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.

Effective Usage of Computational Trust Models in Rational Environments

Karl Aberer, Hung Le Vu

Computational reputation-based trust models using statistical learning have been intensively studied for distributed systems where peers behave maliciously. However practical applications of such models in environments with both malicious and rational behaviors are still very little understood. In this paper, we study the relation between their accuracy measures and their ability to enforce cooperation among participants and discourage selfish behaviors. We provide theoretical results that show the conditions under which cooperation emerges when using computational trust models with a given accuracy and how cooperation can be still sustained while reducing the cost and accuracy of those models. Specifically, we propose a peer selection protocol that uses a computational trust model as a dishonesty detector to filter out unfair ratings. We prove that such a model with reasonable misclassification error bound in identifying malicious ratings can effectively build trust and cooperation in the system, considering rationality of participants. These results reveal two interesting observations. First, the key to the success of a reputation system in a rational environment is not a sophisticated trust learning mechanism, but an effective identity management scheme to prevent whitewashing behaviors. Second, given an appropriate identity management mechanism, a reputation-based trust model with a moderate accuracy bound can be used to enforce cooperation effectively in systems with both rational and malicious participants. As a result, in heterogeneous environments where peers use different algorithms to detect misbehavior of potential partners, cooperation may still emerge. We verify and extend these theoretical results to a variety of settings involving honest, malicious and strategic players through extensive simulation. These results will enable a much more targeted, cost-effective and realistic design for decentralized trust management systems, such as needed for peer-to-peer, electronic commerce or community systems.

2011

Haptic interface design and control with application to surgery simulation

Ulrich Spälter

This thesis proposes a framework for haptic devices interacting with virtual environments. As application of the theoretical results a haptic device for the surgical training of hysteroscopy, a gynecologic intervention, is presented. Surgery simulators, which can be described as 'flight simulators for surgeons', comprise a virtual reality for modeling and visualization of organs, and the haptic device: While the surgeon interactively follows the scene on the computer screen, he perceives the contact forces at the tool handle of the surgical instrument. The haptic device tracks the position of the surgery tool and transforms the virtual contact forces to real forces, which can be actually felt by the surgeon. This thesis treats haptic devices with application to surgery simulators for minimally-invasive surgery. Haptic interfaces are complex mechatronic systems and show inherent trade-offs between haptic realism and system stability. Human factors play an important role, as the human operator can both stabilize or destabilize the system. The haptic perception, which can vary between individuals, as a criterion for haptic rendering quality is still not formalized. The optimization of haptic interfaces, within focus of research since 15 years ago, has remained a complex task. However, with look at the emerging applications for haptics, it has become an even more important topic. For this reason it is necessary to integrate mechanical design, control design, mechatronic elements and human factors in a unifying approach. This thesis highlights the principal trade-offs of haptic interfaces and works out design guidelines for new developments and quantitative information on where and how to optimize haptic systems. As application example a haptic interface for the simulation of hysteroscopy, a gynecologic intervention on the female uterus, has been realized as prototype. The device takes the characteristics of hysteroscopy into account and introduces features like insertion and complete removal of the surgery tool from the haptic interface. A design methodology is proposed, which combines aspects of theoretical kinematics based on Lie-Groups with integrated product development – a systematic approach for engineering tasks. The result, a novel kinematic design, has been realized as haptic interface prototype. The well-known affine parameterization for all stabilizing controllers is shown to be a well-suited tool for haptic control synthesis. It provides insights into the control trade-offs and allows to integrate human factors at controller design stage. The resulting controller, demonstrated by experimental results, can reduce parasitic effects (friction, device dynamics) close to and below the human perception threshhold, thus making the device transparent within the specified bandwidth and suitable for real-time implementation. For numerical controller representation the δ-operator is discussed. It unifies continuous and discrete time domain and has beneficial numerical properties. As there is still no standardized procedure for technical performance evaluation of haptic interfaces methods proposed in literature are summarized. In the near future a large market for haptic technology can be expected with applications from surgery-assist devices and drive-by-wire interfaces in automobiles to entertainment, which highlights the relevance of the treated topic.

EPFL2006

Signaling and Reciprocity

Wojciech Galuba

Complex networks exist for a number of purposes. The neural, metabolic and food networks ensure our survival, while the social, economic, transportation and communication networks allow us to prosper. Independently of the purposes and particularities of the physical embodiment of the networks, one of their fundamental functions is the delivery of information from one part of the network to another. Gossip and diseases diffuse in the social networks, electrochemical signals propagate in the neural networks and data packets travel in the Internet. Engineering networks for robust information flows is a challenging task. First, the mechanism through which the network forms and changes its topology needs to be defined. Second, within a given topology, the information must be routed to the appropriate recipients. Third, both the network formation and the routing mechanisms need to be robust against a wide spectrum of failures and adversaries. Fourth, the network formation, routing and failure recovery must operate under the resource constraints, either intrinsic or extrinsic to the network. Finally, the autonomously operating parts of the network must be incentivized to contribute their resources to facilitate the information flows. This thesis tackles the above challenges within the context of several types of networks: 1) peer-to-peer overlays – computers interconnected over the Internet to form an overlay in which participants provide various services to one another, 2) mobile ad-hoc networks – mobile nodes distributed in physical space communicating wirelessly with the goal of delivering data from one part of the network to another, 3) file-sharing networks – networks whose participants interconnect over the Internet to exchange files, 4) social networks – humans disseminating and consuming information through the network of social relationships. The thesis makes several contributions. Firstly, we propose a general algorithm, which given a set of nodes embedded in an arbitrary metric space, interconnects them into a network that efficiently routes information. We apply the algorithm to the peer-to-peer overlays and experimentally demonstrate its high performance, scalability as well as resilience to continuous peer arrivals and departures. We then shift our focus to the problem of the reliability of routing in the peer-to-peer overlays. Each overlay peer has limited resources and when they are exhausted this ultimately leads to delayed or lost overlay messages. All the solutions addressing this problem rely on message redundancy, which significantly increases the resource costs of fault-tolerance. We propose a bandwidth-efficient single-path Forward Feedback Protocol (FFP) for overlay message routing in which successfully delivered messages are followed by a feedback signal to reinforce the routing paths. Internet testbed evaluation shows that FFP uses 2-5 times less network bandwidth than the existing protocols relying on message redundancy, while achieving comparable fault-tolerance levels under a variety of failure scenarios. While the Forward Feedback Protocol is robust to message loss and delays, it is vulnerable to malicious message injection. We address this and other security problems by proposing Castor, a variant of FFP for mobile ad-hoc networks (MANETs). In Castor, we use the same general mechanism as in FFP; each time a message is routed, the routing path is either enforced or weakened by the feedback signal depending on whether the routing succeeded or not. However, unlike FFP, Castor employs cryptographic mechanisms for ensuring the integrity and authenticity of the messages. We compare Castor to four other MANET routing protocols. Despite Castor's simplicity, it achieves up to 40% higher packet delivery rates than the other protocols and recovers at least twice as fast as the other protocols in a wide range of attacks and failure scenarios. Both of our protocols, FFP and Castor, rely on simple signaling to improve the routing robustness in peer-to-peer and mobile ad-hoc networks. Given the success of the signaling mechanism in shaping the information flows in these two types of networks, we examine if signaling plays a similar crucial role in the on-line social networks. We characterize the propagation of URLs in the social network of Twitter. The data analysis uncovers several statistical regularities in the user activity, the social graph, the structure of the URL cascades as well as the communication and signaling dynamics. Based on these results, we propose a propagation model that accurately predicts which users are likely to mention which URLs. We outline a number of applications where the social network information flow modelling would be crucial: content ranking and filtering, viral marketing and spam detection. Finally, we consider the problem of freeriding in peer-to-peer file-sharing applications, when users can download data from others, but never reciprocate by uploading. To address the problem, we propose a variant of the BitTorrent system in which two peers are only allowed to connect if their owners know one another in the real world. When the users know which other users their BitTorrent client connects to, they are more likely to cooperate. The social network becomes the content distribution network and the freeriding problem is solved by leveraging the social norms and reciprocity to stabilize cooperation rather than relying on technological means. Our extensive simulation shows that the social network topology is an efficient and scalable content distribution medium, while at the same time provides robustness to freeriding.

EPFL2011