Abstract
Due to technology limitation and environmental influence (i.e., equipment faults, noises, clutter, interferences, and security attacks), the sensor data collected by Cyber-Physical System (CPS) is inherently noisy and may trigger many false alarms. These false or misleading data can lead to wrong decisions. Therefore, data trustworthiness (i.e., the data is free from error, up to date, and originate from a reputable source) is always preferred. However, it often has high cost and challenges to identify fault, noise, cyber-attack, and real-world facts, especially in heterogeneous and complex IoT environment. In this article, we briefly review the current developments and research trend in this research area. We highlighted all the challenges and potential solutions for the trustworthy data collections in CPS and propose a taxonomy for data trustworthiness in CPS. Taxonomy aims to describe different aspects of research in this field. Furthermore, it will help researchers as a reference point for the design of data reliability and data trustworthiness evaluation methods. Based on the observations, future directions are also suggested.
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References
Cisco: Internet of Things (IoT) - Cisco IoT Product Portfolio - Cisco. http://www.cisco.com/c/en/us/solutions/internet-ofthings/iot-products.html. Accessed 23 May 2019
Bao, F., Chen, I.-R.: Dynamic trust management for internet of things applications. In: Proceedings of International Workshop on Self-aware Internet of Things, pp. 1–6, September 2012
Aggarwal, C.C., Ashish, N., Sheth, A.: The Internet of Things: a survey from the data-centric perspective. In: Aggarwal, C. (ed.) Managing and Mining Sensor Data. Springer, Boston, MA (2013). https://doi.org/10.1007/978-1-4614-6309-2_12
Wang, Y., Lu, Y.C., Chen, I.R., Cho, J.H., Swami, A.: LogitTrust: a logit regression-based trust model for mobile ad hoc networks. In: 6th ASE International Conference on Privacy, Security, Risk and Trust, Boston, MA, December 2014
Lim, H.-S., Ghinita, G., Bertino, E., Kantarcioglu, M.: A gametheoretic approach for high-assurance of data trustworthiness in sensor networks. In: 2012 IEEE 28th International Conference on Data (2012)
Li, M., Jiang, W., Li, K.: Recommendation systems in real applications: algorithm and parallel architecture. In: Wang, G., Ray, I., Alcaraz Calero, J., Thampi, S. (eds.) SpaCCS 2016. LNCS, vol. 10066, pp. 45–58. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-49148-6_5
Karkouch, A., Mousannif, H., Al Moatassime, H., Noel, T.: Data quality in internet of things: a state-of-the-art survey. J. Netw. Comput. Appl. 73, 57–81 (2016)
Bhuiyan, M.Z.A., Wu, J.: Trustworthy and protected data collection for event detection using networked sensing systems. In: 2016 IEEE 37th Sarnoff Symposium. IEEE (2016)
Bhuiyan, M.Z.A., Wang, G., Choo, K.-K.R.: Secured data collection for a cloud-enabled structural health monitoring system. In: 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE (2016)
Saied, Y.B., Olivereau, A., Zeghlache, D., Laurent, M.: Trust management system design for the Internet of Things: a context-aware and multi-service approach. Comput. Secur. 39, 351–365 (2014)
Hui-hui, D., Ya-jun, G., Zhong-qiang, Y., Hao, C.: A wireless sensor networks based on multi-angle trust of node. In: International Forum on Information Technology and Applications, 2009. IFITA-2009, vol. 1, pp. 28–31 (2009)
Sathe, S., Papaioannou, T.G., Jeung, H., Aberer, K.: A survey of model-based sensor data acquisition and management. In: Aggarwal, C. (ed.) Managing and Mining Sensor Data. Springer, Boston (2013). https://doi.org/10.1007/978-1-4614-6309-2_2
Javed, N., Wolf, T.: Automated sensor verification using outlier detection in the Internet of Things. In: 2012 32nd International Conference on Distributed Computing Systems Workshops (ICDCSW), pp. 291–296 (2012)
Bao, F., Chen, I.R.: Dynamic trust management for the Internet of Things applications. In: International Workshop on Self-Aware Internet of Things, San Jose, USA, September 2012
Elahi, H., Wang, G., Li, X.: Smartphone bloatware: an overlooked privacy problem. In: Wang, G., Atiquzzaman, M., Yan, Z., Choo, K.-K.R. (eds.) SpaCCS 2017. LNCS, vol. 10656, pp. 169–185. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-72389-1_15
Makhdoom, I., et al.: Anatomy of threats to the Internet of Things. In: IEEE Communications Surveys and Tutorials, vol. 21, no. 2, pp. 1636–1675 (2018)
Arif, M., Wang, G., Wang, T., Peng, T.: SDN-based secure VANETs communication with fog computing. In: Wang, G., Chen, J., Yang, L. (eds.) SpaCCS 2018. LNCS, vol. 11342. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-05345-1_4
Haron, N., Jaafar, J., Aziz, I.A., Hassan, M.H., Shapiai, M. I.: Data trustworthiness in Internet of Things: a taxonomy and future directions. In 2017 IEEE Conference on Big Data and Analytics (ICBDA), Kuching, pp. 25–30 (2017)
Tang, L.A., et al.: Trustworthiness analysis of sensor data in cyber-physical systems. J. Comput. Syst. Sci. 79(3), 383–401 (2013)
Guo, J., Chen, R.: A classification of trust computation models for service-oriented internet of things systems. In: IEEE International Conference on Services Computing (SCC), vol. 2015, pp. 324–331 (2015)
Pouryazdan, M., Kantarci, B., Soyata, T., Foschini, L., Song, H.: Quantifying user reputation scores, data trustworthiness, and user incentives in mobile crowd-sensing. IEEE Access 5, 1382–1397 (2017)
Chen, I.-R., Bao, F., Guo, J.: Trust-based service management for social Internet of Things systems. IEEE Trans. Dependable Secure Comput. 13(6), 684–696 (2015)
Josang, A.: A logic for uncertain probabilities. Int. J. Uncertainty Fuzziness Knowl.-Based Syst. 9(3), 279–311 (2001)
Anjum, B., Rajangam, M., Perros, H., Fan, W.: Filtering Unfair Users: A Hidden Markov Model Approach. SciTePress, Setúbal (2015)
ur Rahman, H., Azzedin, F., Shawahna, A., Sajjad, F., Abdulrahman, A.S.: Performance evaluation of vdi environment. In 2016 Sixth International Conference on Innovative Computing Technology (INTECH), pp. 104–109. IEEE, August 2016
ur Rahman, H., Wang, G., Chen, J., Jiang, H.: Performance evaluation of hypervisors and the effect of virtual CPU on Performance. In: 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), pp. 772–779. IEEE, October 2018
Zong, B., Xu, F., Jiao, J., Lv, J.: A broker-assisting trust and reputation system based on artficial neural network. In: IEEE International Conference on Systems, Man and Cybernetics (SMC), pp. 4710–4715, October 2009
Liu, X., Datta, A., Lim, E.P.: Computational Trust Models and Machine Learning. CRC Press, Boca Raton (2014)
Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: bringing order to the web. Technical report, Stanford Digital Library Technologies Project (1998)
Kamvar, S.D., Schlosser, M.T., Molina, H.G.: The EigenTrust algorithm for reputation management in P2P networks. In: Proceedings of the 12th International World Wide Web Conference, Budapest, May 2003
Carbone, M., Nielsen, M., Sassone, V.: A formal model for trust in dynamic networks. In: Proceedings of International Conference on Software Engineering and Formal Methods (SEFM 2003), Brisbane, September 2003
Dhulipala, V.S., Karthik, N., Chandrasekaran, R.M.: A novel heuristic approach based trust worthy architecture for wireless sensor networks. Wireless Personal Commun. 70(1), 189–205 (2013)
Bertino, E.: Data trustworthiness—approaches and research challenges. In: Garcia-Alfaro, J., et al. (eds.) DPM/QASA/SETOP -2014. LNCS, vol. 8872, pp. 17–25. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-17016-9_2
Khan, M.F., Wang, G., Bhuiyan, M.Z.A.: Wi-Fi frequency selection concept for effective coverage in collapsed structures. Fut. Gener. Comput.Syst. 97, 409–424 (2019)
Han, G., Jiang, J., Shu, L., Niu, J., Chao, H.-C.: Management and applications of trust in wireless sensor networks: a survey. J. Comput. Syst. Sci. 80(3), 602–617 (2014)
Acknowledgments
This work was supported in part by the National Natural Science Foundation of China under Grant 61632009 and 61872097, in part by the Guangdong Provincial Natural Science Foundation under Grant 2017A030308006, and in part by the High-Level Talents Program of Higher Education in Guangdong Province under Grant 2016ZJ01.
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Rahman, H.u., Wang, G., Alam Bhuiyan, M.Z., Chen, J. (2019). Trustworthy Data Collection for Cyber Systems: A Taxonomy and Future Directions. In: Wang, G., El Saddik, A., Lai, X., Martinez Perez, G., Choo, KK. (eds) Smart City and Informatization. iSCI 2019. Communications in Computer and Information Science, vol 1122. Springer, Singapore. https://doi.org/10.1007/978-981-15-1301-5_13
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