Abstract
Trust and reputation systems are decision support tools used to drive parties’ interactions on the basis of parties’ reputation. In such systems, parties rate with each other after each interaction. Reputation scores for each ratee are computed via reputation functions on the basis of collected ratings. We propose a general framework based on Bayesian decision theory for the assessment of such systems, with respect to the number of available ratings. Given a reputation function g and n independent ratings, one is interested in the value of the loss a user may incur by relying on the ratee’s reputation as computed by the system. To this purpose, we study the behaviour of both Bayes and frequentist risk of reputation functions with respect to the number of available observations. We provide results that characterise the asymptotic behaviour of these two risks, describing their limits values and the exact exponential rate of convergence. One result of this analysis is that decision functions based on Maximum-Likelihood are asymptotically optimal. We also illustrate these results through a set of numerical simulations.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Barber, D.: Bayesian Reasoning and Machine Learning. Cambridge University Press (2012)
Boreale, M., Celestini, A.: Asymptotic risk analysis for trust and reputation systems, https://dl.dropbox.com/u/6235789/works/FullRisk.pdf
Boreale, M., Pampaloni, F., Paolini, M.: Quantitative Information Flow, with a View. In: Atluri, V., Diaz, C. (eds.) ESORICS 2011. LNCS, vol. 6879, pp. 588–606. Springer, Heidelberg (2011)
Boukerch, A., Xu, L., EL-Khatib, K.: Trust-based security for wireless ad hoc and sensor networks. Computer Communications 30(11-12), 2413–2427 (2007)
Despotovic, Z., Aberer, K.: A Probabilistic Approach to Predict Peers’ Performance in P2P Networks. In: Klusch, M., Ossowski, S., Kashyap, V., Unland, R. (eds.) CIA 2004. LNCS (LNAI), vol. 3191, pp. 62–76. Springer, Heidelberg (2004)
Ellison, C., Frantz, B., Lampson, B., Rivest, R., Thomas, B., Ylonen, T.: Spki certificate theory. IETF RFC (1999)
ElSalamouny, E., Sassone, V., Nielsen, M.: HMM-Based Trust Model. In: Degano, P., Guttman, J.D. (eds.) FAST 2009. LNCS, vol. 5983, pp. 21–35. Springer, Heidelberg (2010)
Heinrich, G.: Parameter estimation for text analysis. Technical report (2004)
Berger, J.O.: Statistical Decison Theory and Bayesian Analysis. Springer (1985)
Jøsang, A., Ismail, R., Boyd, C.: A survey of trust and reputation systems for online service provision. Decision Support Systems 43(2), 618–644 (2007)
Jøsang, A., Ismail, R.: The beta reputation system. In: Proceedings of Bled eCommerce Conference (2002)
Kulhavý, R.: A kullback-leibler distance approach to system identification. Annual Reviews in Control 20, 119–130 (1996)
Lacoste-Julien, S., Huszár, F., Ghahramani, Z.: Approximate inference for the loss-calibrated bayesian. In: Proceedings of AISTATS (2011)
Leang, C.C., Johnson, D.H.: On the asymptotics of m-hypothesis bayesian detection. IEEE Transactions on Information Theory 43(1), 280–282 (1997)
Palamidessi, C., Alvim, M., Chatzikokolakis, K., Smith, G.: Measuring information leakage using generalized gain functions. In: Proceedings of CSF 2012 (to appear, 2012)
Mui, L., Mohtashemi, M., Halberstadt, A.: A computational model of trust and reputation. In: Proceedings of HICSS, pp. 2431–2439 (2002)
Neuman, B.C., Ts’o, T.: Kerberos: an authentication service for computer networks. IEEE Communications Magazine 32(9), 33–38 (1994)
Nguyen, C.T., Camp, O., Loiseau, S.: A bayesian network based trust model for improving collaboration in mobile ad hoc networks. In: RIVF, pp. 144–151 (2007)
Robert, C.P.: The Bayesian Choice. Springer (2001)
Sassone, V., Nielsen, M., Krukow, K.: Towards a formal framework for computational trust. Formal Methods for Components and Objects 4, 175–184 (2007)
Schlosser, A., Voss, M., Brückner, L.: Comparing and evaluating metrics for reputation systems by simulation. In: Paolucci, et al. [21] (2004)
Cover, T.M., Thomas, J.A.: Elements of Information Theory, 2/e. Addison-Wesley (2006)
Teacy, W.T.L., Patel, J., Jennings, N.R., Luck, M.: Coping with inaccurate reputation sources: Experimental analysis of a probabilistic trust model. In: AAMAS (2005)
Wang, Y., Vassileva, J.: Trust and reputation model in peer-to-peer networks. In: P2P, pp. 150–157 (2003)
Xiong, L., Liu, L.: Peertrust: supporting reputation-based trust for peer-to-peer electronic communities. IEEE TKDE 16(7), 843–857 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Boreale, M., Celestini, A. (2013). Asymptotic Risk Analysis for Trust and Reputation Systems. In: van Emde Boas, P., Groen, F.C.A., Italiano, G.F., Nawrocki, J., Sack, H. (eds) SOFSEM 2013: Theory and Practice of Computer Science. SOFSEM 2013. Lecture Notes in Computer Science, vol 7741. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35843-2_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-35843-2_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35842-5
Online ISBN: 978-3-642-35843-2
eBook Packages: Computer ScienceComputer Science (R0)