2,871 research outputs found
Closed-loop feedback computation model of dynamical reputation based on the local trust evaluation in business-to-consumer e-commerce
Trust and reputation are important factors that influence the success of both traditional transactions in physical social networks and modern e-commerce in virtual Internet environments. It is difficult to define the concept of trust and quantify it because trust has both subjective and objective characteristics at the same time. A well-reported issue with reputation management system in business-to-consumer (BtoC) e-commerce is the “all good reputation” problem. In order to deal with the confusion, a new computational model of reputation is proposed in this paper. The ratings of each customer are set as basic trust score events. In addition, the time series of massive ratings are aggregated to formulate the sellers’ local temporal trust scores by Beta distribution. A logical model of trust and reputation is established based on the analysis of the dynamical relationship between trust and reputation. As for single goods with repeat transactions, an iterative mathematical model of trust and reputation is established with a closed-loop feedback mechanism. Numerical experiments on repeated transactions recorded over a period of 24 months are performed. The experimental results show that the proposed method plays guiding roles for both theoretical research into trust and reputation and the practical design of reputation systems in BtoC e-commerce
A Trust Management Framework for Decision Support Systems
In the era of information explosion, it is critical to develop a framework which can extract useful information and help people to make “educated” decisions. In our lives, whether we are aware of it, trust has turned out to be very helpful for us to make decisions. At the same time, cognitive trust, especially in large systems, such as Facebook, Twitter, and so on, needs support from computer systems. Therefore, we need a framework that can effectively, but also intuitively, let people express their trust, and enable the system to automatically and securely summarize the massive amounts of trust information, so that a user of the system can make “educated” decisions, or at least not blind decisions. Inspired by the similarities between human trust and physical measurements, this dissertation proposes a measurement theory based trust management framework. It consists of three phases: trust modeling, trust inference, and decision making. Instead of proposing specific trust inference formulas, this dissertation proposes a fundamental framework which is flexible and can be adapted by many different inference formulas. Validation experiments are done on two data sets: the Epinions.com data set and the Twitter data set. This dissertation also adapts the measurement theory based trust management framework for two decision support applications. In the first application, the real stock market data is used as ground truth for the measurement theory based trust management framework. Basically, the correlation between the sentiment expressed on Twitter and stock market data is measured. Compared with existing works which do not differentiate tweets’ authors, this dissertation analyzes trust among stock investors on Twitter and uses the trust network to differentiate tweets’ authors. The results show that by using the measurement theory based trust framework, Twitter sentiment valence is able to reflect abnormal stock returns better than treating all the authors as equally important or weighting them by their number of followers. In the second application, the measurement theory based trust management framework is used to help to detect and prevent from being attacked in cloud computing scenarios. In this application, each single flow is treated as a measurement. The simulation results show that the measurement theory based trust management framework is able to provide guidance for cloud administrators and customers to make decisions, e.g. migrating tasks from suspect nodes to trustworthy nodes, dynamically allocating resources according to trust information, and managing the trade-off between the degree of redundancy and the cost of resources
A Survey on Trust Computation in the Internet of Things
Internet of Things defines a large number of diverse entities and services which interconnect with each other and individually or cooperatively operate depending on context, conditions and environments, produce a huge personal and sensitive data. In this scenario, the satisfaction of privacy, security and trust plays a critical role in the success of the Internet of Things. Trust here can be considered as a key property to establish trustworthy and seamless connectivity among entities and to guarantee secure services and applications. The aim of this study is to provide a survey on various trust computation strategies and identify future trends in the field. We discuss trust computation methods under several aspects and provide comparison of the approaches based on trust features, performance, advantages, weaknesses and limitations of each strategy. Finally the research discuss on the gap of the trust literature and raise some research directions in trust computation in the Internet of Things
Trust beyond reputation: A computational trust model based on stereotypes
Models of computational trust support users in taking decisions. They are
commonly used to guide users' judgements in online auction sites; or to
determine quality of contributions in Web 2.0 sites. However, most existing
systems require historical information about the past behavior of the specific
agent being judged. In contrast, in real life, to anticipate and to predict a
stranger's actions in absence of the knowledge of such behavioral history, we
often use our "instinct"- essentially stereotypes developed from our past
interactions with other "similar" persons. In this paper, we propose
StereoTrust, a computational trust model inspired by stereotypes as used in
real-life. A stereotype contains certain features of agents and an expected
outcome of the transaction. When facing a stranger, an agent derives its trust
by aggregating stereotypes matching the stranger's profile. Since stereotypes
are formed locally, recommendations stem from the trustor's own personal
experiences and perspective. Historical behavioral information, when available,
can be used to refine the analysis. According to our experiments using
Epinions.com dataset, StereoTrust compares favorably with existing trust models
that use different kinds of information and more complete historical
information
BUILDING TRUST FOR SERVICE ASSESSMENT IN INTERNET-ENABLED COLLABORATIVE PRODUCT DESIGN & REALIZATION ENVIRONMENTS
Reducing costs, increasing speed and leveraging the intelligence of partners involved during product design processes are important benefits of Internet-enabled collaborative product design and realization environments. The options for cost-effective product design, re-design or improvement are at their peak during the early stages of the design process and designers can collaborate with suppliers, manufacturers and other relevant contributors to acquire a better understanding of associated costs and product viability. Collaboration is by no means a new paradigm. However, companies have found distrust of collaborative partners to be the most intractable obstacle to collaborative commerce and Internet-enabled business especially in intellectual property environments, which handle propriety data on a constant basis. This problem is also reinforced in collaborative environments that are distributed in nature. Thus trust is the main driver or enabler of successful collaborative efforts or transactions in Internet-enabled product design environments. Focus is on analyzing the problem of ¡®trust for services¡¯ in distributed collaborative service provider assessment and selection, concentrating on characteristics specific to electronic product design (e-Design) environments. Current tools for such collaborative partner/provider assessment are inadequate or non-existent and researching network, user, communication and service trust problems, which hinder the growth and acceptance of true collaboration in product design, can foster new frontiers in manufacturing, business and technology. Trust and its associated issues within the context of a secure Internet-enabled product design & realization platform is a multifaceted and complex problem, which demands a strategic approach crossing disciplinary boundaries. A Design Environment Trust Service (DETS) framework is proposed to incorporate trust for services in product design environments based on client specified (or default) criteria. This involves the analysis of validated network (objective) data and non-network (subjective) data and the use of Multi Criteria Decision Making (MCDM) methodology for the selection of the most efficient service provision alternative through the minimization of distance from a specified ideal point and interpreted as a Dynamic (Design) Trust Index (DTI) or rank. Hence, the service requestor is provided with a quantifiable degree of belief to mitigate information asymmetry and enable knowledgeable decision-making regarding trustworthy service provision in a distributed environment
Flow-based reputation: more than just ranking
The last years have seen a growing interest in collaborative systems like
electronic marketplaces and P2P file sharing systems where people are intended
to interact with other people. Those systems, however, are subject to security
and operational risks because of their open and distributed nature. Reputation
systems provide a mechanism to reduce such risks by building trust
relationships among entities and identifying malicious entities. A popular
reputation model is the so called flow-based model. Most existing reputation
systems based on such a model provide only a ranking, without absolute
reputation values; this makes it difficult to determine whether entities are
actually trustworthy or untrustworthy. In addition, those systems ignore a
significant part of the available information; as a consequence, reputation
values may not be accurate. In this paper, we present a flow-based reputation
metric that gives absolute values instead of merely a ranking. Our metric makes
use of all the available information. We study, both analytically and
numerically, the properties of the proposed metric and the effect of attacks on
reputation values
SLA-based trust model for secure cloud computing
Cloud computing has changed the strategy used for providing distributed services to many business and government agents. Cloud computing delivers scalable and on-demand services to most users in different domains. However, this new technology has also created many challenges for service providers and customers, especially for those users who already own complicated legacy systems. This thesis discusses the challenges of, and proposes solutions to, the issues of dynamic pricing, management of service level agreements (SLA), performance measurement methods and trust management for cloud computing.In cloud computing, a dynamic pricing scheme is very important to allow cloud providers to estimate the price of cloud services. Moreover, the dynamic pricing scheme can be used by cloud providers to optimize the total cost of cloud data centres and correlate the price of the service with the revenue model of service. In the context of cloud computing, dynamic pricing methods from the perspective of cloud providers and cloud customers are missing from the existing literature. A dynamic pricing scheme for cloud computing must take into account all the requirements of building and operating cloud data centres. Furthermore, a cloud pricing scheme must consider issues of service level agreements with cloud customers.I propose a dynamic pricing methodology which provides adequate estimating methods for decision makers who want to calculate the benefits and assess the risks of using cloud technology. I analyse the results and evaluate the solutions produced by the proposed scheme. I conclude that my proposed scheme of dynamic pricing can be used to increase the total revenue of cloud service providers and help cloud customers to select cloud service providers with a good quality level of service.Regarding the concept of SLA, I provide an SLA definition in the context of cloud computing to achieve the aim of presenting a clearly structured SLA for cloud users and improving the means of establishing a trustworthy relationship between service provider and customer. In order to provide a reliable methodology for measuring the performance of cloud platforms, I develop performance metrics to measure and compare the scalability of the virtualization resources of cloud data centres. First, I discuss the need for a reliable method of comparing the performance of various cloud services currently being offered. Then, I develop a different type of metrics and propose a suitable methodology to measure the scalability using these metrics. I focus on virtualization resources such as CPU, storage disk, and network infrastructure.To solve the problem of evaluating the trustworthiness of cloud services, this thesis develops a model for each of the dimensions for Infrastructure as a Service (IaaS) using fuzzy-set theory. I use the Takagi-Sugeno fuzzy-inference approach to develop an overall measure of trust value for the cloud providers. It is not easy to evaluate the cloud metrics for all types of cloud services. So, in this thesis, I use Infrastructure as a Service (IaaS) as a main example when I collect the data and apply the fuzzy model to evaluate trust in terms of cloud computing. Tests and results are presented to evaluate the effectiveness and robustness of the proposed model
Enhancing trustability in MMOGs environments
Massively Multiplayer Online Games (MMOGs; e.g., World of Warcraft), virtual worlds
(VW; e.g., Second Life), social networks (e.g., Facebook) strongly demand for more
autonomic, security, and trust mechanisms in a way similar to humans do in the real
life world. As known, this is a difficult matter because trusting in humans and organizations
depends on the perception and experience of each individual, which is difficult to
quantify or measure. In fact, these societal environments lack trust mechanisms similar
to those involved in humans-to-human interactions. Besides, interactions mediated
by compute devices are constantly evolving, requiring trust mechanisms that keep the
pace with the developments and assess risk situations.
In VW/MMOGs, it is widely recognized that users develop trust relationships from their
in-world interactions with others. However, these trust relationships end up not being
represented in the data structures (or databases) of such virtual worlds, though they
sometimes appear associated to reputation and recommendation systems. In addition,
as far as we know, the user is not provided with a personal trust tool to sustain his/her
decision making while he/she interacts with other users in the virtual or game world.
In order to solve this problem, as well as those mentioned above, we propose herein a
formal representation of these personal trust relationships, which are based on avataravatar
interactions. The leading idea is to provide each avatar-impersonated player
with a personal trust tool that follows a distributed trust model, i.e., the trust data is
distributed over the societal network of a given VW/MMOG.
Representing, manipulating, and inferring trust from the user/player point of view certainly
is a grand challenge. When someone meets an unknown individual, the question
is “Can I trust him/her or not?”. It is clear that this requires the user to have access to
a representation of trust about others, but, unless we are using an open source VW/MMOG,
it is difficult —not to say unfeasible— to get access to such data. Even, in an open
source system, a number of users may refuse to pass information about its friends, acquaintances,
or others. Putting together its own data and gathered data obtained from
others, the avatar-impersonated player should be able to come across a trust result
about its current trustee. For the trust assessment method used in this thesis, we use
subjective logic operators and graph search algorithms to undertake such trust inference
about the trustee. The proposed trust inference system has been validated using
a number of OpenSimulator (opensimulator.org) scenarios, which showed an accuracy
increase in evaluating trustability of avatars.
Summing up, our proposal aims thus to introduce a trust theory for virtual worlds, its
trust assessment metrics (e.g., subjective logic) and trust discovery methods (e.g.,
graph search methods), on an individual basis, rather than based on usual centralized
reputation systems. In particular, and unlike other trust discovery methods, our methods
run at interactive rates.MMOGs (Massively Multiplayer Online Games, como por exemplo, World of Warcraft),
mundos virtuais (VW, como por exemplo, o Second Life) e redes sociais (como por exemplo,
Facebook) necessitam de mecanismos de confiança mais autónomos, capazes de
assegurar a segurança e a confiança de uma forma semelhante à que os seres humanos
utilizam na vida real. Como se sabe, esta não é uma questão fácil. Porque confiar em
seres humanos e ou organizações depende da percepção e da experiĂŞncia de cada indivĂduo,
o que Ă© difĂcil de quantificar ou medir Ă partida. Na verdade, esses ambientes
sociais carecem dos mecanismos de confiança presentes em interacções humanas presenciais.
Além disso, as interacções mediadas por dispositivos computacionais estão em
constante evolução, necessitando de mecanismos de confiança adequados ao ritmo da
evolução para avaliar situações de risco.
Em VW/MMOGs, é amplamente reconhecido que os utilizadores desenvolvem relações
de confiança a partir das suas interacções no mundo com outros. No entanto, essas relações
de confiança acabam por não ser representadas nas estruturas de dados (ou bases
de dados) do VW/MMOG especĂfico, embora Ă s vezes apareçam associados Ă reputação
e a sistemas de reputação. Além disso, tanto quanto sabemos, ao utilizador não lhe
é facultado nenhum mecanismo que suporte uma ferramenta de confiança individual
para sustentar o seu processo de tomada de decisĂŁo, enquanto ele interage com outros
utilizadores no mundo virtual ou jogo. A fim de resolver este problema, bem como
os mencionados acima, propomos nesta tese uma representação formal para essas relações
de confiança pessoal, baseada em interacções avatar-avatar. A ideia principal
é fornecer a cada jogador representado por um avatar uma ferramenta de confiança
pessoal que segue um modelo de confiança distribuĂda, ou seja, os dados de confiança
sĂŁo distribuĂdos atravĂ©s da rede social de um determinado VW/MMOG.
Representar, manipular e inferir a confiança do ponto de utilizador/jogador, é certamente
um grande desafio. Quando alguĂ©m encontra um indivĂduo desconhecido, a
pergunta é “Posso confiar ou não nele?”. É claro que isto requer que o utilizador tenha
acesso a uma representação de confiança sobre os outros, mas, a menos que possamos
usar uma plataforma VW/MMOG de cĂłdigo aberto, Ă© difĂcil — para nĂŁo dizer impossĂvel
— obter acesso aos dados gerados pelos utilizadores. Mesmo em sistemas de código
aberto, um número de utilizadores pode recusar partilhar informações sobre seus amigos,
conhecidos, ou sobre outros. Ao juntar seus prĂłprios dados com os dados obtidos de
outros, o utilizador/jogador representado por um avatar deve ser capaz de produzir uma
avaliação de confiança sobre o utilizador/jogador com o qual se encontra a interagir.
Relativamente ao método de avaliação de confiança empregue nesta tese, utilizamos
lógica subjectiva para a representação da confiança, e também operadores lógicos da
lĂłgica subjectiva juntamente com algoritmos de procura em grafos para empreender
o processo de inferência da confiança relativamente a outro utilizador. O sistema de
inferência de confiança proposto foi validado através de um número de cenários Open-Simulator (opensimulator.org), que mostrou um aumento na precisão na avaliação da
confiança de avatares.
Resumindo, a nossa proposta visa, assim, introduzir uma teoria de confiança para mundos
virtuais, conjuntamente com métricas de avaliação de confiança (por exemplo, a
lógica subjectiva) e em métodos de procura de caminhos de confiança (com por exemplo,
através de métodos de pesquisa em grafos), partindo de uma base individual, em
vez de se basear em sistemas habituais de reputação centralizados. Em particular, e ao
contrário de outros métodos de determinação do grau de confiança, os nossos métodos
sĂŁo executados em tempo real
- …