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Modeling trust and reputation systems in hostile environments

机译：在敌对环境中建模信任和信誉系统

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In many modern network environments, agents of the system have to select optimal service providers who in turn decide to provide different quality of services. This is while maximization of their profits is a concern for both agents and service providers. These environments may also include malicious agents who try to illegally raise up their benefits by deception of honest agents and trampling their benefits. Trust and Reputation Systems (TRSs) are used to control the malicious agents' behavior and to help honest agents improving their decision making quality. Security analysis and robustness evaluation of TRSs in such hostile environments is an important concern and there are a few works to address this problem. However, most of the works in this regard are not based on a proper formal model. Instead, they normally do ad-hoc or intuitive evaluations on specific case studies. There are also a number of works that do model-based analysis and evaluation on TRSs using either simulation or verification methods. However, the proposed models in these works almost suffer from lack of generality, inexpressive formalism, and/or limited applicability. In this paper, we introduce the Trust and Reputation Interaction Model (TRIM) as a comprehensive and expressive model of an interacting agent environment with malicious agents along with an underlying TRS. TRIM has enough expressive power to cover a wide range of TRSs and is able to define advanced complicated attacks. We show that how the runtime behavior of TRIM can be specified as an infinite state homogeneous Markov Decision Process (MDP) tree through the proposed algorithm. To show the applicability of the model, some famous TRSs along with the number of important trust attacks are specified using the proposed formalism. Furthermore, although the focus of this paper is on modeling, we implemented the TRIM Checker as a preliminary tool for robustness verification of TRSs against trust attacks. The specified TRSs are then experimentally evaluated and compared against potential attacks through a novel proposed robustness criterion which is based on MDP analysis. (C) 2019 Elsevier B.V. All rights reserved.
机译：在许多现代网络环境中，系统的代理必须选择最佳服务提供商，而后者又决定提供不同的服务质量。与此相对，代理商和服务提供商都需要最大化他们的利润。这些环境还可能包括恶意代理，这些代理试图通过欺骗诚实代理并践踏其利益来非法提高其利益。信任和信誉系统（TRS）用于控制恶意代理的行为并帮助诚实的代理提高其决策质量。在这样的恶劣环境中，TRS的安全性分析和鲁棒性评估是一个重要的问题，并且有一些工作可以解决这个问题。但是，这方面的大多数作品都不基于适当的形式模型。取而代之的是，他们通常会对特定的案例研究进行临时或直观的评估。还有许多工作使用模拟或验证方法对TRS进行基于模型的分析和评估。然而，这些作品中提出的模型几乎遭受普遍性不足，表达形式主义和/或适用性有限的困扰。在本文中，我们将信任和信誉交互模型（TRIM）引入，将其作为具有恶意代理的交互代理环境以及基础TRS的一种综合，可表达的模型。 TRIM具有足够的表达能力来覆盖各种TRS，并且能够定义高级复杂攻击。我们展示了如何通过所提出的算法将TRIM的运行时行为指定为无限状态齐次马尔可夫决策过程（MDP）树。为了显示该模型的适用性，使用提议的形式主义指定了一些著名的TRS以及重要的信任攻击的数量。此外，尽管本文的重点是建模，但我们将TRIM Checker实施为TRS抵御信任攻击的鲁棒性验证的初步工具。然后，通过基于MDP分析的新型建议稳健性标准，对指定的TRS进行实验评估，并与潜在攻击进行比较。 （C）2019 Elsevier B.V.保留所有权利。

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