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2020 | OriginalPaper | Chapter

6. Quantifying Trust Perception to Enable Design for Connectivity in Cyber-Physical-Social Systems

Author : Yan Wang

Published in: Emotional Engineering, Vol. 8

Publisher: Springer International Publishing

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Abstract

Cyber-physical systems possess highly integrated functions of data collection, data processing, communication, and control. Given their seamless integration with human society, they are also termed as cyber-physical-social systems (CPSS). The advanced capabilities and functions of CPSS rely on their highly networked working environment and deep interdependency. The effectiveness of their performance critically depends on what and how they share among each other. Designing a trustworthy CPSS network, which can work together collaboratively thus is important. To perform systems design, quantitative measures of trustworthiness are required. In this chapter, quantitative metrics of trustworthiness, including capability, benevolence, and integrity, are proposed based on a generic probabilistic graph model of CPSS networks. The proposed metrics can be calculated from either subjective perception or objective statistics of sensing, computing, and communication functions in CPSS networks. A design optimization framework based on the trustworthiness metrics is also demonstrated.

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Literature
1.
Akter S, D’Ambra J, Ray P (2011) Trustworthiness in mHealth information services: an assessment of a hierarchical model with mediating and moderating effects using partial least squares (PLS). J Assoc Inf Sci Technol (Wiley Online Library) 62(1):100–116CrossRef
2.
Al-Hamadi H, Chen R (2017) Trust-based decision making for health IoT systems. IEEE Internet Things J IEEE 4(5):1408–1419CrossRef
3.
Angelaki DE, Gu Y, DeAngelis GC (2009) Multisensory integration: psychophysics, neurophysiology, and computation. Curr Opin Neurobiol (Elsevier) 19(4):452–458CrossRef
4.
Barber KS, Kim J (2001) Belief revision process based on trust: agents evaluating reputation of information sources. In: Falcone R, Singh M, Tan Y-H (eds) Trust in Cyber-societies. Springer, pp 73–82
5.
Beth T, Borcherding M, Klein B (1994) Valuation of trust in open networks. Computer security—ESORICS 94. Springer, pp 1–18
6.
Chen D et al (2011) TRM-IoT: a trust management model based on fuzzy reputation for internet of things. Comput Sci Inf Syst 8(4):1207–1228CrossRef
7.
Chen R, Bao F, Guo J (2016) Trust-based service management for social internet of things systems. IEEE Trans Dependable Secure Comput (IEEE) 13(6):684–696CrossRef
8.
Chen Z, Tian L, Lin C (2017) Trust model of wireless sensor networks and its application in data fusion. Sensors (Multidisciplinary Digital Publishing Institute) 17(4):703CrossRef
9.
Ernst MO, Banks MS (2002) Humans integrate visual and haptic information in a statistically optimal fashion. Nature (Nature Publishing Group) 415(6870):429CrossRef
10.
Fuller MA et al (2010) Clarifying the integration of trust and TAM in e-commerce environments: implications for systems design and management. IEEE Trans Eng Manag 57(3):380–393 (IEEE)CrossRef
11.
Golbeck J, others (2008) Trust on the world wide web: a survey. Foundations and trends® in web science, vol 1, no 2. Now Publishers, Inc., pp 131–197
12.
Govindan K, Mohapatra P (2012) Trust computations and trust dynamics in mobile adhoc networks: a survey. IEEE Commun Surv Tutor 14(2):279–298 (IEEE)CrossRef
13.
Grabner-Kräuter S, Kaluscha EA (2003) Empirical research in on-line trust: a review and critical assessment. Int J Hum-Comput Stud 58(6):783–812 (Elsevier)CrossRef
14.
Huynh TD, Jennings NR, Shadbolt NR (2006) An integrated trust and reputation model for open multi-agent systems. Autonomous agents and multi-agent systems 13(2):119–154 (Springer)CrossRef
15.
16.
Kim H et al (2010) A trust evaluation model for QoS guarantee in cloud systems. Int J Grid Distrib Comput 3(1):1–10
17.
Lee MKO, Turban E (2001) A trust model for consumer internet shopping. Int J Electron Commer (Taylor & Francis) 6(1):75–91
18.
Lee S, Sherwood R, Bhattacharjee B (2003) Cooperative peer groups in NICE. In: INFOCOM 2003. twenty-second annual joint conference of the IEEE computer and communications. IEEE Societies, pp 1272–1282
19.
Li X et al (2015) ‘Service operator-aware trust scheme for resource matchmaking across multiple clouds. IEEE Trans Parallel Distrib Syst 26(5):1419–1429 IEEECrossRef
20.
Li X, Zhou F, Du J (2013) ‘LDTS: A lightweight and dependable trust system for clustered wireless sensor networks. IEEE Trans Inf Forensics Secur 8(6):924–935 IEEECrossRef
21.
Ma X, Lu H, Gan Z (2014) Improving recommendation accuracy by combining trust communities and collaborative filtering. In: Proceedings of the 23rd ACM international conference on conference on information and knowledge management, pp 1951–1954
22.
Mayer RC, Davis JH, Schoorman FD (1995) An integrative model of organizational trust. Acad Manag Rev 20(3):709–734 Academy of ManagementCrossRef
23.
Nitti M, Girau R, Atzori L (2014) Trustworthiness management in the social internet of things. IEEE Trans Knowl Data Eng 26(5):1253–1266 IEEECrossRef
24.
O’Doherty D, Jouili S, Van Roy P (2012) Towards trust inference from bipartite social networks. In: Proceedings of the 2nd ACM SIGMOD workshop on databases and social networks, pp 13–18
25.
Patel J et al (2005) A probabilistic trust model for handling inaccurate reputation sources. In: Herrmann P, Issarny V, Shiu S (eds) Trust management. Springer, Berlin, Heidelberg, pp 193–209CrossRef
26.
Reddy VB, Venkataraman S, Negi A (2017) Communication and data trust for wireless sensor networks using D-S theory. IEEE Sens J 17(12):3921–3929 IEEECrossRef
27.
Ruan Y, Durresi A (2016) ‘A survey of trust management systems for online social communities—Trust modeling, trust inference and attacks. Knowl-Based Syst 106:150–163 ElsevierCrossRef
28.
Sabater J, Sierra C (2002) Reputation and social network analysis in multi-agent systems. In: Proceedings of the first international joint conference on autonomous agents and multiagent systems: part 1, pp 475–482
29.
30.
Saied YB et al (2013) Trust management system design for the internet of things: a context-aware and multi-service approach. Comput Secur 39:351–365 ElsevierCrossRef
31.
Wang Y (2016) System resilience quantification for probabilistic design of internet-of-things architecture. In: ASME 2016 international design engineering technical conferences and computers and information in engineering conference, p V01BT02A011
32.
Wang Y (2017) On social value of risk information in risk communication. ASCE-ASME J Risk Uncertain Eng Syst Part B: Mech Eng (American Society of Mechanical Engineers) 3(4):41009
33.
Wang Y (2018a) Resilience Quantification for probabilistic design of cyber-physical system networks. ASCE-ASME J Risk Uncertain Eng Syst Part B (ASME) 4(3):31006
34.
Wang Y (2018b) Trust based cyber-physical systems network design. In: ASME 2018 international design engineering technical conferences and computers and information in engineering conference, p V01AT02A037–V01AT02A037
35.
Wang Y (2018) Trust quantification for networked cyber-physical systems. IEEE Internet Things J 5(3):2055–2070 IEEECrossRef
36.
Wang Y (2018d) Trustworthiness in designing cyber-physical systems. In: Proceedings of 12th international symposium on tools and methods of competitive engineering (TMCE2018). Las Palmas, Gran Canaria
37.
Yousafzai SY et al (2005) Strategies for building and communicating trust in electronic banking: a field experiment. Psychol Mark 22(2):181–201 Wiley Online LibraryCrossRef
38.
Yu B, Singh M (2000) A social mechanism of reputation management in electronic communities. In: Klusch M, Kerschberg L (eds) Cooperative information agents IV-the future of information agents in cyberspace. Springer, Berlin, Heidelberg, pp 154–165CrossRef
39.
Yu B, Singh MP (2002) Distributed reputation management for electronic commerce. Comput Intell 18(4):535–549 Wiley Online LibraryMathSciNetCrossRef
40.
Zhou P et al (2015) Toward energy-efficient trust system through watchdog optimization for WSNs. IEEE Trans Inf Forensics Secur (IEEE) 10(3):613–625CrossRef
Metadata
Title
Quantifying Trust Perception to Enable Design for Connectivity in Cyber-Physical-Social Systems
Author
Yan Wang
Copyright Year
2020
Book
Emotional Engineering, Vol. 8

Print ISBN: 978-3-030-38359-6

Electronic ISBN: 978-3-030-38360-2

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-38360-2_6

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