Experimenting with Certified Reputation in a Competitive Multi-Agent Scenario

Buccafurri, Francesco; Comi, Antonello; Lax, Gianluca; Rosaci, Domenico

doi:10.1109/mis.2015.98

Cited by 10 publications

(8 citation statements)

References 12 publications

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“…However, as reputation does not require that the agents commit themselves to the truth of the communicated information, a cannot verify the veracity of the b's reputation. Such a characteristic decreases the reputation's immunity to malicious agent behavior [1] [17]. Malicious agents are able to share fake information with other agents, making different types of attacks, as self-promotion and slandering attacks.…”

Section: Certified Reputationmentioning

confidence: 99%

“…In this experiment, we discuss how our model can be configured to deal with the partner selection process. In general, several trust and reputation models in literature make use of the abilities and expertise of agents to select good partners [1] [26] [7]. Nevertheless, as discussed in [4], for some applications, the best partner may not be the most skilled agent.…”

Section: Evaluating Ability and Availabilitymentioning

confidence: 99%

“…In Multi-agent systems (MAS), trust and reputation models have been adopted as an important solution to ensure security and efficiency [1] [2]. These models offer mechanisms to penalize inappropriate behaviors of agents and improve the partner selection process in uncertain situations [3].…”

Section: Introductionmentioning

confidence: 99%

“…• Information sources: in [8], it is assumed that the inputs of the trust model come from beliefs produced through direct experiences of agents. In our approach, the trust measure is computed from the social image (agent's opinion) [3], reputation (third party opinions) [9], references (recommendations about services performed by agents in the past) [1], and the availability of agents. The adoption of multiple sources of information increases the volume of the available information in the system.…”

Section: Introductionmentioning

confidence: 99%

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An Adaptive Trust Model Based on Fuzzy Logic

Baqueta

Morveli-Espinoza

Lugo

et al. 2022

RITA

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In cooperative environments is common that agents delegate tasks to each other to achieve their goals since an agent may not have the capabilities or resources to achieve its objectives alone. However, to select good partners, the agent needs to deal with information about the abilities, experience, and goals of their partners. In this situation, the lack or inaccuracy of information may affect the agent's judgment about a given partner; and hence, increases the risk to rely on an untrustworthy agent. Therefore, in this work, we present a trust model that combines different pieces of information, such as social image, reputation, and references to produce more precise information about the characteristics and abilities of agents. An important aspect of our trust model is that it can be easily configured to deal with different evaluation criteria. For instance, as presented in our experiments, the agents are able to select their partners by availability instead of the expertise level. Besides, the model allows the agents to decide when their own opinions about a partner are more relevant than the opinions received from third parties, and vice-versa. Such flexibility can be explored in dynamic scenarios, where the environment and the behavior of the agents might change constantly.

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Section: Certified Reputationmentioning

confidence: 99%

Section: Evaluating Ability and Availabilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Adaptive Trust Model Based on Fuzzy Logic

Baqueta

Morveli-Espinoza

Lugo

et al. 2022

RITA

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“…This issue has been considered in several recent works e.g. (Rosaci 2012) and (Buccafurri, et al 2016).…”

Section: Lightweight Coordination Calculus (Lcc)mentioning

confidence: 99%

Secure information sharing in social agent interactions using information flow analysis

Bijani

Robertson

Aspinall

2018

Engineering Applications of Artificial Intelligence

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When we wish to coordinate complex, cooperative tasks in open multi-agent systems, where each agent has autonomy and the agents have not been designed to work together, we need a way for the agents themselves to determine the social norms that govern collective behaviour. An effective way to define social norms for agent communication is through the use of interaction models such as those expressed in the Lightweight Coordination Calculus (LCC), a compact executable specification language based on logic programming and pi-calculus. Open multi-agent systems have experienced growing popularity in the multi-agent community and gain importance as large scale distributed systems become more widespread. A major practical limitation to such systems is security, because the very openness of such systems opens the doors to adversaries to exploit vulnerabilities introduced through acceptance of social norms. This paper addresses a key vulnerability of security of open multi-agent systems governed by formal models of social norms (as exemplified by LCC). A fundamental limitation of conventional security mechanisms (e.g. access control and encryption) is the inability to prevent information from being propagated. Focusing on information leakage in choreography systems using LCC, we suggest a framework to detect insecure information flows. A novel security-typed LCC language is proposed to prevent information leakage. Both static (design-time) and dynamic (run-time) security type checking are employed to guarantee no information leakage can occur in annotated agent interaction models. The proposed security type system is discussed and then formally evaluated by proving its properties. Two disadvantages of the pure dynamic analysis are its late detection and its inability to detect implicit information flows. We overcome these issues by performing static analysis. The proposed security type system supports non-interference, i.e. high-security input to the program never affect low-security output. However, it disregards information leaks due to the termination of the program.

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A dynamic stage-based fraud monitoring framework of multiple live auctions

Sadaoui

Wang

2016

Appl Intell

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Xuegang Wang, candidate for the degree of Master of Applied Science in Computer Science, has presented a thesis titled, A Dynamic Stage-Based Fraud Monitoring Framework for Multiple Live Auctions, in an oral examination held on April 21, 2016. The following committee members have found the thesis acceptable in form and content, and that the candidate demonstrated satisfactory knowledge of the subject material.

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Experimenting with Certified Reputation in a Competitive Multi-Agent Scenario

Cited by 10 publications

References 12 publications

An Adaptive Trust Model Based on Fuzzy Logic

An Adaptive Trust Model Based on Fuzzy Logic

Secure information sharing in social agent interactions using information flow analysis

A dynamic stage-based fraud monitoring framework of multiple live auctions

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