Gossip-based aggregation of trust in decentralized reputation systems

Pacheco

2016

Sci Rep

Cooperation has been recognized as an evolutionary puzzle since Darwin, and remains identified as one of the biggest challenges of the XXIst century. Indirect Reciprocity (IR), a key mechanism that humans employ to cooperate with each other, establishes that individual behaviour depends on reputations, which in turn evolve depending on social norms that classify behaviours as good or bad. While it is well known that different social norms give rise to distinct cooperation levels, it remains unclear how the performance of each norm is influenced by the random exploration of new behaviours, often a key component of social dynamics where a plethora of stimuli may compel individuals to deviate from pre-defined behaviours. Here we study, for the first time, the impact of varying degrees of exploration rates – the likelihood of spontaneously adopting another strategy, akin to a mutation probability in evolutionary dynamics – in the emergence of cooperation under IR. We show that high exploration rates may either improve or harm cooperation, depending on the underlying social norm at work. Regarding some of the most popular social norms studied to date, we find that cooperation under Simple-standing and Image-score is enhanced by high exploration rates, whereas the opposite occurs for Stern-judging and Shunning.

Section: Discussionmentioning

confidence: 99%

Evolution of cooperation under indirect reciprocity and arbitrary exploration rates

Pacheco

2016

Sci Rep

IEEE Commun. Surv. Tutorials

“…A gossip based trust aggregation with the gossip average function Push-Sum as an aggregation operator is proposed in [116]. Push-sum is a weighted average aggregation operator derived in [117].…”

Section: Operatorsmentioning

confidence: 99%

Trust Computations and Trust Dynamics in Mobile Adhoc Networks: A Survey

Govindan

Mohapatra

2012

319

181

Trust is an important aspect of mobile adhoc networks (MANETs). It enables entities to cope with uncertainty and uncontrollability caused by the free will of others. Trust computations and management are highly challenging issues in MANETs due to computational complexity constraints, and the independent movement of component nodes. This prevents the direct application of techniques suited for other networks. In MANETs, an untrustworthy node can wreak considerable damage and adversely affect the quality and reliability of data. Therefore, analyzing the trust level of a node has a positive influence on the confidence with which an entity conducts transactions with that node. In this work we present a detailed survey on various trust computing approaches that are geared towards MANETs. We highlight the summary and comparisons of these approaches. In addition, we analyze various works on trust dynamics including trust propagation, prediction and aggregation algorithms, the influence of network dynamics on trust dynamics and the impact of trust on security services.

“…A number of systematic approaches and corresponding architectures for creating reliable trust and reputation systems have been recently proposed in [14][15][16][17][18]. The main scope of these papers is the definitions of variety of settings for decentralized trust and reputation systems.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Efficient private multi-party computations of trust in the presence of curious and malicious users

Gilboa

Kopeetsky

2014

J Trust Manag

Schemes for multi-party trust computation are presented. The schemes do not make use of a Trusted Authority. The schemes are more efficient than previous schemes in terms of the number of messages exchanged, which is proportional to the number of participants rather than to its square. We note that in our schemes the length of each message may be larger than the message length typically found in previously published schemes. The calculation of a trust, in a specific user by a group of community members starts following a request by an initiator. The trust computation is provided in a completely distributed manner, where each user calculates its trust value privately and independently. Given a community C and its members (users) U 1 , . . . , U n , we present computationally secure schemes for trust computation. The first scheme, Accumulated Protocol AP computes the average trust attributed to a specific user, U t following a trust evaluation request initiated by a user U n . The exact trust values of each queried user are not disclosed to U n . The next scheme, Weighted Accumulated Protocol WAP generates the average weighted trust in a specific user U t taking into consideration the unrevealed trust that U n has in each user participating in the trust evaluation process. The Public Key Encryption Protocol PKEP outputs a set of the exact trust values given by the users without linking the user that contributed a specific trust value to the trust this user contributed. The obtained vector of trust values assists in removing outliers. Given the set of trust values, the outliers that provide extremely low or high trust values can be removed from the trust evaluation process. We extend our schemes to the case when the initiator, U n , can be compromised by the adversary, and we introduce the Multiple Private Keys and the Weighted protocols (MPKP and MPWP) for computing average unweighted and weighted trust, respectively. Moreover, the Commutative Encryption Based Protocol (CEBP) extends the PKEBP in this case. The computation of all our algorithms requires the transmission of O(n) (possibly large) messages. Keywords: Private trust computations; Multi-party computations; Anonymity Our contributionThe purpose of this paper is to introduce new schemes for decentralized reputation systems. These schemes do not make use of a Trusted Authority to compute the trust in a particular user that is attributed by a community of users. Our objective is to compute trust while preserving user privacy.We present new efficient schemes for calculating the trust in a specific user by a group of community members upon the request of an initiator. The trust computation is © 2014 Dolev et al.; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Dolev et al. Journal of Trust Management2014, 1:8 Pa...