Employing Trusted Computing for the forward pricing of pseudonyms in reputation systems

Reputation and recommendation systems are fundamental for the formation of community market places. Yet, they are easy targets for attacks which disturb a market's equilibrium and are often based on cheap pseudonyms used to submit ratings. We present a method to price ratings using trusted computing, based on pseudonymous tickets.Comment: Refereed contribution to the 4th International Workshop for Technical, Economic and Legal Aspects of Business Models for Virtual Goods, December 13 -15, 2006 on AXMEDIS 2006 in Leeds, England. 5 pages, 3 figures, final versio

Trustworthy content push

Delivery of content to mobile devices gains increasing importance in industrial environments to support employees in the field. An important application are e-mail push services like the fashionable Blackberry. These systems are facing security challenges regarding data transport to, and storage of the data on the end user equipment. The emerging Trusted Computing technology offers new answers to these open questions.Comment: 4 pages, 4 eps figure

From Social Data Mining to Forecasting Socio-Economic Crisis

Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data mining, progress in these areas seems hard or impossible. Therefore, a suitable, distributed data mining infrastructure and research centers should be built in Europe. It also appears appropriate to build a network of Crisis Observatories. They can be imagined as laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human techno-socio-economic systems, so as to gain early warnings of impending events. Reality mining provides the chance to adapt more quickly and more accurately to changing situations. Further opportunities arise by individually customized services, which however should be provided in a privacy-respecting way. This requires the development of novel ICT (such as a self- organizing Web), but most likely new legal regulations and suitable institutions as well. As long as such regulations are lacking on a world-wide scale, it is in the public interest that scientists explore what can be done with the huge data available. Big data do have the potential to change or even threaten democratic societies. The same applies to sudden and large-scale failures of ICT systems. Therefore, dealing with data must be done with a large degree of responsibility and care. Self-interests of individuals, companies or institutions have limits, where the public interest is affected, and public interest is not a sufficient justification to violate human rights of individuals. Privacy is a high good, as confidentiality is, and damaging it would have serious side effects for society.Comment: 65 pages, 1 figure, Visioneer White Paper, see http://www.visioneer.ethz.c

From social data mining to forecasting socio-economic crises

Abstract.: The purpose of this White Paper of the EU Support Action "Visioneer”(see www.visioneer.ethz.ch) is to address the following goals: 1. Develop strategies to quickly increase the objective knowledge about social and economic systems. 2. Describe requirements for efficient large-scale scientific data mining of anonymized social and economic data. 3. Formulate strategies how to collect stylized facts extracted from large data set. 4. Sketch ways how to successfully build up centers for computational social science. 5. Propose plans how to create centers for risk analysis and crisis forecasting. 6. Elaborate ethical standards regarding the storage, processing, evaluation, and publication of social and economic dat

High Quality P2P Service Provisioning via Decentralized Trust Management

Trust management is essential to fostering cooperation and high quality service provisioning in several peer-to-peer (P2P) applications. Among those applications are customer-to-customer (C2C) trading sites and markets of services implemented on top of centralized infrastructures, P2P systems, or online social networks. Under these application contexts, existing work does not adequately address the heterogeneity of the problem settings in practice. This heterogeneity includes the different approaches employed by the participants to evaluate trustworthiness of their partners, the diversity in contextual factors that influence service provisioning quality, as well as the variety of possible behavioral patterns of the participants. This thesis presents the design and usage of appropriate computational trust models to enforce cooperation and ensure high quality P2P service provisioning, considering the above heterogeneity issues. In this thesis, first I will propose a graphical probabilistic framework for peers to model and evaluate trustworthiness of the others in a highly heterogeneous setting. The framework targets many important issues in trust research literature: the multi-dimensionality of trust, the reliability of different rating sources, and the personalized modeling and computation of trust in a participant based on the quality of services it provides. Next, an analysis on the effective usage of computational trust models in environments where participants exhibit various behaviors, e.g., honest, rational, and malicious, will be presented. I provide theoretical results showing the conditions under which cooperation emerges when using trust learning models with a given detecting accuracy and how cooperation can still be sustained while reducing the cost and accuracy of those models. As another contribution, I also design and implement a general prototyping and simulation framework for reputation-based trust systems. The developed simulator can be used for many purposes, such as to discover new trust-related phenomena or to evaluate performance of a trust learning algorithm in complex settings. Two potential applications of computational trust models are then discussed: (1) the selection and ranking of (Web) services based on quality ratings from reputable users, and (2) the use of a trust model to choose reliable delegates in a key recovery scenario in a distributed online social network. Finally, I will identify a number of various issues in building next-generation, open reputation-based trust management systems as well as propose several future research directions starting from the work in this thesis