           its presence with the sensing broker, which in turn informs   system].
           the framework of the new available sensor. The new sensor
           can then publish its data to the broker. The broker notifies        REFERENCES
           the TCPD to predict the trust of the received data. Similarly,   [1]  U. Jayasinghe, H. W. Lee, and G. M. Lee, “A Computational
           whenever a new subscriber joins the system, its subscription   Model to Evaluate Honesty in Social Internet of Things,” in
           is submitted to the broker via the TCPD system. If a   32nd ACM  SIGAPP  Symposium On Applied Computing,
           subscription matching at least one of the subscriptions of the   Marrakesh, Morocco., 2017.



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