New Graph Based Trust Similarity Measure

Trust network in social networks can be considered as graph which trustors and trustees are graph vertices and edges present trust between them with measured values. To evaluate trust between trustors and trustees there is some similarity measures to measure similarity between trustors together or trustees together and then by using evaluated values predict trust value between them. Similarity measure has important effect on final accuracy. In this paper we propose graph based similarity measure. Similarity between two users is computed by connection between them on graph then this computed similarity used with k- nearest neighbors method to evaluate(predict) trust between users. To the best of our knowledge this is the first work introduces graph based similarity measure, empirical results on two real datasets show accuracy of predicted trust using proposed similarity measure outperforms accuracy of method without it

روشی نوین برای محاسبه اعتماد در شبکه‌های اجتماعی موبایلی

شبکه‌های اجتماعی موبایلی موجب تسهیل ارتباطات از طریق موبایل می‌شوند که کاربران این شبکه‌ها از موبایل به‌منظور دسترسی، اشتراک و توزیع اطلاعات استفاده می‌کنند. با افزایش روزافزون کاربران در شبکه‌های اجتماعی، حجم زیادی از اطلاعات به اشتراک گذاشته می‌شود که مشکلاتی ازجمله انتشار مطالب نادرست و شایعات دروغ را نیز به دنبال دارد. در این زمینه قوی‌ترین عامل برای سنجش صحت اطلاعات، استفاده از اعتبار هر کاربر به‌عنوان منبع توزیع اطلاعات است. اعتبار هر کاربر به‌عنوان منبع پخش اطلاعات می‌تواند بر اساس اعتماد دیگر کاربران به آن کاربر محاسبه شود. با توجه به ذهنی و ادراکی بودن مفهوم اعتماد، نگاشت اعتماد به یک مدل محاسباتی یکی از مسائل مهم در سیستم‌های محاسباتی شبکه‌های اجتماعی است. ازجمله پیچیدگی‌های فرآیند محاسبه اعتماد در این شبکه‌ها توجه به این موضوع است که در شبکه‌های اجتماعی، اجتماعات گوناگونی وجود داشته که همه کاربران آن‌ها به‌صورت مستقیم به یکدیگر متصل نمی‌باشند. در این مقاله با استفاده از ویژگی‌های کاربران در شبکه‌های اجتماعی، روشی منطبق بر منطق فازی برای دسته‌بندی کاربران پیشنهادشده است که اعتماد بین کاربران واقع در یک دسته با استفاده از مدل پیشنهادی محاسبه می‌شود. هم‌چنین با استفاده از فرآیندهای ترکیب، انتقال و اجتماع اعتمادها، اعتماد بین کاربرانی که به‌صورت مستقیم به یکدیگر متصل نیستند نیز بدست می‌آید. بررسی نتایج بیانگر این مسئله است که روش پیشنهادشده اعتماد افراد را در یک شبکه با دقت قابل قبولی معین می‌سازد

Idealização de um modelo para a compreensão da construção da confiança nas plataformas da economia de partilha

A confiança é um princípio essencial à economia de partilha em rede. Neste contexto, uma experiência de partilha é mediada digitalmente e acontece entre alguém que possui um produto ou serviço para trocar, alugar, vender ou doar à outra pessoa normalmente desconhecida. Diante disto, o trabalho tem como objetivo elaborar um modelo que explique o processo de construção da confiança na economia de partilha. Realizou-se uma revisão da literatura com base na plataforma Scopus a partir das tags ‘sharing economy’; ‘collaborative economy’; ‘trust’; e ‘confidence’. Foram analisados, inicialmente, 135 estudos publicados entre 2013 e 2018. O modelo desenvolvido a partir desta revisão propõe três dimensões psicossociais para a construção da confiança: Affect, Cognitive e Subjective. Para cada uma das três dimensões se identificam um conjunto de critérios hermenêuticos adotados pelos utilizadores das ditas plataformas durante o processo de interação visado à construção da confiança. A primeira considera sobretudo os efeitos emotivos desafiados pelas relações interpessoais na plataforma, em particular a criação de expetativas entre os utilizadores. A dimensão cognitiva remete para a confiança inspirada pela política da plataforma onde ocorrem as interações. Já a dimensão subjetiva compreende os princípios éticos, os objetivos, as propensões e as experiências pessoais que influenciam a construção da confiança dos utilizadores das plataformas. O modelo de construção da confiança permite, portanto, perceber como os utilizadores das plataformas digitais da economia de partilha podem desenvolver parâmetros de confiança. Este modelo também pode ser relevante para estas plataformas melhorarem as estratégias infocomunicacionais e criarem ferramentas de confiança

A cross-domain trust model of smart city IoT based on self-certification

Smart city refers to the information system with Internet of things and cloud computing as the core technology and government management and industrial development as the core content, forming a large-scale, heterogeneous and dynamic distributed Internet of things environment between different Internet of things. There is a wide demand for cooperation between equipment and management institutions in the smart city. Therefore, it is necessary to establish a trust mechanism to promote cooperation, and based on this, prevent data disorder caused by the interaction between honest terminals and malicious terminals. However, most of the existing research on trust mechanism is divorced from the Internet of things environment, and does not consider the characteristics of limited computing and storage capacity and large differences of Internet of things devices, resulting in the fact that the research on abstract trust mechanism cannot be directly applied to the Internet of things; On the other hand, various threats to the Internet of things caused by security vulnerabilities such as collision attacks are not considered. Aiming at the security problems of cross domain trusted authentication of Intelligent City Internet of things terminals, a cross domain trust model (CDTM) based on self-authentication is proposed. Unlike most trust models, this model uses self-certified trust. The cross-domain process of internet of things (IoT) terminal can quickly establish a trust relationship with the current domain by providing its trust certificate stored in the previous domain interaction. At the same time, in order to alleviate the collision attack and improve the accuracy of trust evaluation, the overall trust value is calculated by comprehensively considering the quantity weight, time attenuation weight and similarity weight. Finally, the simulation results show that CDTM has good anti collusion attack ability. The success rate of malicious interaction will not increase significantly. Compared with other models, the resource consumption of our proposed model is significantly reduced

A New Approach for Trust Prediction by using collaborative filtering based of Pareto dominance in Social Networks

Along with the increasing popularity of social web sites, users rely more on the trustworthiness informationfor many online activities among users.[24] However, such social network data often suffers from two problems,(1)severe data sparsity and are not able to provide users with enough information, (2)dataset’s is very large.Therefore, trust prediction has emerged as an important topic in social network research. In this paper weproposed a new approach by using collaborative filtering method and the concept of Pareto dominance. We usesPareto dominance to perform a pre-filtering process eliminating less representative users from the k-neighbourselection process while retaining the most promising ones. The results from experiments performed on FilmTrustdataset and Epinions dataset

Crowdsourcing the identification of organisms: a case-study of iSpot

Accurate species identification is fundamental to biodiversity science, but the natural history skills required for this are neglected in formal education at all levels. In this paper we describe how the web application ispotnature.org and its sister site ispot.org.za (collectively, “iSpot”) are helping to solve this problem by combining learning technology with crowdsourcing to connect beginners with experts. Over 94% of observations submitted to iSpot receive a determination. External checking of a sample of 3,287 iSpot records verified > 92% of them. To mid 2014, iSpot crowdsourced the identification of 30,000 taxa (>80% at species level) in > 390,000 observations with a global community numbering > 42,000 registered participants. More than half the observations on ispotnature.org were named within an hour of submission. iSpot uses a unique, 9-dimensional reputation system to motivate and reward participants and to verify determinations. Taxon-specific reputation points are earned when a participant proposes an identification that achieves agreement from other participants, weighted by the agreers’ own reputation scores for the taxon. This system is able to discriminate effectively between competing determinations when two or more are proposed for the same observation. In 57% of such cases the reputation system improved the accuracy of the determination, while in the remainder it either improved precision (e.g. by adding a species name to a genus) or revealed false precision, for example where a determination to species level was not supported by the available evidence. We propose that the success of iSpot arises from the structure of its social network that efficiently connects beginners and experts, overcoming the social as well as geographic barriers that normally separate the two

LCT: A Lightweight Cross-domain Trust Model for the Mobile Distributed Environment

In the mobile distributed environment, an entity may move across domains with great frequency. How to utilize the trust information in the previous domains and quickly establish trust relationships with others in the current domain remains a challenging issue. The classic trust models do not support cross-domain and the existing cross-domain trust models are not in a fully distributed way