ENHANCING PRIVACY IN MULTI-AGENT SYSTEMS

La pérdida de privacidad se está convirtiendo en uno de los mayores problemas en el mundo de la informática. De hecho, la mayoría de los usuarios de Internet (que hoy en día alcanzan la cantidad de 2 billones de usuarios en todo el mundo) están preocupados por su privacidad. Estas preocupaciones también se trasladan a las nuevas ramas de la informática que están emergiendo en los ultimos años. En concreto, en esta tesis nos centramos en la privacidad en los Sistemas Multiagente. En estos sistemas, varios agentes (que pueden ser inteligentes y/o autónomos) interactúan para resolver problemas. Estos agentes suelen encapsular información personal de los usuarios a los que representan (nombres, preferencias, tarjetas de crédito, roles, etc.). Además, estos agentes suelen intercambiar dicha información cuando interactúan entre ellos. Todo esto puede resultar en pérdida de privacidad para los usuarios, y por tanto, provocar que los usuarios se muestren adversos a utilizar estas tecnologías. En esta tesis nos centramos en evitar la colección y el procesado de información personal en Sistemas Multiagente. Para evitar la colección de información, proponemos un modelo para que un agente sea capaz de decidir qué atributos (de la información personal que tiene sobre el usuario al que representa) revelar a otros agentes. Además, proporcionamos una infraestructura de agentes segura, para que una vez que un agente decide revelar un atributo a otro, sólo este último sea capaz de tener acceso a ese atributo, evitando que terceras partes puedan acceder a dicho atributo. Para evitar el procesado de información personal proponemos un modelo de gestión de las identidades de los agentes. Este modelo permite a los agentes la utilización de diferentes identidades para reducir el riesgo del procesado de información. Además, también describimos en esta tesis la implementación de dicho modelo en una plataforma de agentes.Such Aparicio, JM. (2011). ENHANCING PRIVACY IN MULTI-AGENT SYSTEMS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/13023Palanci

The Design of Trust Networks

One can use trust networks to find trustworthy information, people, products, and services on public networks. Hence, they have the potential to combine the advantages of search, recommendation systems, and social networks. But proper design and correct incentives are critical to the success of such networks. In this paper, I propose a trust network architecture that emphasizes simplicity and robustness. I propose a trust network with constrained trust relationships and design a decentralized search and recommendation process. I create both informational and monetary incentives to encourage joining the network, to investigate and discover other trustworthy agents, and to make commitments to them by trusting them, by insuring them, or even by directly investing in them. I show that making the correct judgments about trustworthiness of others and reporting it truthfully are the optimum strategies since they reward the agents both with information by providing access to more of the network and with monetary payments by paying them for their services as information intermediaries. The extensive income potential from the trust connections creates strong incentives to join the network, to create reliable trust connections, and to report them truthfully

Investigating E-commerce Adoption in Small and Medium-sized Tourism Enterprises: A Case of Travel Agents in Egypt

SMEs are often described as slow adopters of technology. However, adopting e-commerce is one of many strategies taken by travel agents to re-intermediate themselves in the global travel market against the threat of disintermediation. Exploratory studies have revealed that Egyptian travel agents are laggards when it comes to technology adoption, although they perceive e-commerce as a beneficial tool that can increase their chances of survival. As many as 59.2% of Egyptian travel agents were found not to have websites (Egyptian Travel Agents Association, 2008), this study investigates the factors affecting e-commerce adoption by travel agents. Past literature has shown that there are three main factors affecting the adoption of e-commerce by SMEs. Environmental pressures push SMEs to adopt in order to bolster their survival chances. The benefits of adoption are critical factors considered by managers when making the adoption decision. Finally, there are barriers to e-commerce adoption. By modifying the technology acceptance model, this research conceptualizes the causal relationships amongst these three types of factors. The benefits and barriers to e-commerce adoption are found to mediate the relationship between environmental pressures and e-commerce adoption. This study employs mixed methods starting with a quantitative survey and following it up with qualitative interviews. A questionnaire was used to collect data from 411 adopter and non-adopter e-commerce travel agents. Later, 22 interviews were conducted with the managers of travel agents. Structural equation modelling produced findings reveal that environmental pressures significantly affect the perceived benefits of and barriers to adoption, in addition to having an indirect effect on adoption behaviour. This study contributes to theory as it responds to the claim that the factors affecting e-commerce adoption have not been well documented in the travel sector (Hung et al., 2011, Thomas et al., 2011), especially in the context of developing countries (Thulani et al., 2010). The findings reveal that the modified technology acceptance model successfully interprets e-commerce adoption. The study compares other adoption models with the research model and provides statistical criteria for this comparison. Its contribution to practice is twofold, affecting the managers of travel agencies and policy makers. Recognizing the factors affecting adoption would enable managers to devise strategies and prepare better agendas for expanding their businesses, while at the same time identifying any defects and training needs that present barriers. Meanwhile, recognizing the barriers to adoption could encourage government bodies and policy makers to implement appropriate measures, such as introducing protective and financial legislation to encourage SMEs to adopt technology, or to formulate national policies and initiatives aimed specifically at supporting the adoption of e-commerce by SMEs.Egyptian Governmen

Computational models of trust for cooperative evolution. Reputation based game theoretic models of trust for cooperative evolution in online business games.

Online services such as e-marketplaces, social networking sites, online gaming environments etc have grown in popularity in the recent years. These services represent situation where participants do not get to negotiate face to face before interaction and most of the time parties to transaction remain anonymous. It is thus necessary to have a system that rightly assesses trustworthiness of the other party in order to maintain quality assurance in such systems. Recent works on Trust and Reputation in online communities have focused on identifying probable defaulters, but less effort has been put to come up with system that make cooperation attractive over defection in order to achieve cooperation without enforcement. Our work in this regard concerns design and investigation of trust assessment systems that not only filter defaulters but also promote evolution of cooperativeness in player society. Based on the concept of game theory and prisoner¿s dilemma, we model business games and design incentive method, compensation method, acquaintance based assessment method and decision theoretic assessment method as mechanisms to assure trustworthiness in online business environments. Effectiveness of each of these methods in promoting the evolution of cooperation in player society has been investigated. Our results show that these methods contribute positively in promoting cooperative evolution. We have further extended our trust assessment model to suit the needs of a mobile ad-hoc network setting. The effectiveness of this model has been tested against its capability to reduce packet drop rate and energy conservation. In both of these the results show promise.EU Asia-link project TH/Asia Link/004(91712) East-West and its local host Kantipur Engineering College in Nepal, and Kathmandu University

Trustworthiness of Web Services

Workflow systems orchestrate various business tasks to attain an objective. Web services can be leveraged to handle individual tasks. Before anyone intends to leverage service components, it is imperative and essential to evaluate the trustworthiness of these services. Therefore, choosing a trustworthy service has become an important decision while designing a workflow system. Trustworthiness can be defined as the likelihood of a service functioning as it is intended. Selection of a service that satisfies business goals involves collecting relevant information such as security mechanisms, reliability, performance and availability. It is important to arrive at total trustworthiness, which incorporates all of the above mentioned multi-facet values relevant to a service. These values can be gathered and analyzed to derive the total trustworthiness of a service. Measuring trustworthiness of a service involves arriving at a suitable value that would help an end-user make a decision for the given business settings. The primary focus of this thesis is to gather relevant details and measure trustworthiness based on inputs provided by the user. A conceptual model was developed after extensive literature review to identify factors that influence trustworthiness of a service. A mechanism was created to gather concept values for a given service and utilize those values to calculate trustworthiness index value. A proof-of-concept prototype was also developed. The prototype is a web-based application that implements the mechanism to measure the trustworthiness of the service. The prototype was evaluated using a scenario-based analysis method to demonstrate the utility of the trustworthiness mechanism using three different scenarios. Results of the evaluation shows that trustworthiness is a multidimensional concept, the relevant conceptual values can be collected, a trustworthiness index value can be calculated based on the gathered concepts, and a trustworthiness index can be interpreted to select the most relevant service for a given requirement

An Exploration of Engagement: A Customer Perspective

This study examines a proposed framework for measuring customer engagement with support from employee engagement literature. Archival data was utilized to evaluate these relationships which included 4.530 participants that were customers of a business-to-business (B2B) organization and utilized the business\u27 website. A similar factor structure resulted for the measurement of customer engagement. Structural equation modeling showed partial support for the hypothesized predictors of engagement (i.e. commitment, brand image, preference and decision making) because the relationship between satisfaction and engagement was not significant. The hypothesized outcome variables of engagement were also partially supported with loyalty, sales, average order value, and website page views demonstrating significant relationships. The implications and future research of customer engagement, e-commerce, and B2B contexts are discussed

Promoting Honesty in Electronic Marketplaces: Combining Trust Modeling and Incentive Mechanism Design

This thesis work is in the area of modeling trust in multi-agent systems, systems of software agents designed to act on behalf of users (buyers and sellers), in applications such as e-commerce. The focus is on developing an approach for buyers to model the trustworthiness of sellers in order to make effective decisions about which sellers to select for business. One challenge is the problem of unfair ratings, which arises when modeling the trust of sellers relies on ratings provided by other buyers (called advisors). Existing approaches for coping with this problem fail in scenarios where the majority of advisors are dishonest, buyers do not have much personal experience with sellers, advisors try to flood the trust modeling system with unfair ratings, and sellers vary their behavior widely. We propose a novel personalized approach for effectively modeling trustworthiness of advisors, allowing a buyer to 1) model the private reputation of an advisor based on their ratings for commonly rated sellers 2) model the public reputation of the advisor based on all ratings for the sellers ever rated by that agent 3) flexibly weight the private and public reputation into one combined measure of the trustworthiness of the advisor. Our approach tracks ratings provided according to their time windows and limits the ratings accepted, in order to cope with advisors flooding the system and to deal with changes in agents' behavior. Experimental evidence demonstrates that our model outperforms other models in detecting dishonest advisors and is able to assist buyers to gain the largest profit when doing business with sellers. Equipped with this richer method for modeling trustworthiness of advisors, we then embed this reasoning into a novel trust-based incentive mechanism to encourage agents to be honest. In this mechanism, buyers select the most trustworthy advisors as their neighbors from which they can ask advice about sellers, forming a social network. In contrast with other researchers, we also have sellers model the reputation of buyers. Sellers will offer better rewards to satisfy buyers that are well respected in the social network, in order to build their own reputation. We provide precise formulae used by sellers when reasoning about immediate and future profit to determine their bidding behavior and the rewards to buyers, and emphasize the importance for buyers to adopt a strategy to limit the number of sellers that are considered for each good to be purchased. We theoretically prove that our mechanism promotes honesty from buyers in reporting seller ratings, and honesty from sellers in delivering products as promised. We also provide a series of experimental results in a simulated dynamic environment where agents may be arriving and departing. This provides a stronger defense of the mechanism as one that is robust to important conditions in the marketplace. Our experiments clearly show the gains in profit enjoyed by both honest sellers and honest buyers when our mechanism is introduced and our proposed strategies are followed. In general, our research will serve to promote honesty amongst buyers and sellers in e-marketplaces. Our particular proposal of allowing sellers to model buyers opens a new direction in trust modeling research. The novel direction of designing an incentive mechanism based on trust modeling and using this mechanism to further help trust modeling by diminishing the problem of unfair ratings will hope to bridge researchers in the areas of trust modeling and mechanism design