Collusion in Peer-to-Peer Systems

Peer-to-peer systems have reached a widespread use, ranging from academic and industrial applications to home entertainment. The key advantage of this paradigm lies in its scalability and flexibility, consequences of the participants sharing their resources for the common welfare. Security in such systems is a desirable goal. For example, when mission-critical operations or bank transactions are involved, their effectiveness strongly depends on the perception that users have about the system dependability and trustworthiness. A major threat to the security of these systems is the phenomenon of collusion. Peers can be selfish colluders, when they try to fool the system to gain unfair advantages over other peers, or malicious, when their purpose is to subvert the system or disturb other users. The problem, however, has received so far only a marginal attention by the research community. While several solutions exist to counter attacks in peer-to-peer systems, very few of them are meant to directly counter colluders and their attacks. Reputation, micro-payments, and concepts of game theory are currently used as the main means to obtain fairness in the usage of the resources. Our goal is to provide an overview of the topic by examining the key issues involved. We measure the relevance of the problem in the current literature and the effectiveness of existing philosophies against it, to suggest fruitful directions in the further development of the field

Analysis of a Reputation System for Mobile Ad-Hoc Networks with Liars

The application of decentralized reputation systems is a promising approach to ensure cooperation and fairness, as well as to address random failures and malicious attacks in Mobile Ad-Hoc Networks. However, they are potentially vulnerable to liars. With our work, we provide a first step to analyzing robustness of a reputation system based on a deviation test. Using a mean-field approach to our stochastic process model, we show that liars have no impact unless their number exceeds a certain threshold (phase transition). We give precise formulae for the critical values and thus provide guidelines for an optimal choice of parameters.Comment: 17 pages, 6 figure

Exploring the effects of consumers’ trust : a predictive model for satisfying buyers’ expectations based on sellers’ behaviour in the marketplace

In recent years, Consumer-to-Consumer (C2C) marketplaces have become very popular amongInternet users. However, compared to traditional Business-to-Consumer (B2C) stores, mostmodern C2C marketplaces are reported to be associated with stronger negative sentimentsamong consumers. On the other hand, these negative sentiments are a result of sellers’ inabilityto meet buyers’ expectations. These negative emotions are also linked to the low trustrelationship among sellers and buyers in C2C marketplaces. The growth of these negativeemotions might jeopardize buyers’ decisions to opt for C2C marketplaces in their futurepurchase intentions.In the present study, the concept of trust is explained in a situation characterised by thefollowing aspects: One party (the trustor) is willing to rely on the actions of another party (thetrustee) in a situation in the future to meet his/her expectations. Based on the buyer’s andseller’s behaviour in the C2C marketplace, we were able to quantify the trust emotion found intext. We also performed text mining on Airbnb, a rich source of data in C2C interactions, toquantify the trust level in host descriptions of offered facilities. Specifically, the researchquestions addressed the possibility to infer trust from C2C interactions on Airbnb, as well aswhether it is possible to infer trust from emotions such as joy and fear. The data are acquiredfrom Ashville, and Boston in the USA, Vancouver in Canada and Manchester in the UK. Inline with our expectations, the results of the analysis demonstrate that negative guest feedbackin Airbnb reviews is stronger when the description of the host’s property expresses the emotionof joy only. Conversely, negative guest sentiments in reviews are the weakest when the hostsentiment expressed in Airbnb listings is mixed and expresses different balanced emotions(e.g., joy and fear)

Trust Computational Models for Mobile Ad Hoc Networks. Recommendation Based Trustworthiness Evaluation using Multidimensional Metrics to Secure Routing Protocol in Mobile Ad Hoc Networks.

Distributed systems like e-commerce and e-market places, peer-to-peer networks, social networks, and mobile ad hoc networks require cooperation among the participating entities to guarantee the formation and sustained existence of network services. The reliability of interactions among anonymous entities is a significant issue in such environments. The distributed entities establish connections to interact with others, which may include selfish and misbehaving entities and result in bad experiences. Therefore, trustworthiness evaluation using trust management techniques has become a significant issue in securing these environments to allow entities decide on the reliability and trustworthiness of other entities, besides it helps coping with defection problems and stimulating entities to cooperate. Recent models on evaluating trustworthiness in distributed systems have heavily focused on assessing trustworthiness of entities and isolate misbehaviours based on single trust metrics. Less effort has been put on the investigation of the subjective nature and differences in the way trustworthiness is perceived to produce a composite multidimensional trust metrics to overcome the limitation of considering single trust metric. In the light of this context, this thesis concerns the evaluation of entities’ trustworthiness by the design and investigation of trust metrics that are computed using multiple properties of trust and considering environment. Based on the concept of probabilistic theory of trust management technique, this thesis models trust systems and designs cooperation techniques to evaluate trustworthiness in mobile ad hoc networks (MANETs). A recommendation based trust model with multi-parameters filtering algorithm, and multidimensional metric based on social and QoS trust model are proposed to secure MANETs. Effectiveness of each of these models in evaluating trustworthiness and discovering misbehaving nodes prior to interactions, as well as their influence on the network performance has been investigated. The results of investigating both the trustworthiness evaluation and the network performance are promising.Ministry of Higher Education in Libya and the Libyan Cultural Attaché bureau in Londo

Trusted content-based publish/subscribe trees

Publish/Subscribe systems hold strong assumptions of the expected behaviour of clients and routers, as it is assumed they all abide by the matching and routing protocols. Assumptions of implicit trust between the components of the publish/subscribe infrastructure are acceptable where the underlying event distribution service is under the control of a single or multiple co-operating administrative entities and contracts between clients and these authorities exist, however there are application contexts where these presumptions do not hold. In such environments, such as ad hoc networks, there is the possibility of selfish and malicious behaviour that can lead to disruption of the routing and matching algorithms. The most commonly researched approach to security in publish/subscribe systems is role-based access control (RBAC). RBAC is suitable for ensuring confidentiality, but due to the assumption of strong identities associated with well defined roles and the absence of monitoring systems to allow for adaptable policies in response to the changing behaviour of clients, it is not appropriate for environments where: identities can not be assigned to roles in the absence of a trusted administrative entity; long-lived identities of entities do not exist; and where the threat model consists of highly adaptable malicious and selfish entities. Motivated by recent work in the application of trust and reputation to Peer-to-Peer networks, where past behaviour is used to generate trust opinions that inform future transactions, we propose an approach where the publish/subscribe infrastructure is constructed and re-configured with respect to the trust preferences of clients and routers. In this thesis, we show how Publish/Subscribe trees (PSTs) can be constructed with respect to the trust preferences of publishers and subscribers, and the overhead costs of event dissemination. Using social welfare theory, it is shown that individual trust preferences over clients and routers, which are informed by a variety of trust sources, can be aggregated to give a social preference over the set of feasible PSTs. By combining this and the existing work on PST overheads, the Maximum Trust PST with Overhead Budget problem is defined and is shown to be in NP-complete. An exhaustive search algorithm is proposed that is shown to be suitable only for very small problem sizes. To improve scalability, a faster tabu search algorithm is presented, which is shown to scale to larger problem instances and gives good approximations of the optimal solutions. The research contributions of this work are: the use of social welfare theory to provide a mechanism to establish the trustworthiness of PSTs; the finding that individual trust is not interpersonal comparable as is considered to be the case in much of the trust literature; the Maximum Trust PST with Overhead Budget problem; and algorithms to solve this problem

ADDRESSING SELFISHNESS IN THE DESIGN OF COOPERATIVE SYSTEMS

I sistemi distribuiti cooperativi, tra cui in particolare i sistemi peer-to-peer, sono oggi alla base di applicazioni Internet di larga diffusione come file-sharing e media streaming, nonch\ue9 di tecnologie emergenti quali Blockchain e l'Internet of Things. Uno dei fattori chiave per il successo di un sistema cooperativo \ue8 che i nodi che vi partecipano mettano a disposizione della comunit\ue0 una parte delle proprie risorse (es. capacit\ue0 di calcolo, banda, spazio disco). Alcuni nodi, poich\ue9 controllati da agenti autonomi e indipendenti, potrebbero tuttavia agire egoisticamente e scegliere di non condividere alcuna risorsa, spinti dall'obiettivo di massimizzare la propria utilit\ue0 anche se a danno delle prestazioni dell'intero sistema. Affrontare l'egoismo dei nodi rappresenta dunque un'attivit\ue0 imprescindibile per lo sviluppo di un sistema cooperativo affidabile e performante. Nonostante il grande numero di tecniche ed approcci presenti in letteratura, tale attivit\ue0 richiede elaborazioni complesse, manuali e laboriose, nonch\ue9 conoscenze approfondite in vari domini di applicazione. Obiettivo di questa tesi \ue8 di fornire strumenti sia pratici che teorici per semplificare lo studio e il contrasto dei comportamenti egoistici nei sistemi cooperativi. Il primo contributo, basato su un'analisi esaustiva dello stato dell'arte sull'egoismo in sistemi distribuiti, presenta un framework di classificazione finalizzato all'identificazione e comprensione dei comportamenti egoistici pi\uf9 importanti su cui concentrarsi durante la progettazione di un sistema cooperativo. Come secondo contributo, presentiamo RACOON, un framework per la progettazione e configurazione di sistemi cooperativi resilienti all'egoismo dei nodi. L'obiettivo di RACOON \ue8 di semplificare tali attivit\ue0 fornendo una metodologia generale e semi-automatica, capace di integrare in un dato sistema pratici meccanismi di incentivo alla cooperazione, attentamente calibrati in modo da raggiungere gli obiettivi di resilienza e performance desiderati. A tal fine, RACOON impiega sia strumenti analitici appartenenti alla teoria dei giochi che metodi simulativi, che vengono utilizzati per fare previsioni sul comportamento del sistema in presenza di nodi egoisti. In questa tesi presentiamo inoltre una versione estesa del framework, chiamata RACOON++, sviluppata per migliorare l'accuratezza, flessibilit\ue0 e usabilit\ue0 del framework originale. Infine, come ultimo contributo del lavoro di tesi, presentiamo SEINE, un framework per la rapida modellazione e analisi sperimentale di vari tipi di comportamenti egoistici in un dato sistema cooperativo. Il framework \ue8 basato su un nuovo linguaggio specifico di dominio (SEINE-L) sviluppato per la descrizione degli scenari di egoismo da analizzare. SEINE fornisce inoltre supporto semi-automatico per l'implementazione e lo studio di tali scenari in un simulatore di sistemi distribuiti selezionato dallo stato dell'arte.Cooperative distributed systems, particularly peer-to-peer systems, are the basis of several mainstream Internet applications (e.g., file-sharing, media streaming) and the key enablers of new and emerging technologies, including blockchain and the Internet of Things. Essential to the success of cooperative systems is that nodes are willing to cooperate with each other by sharing part of their resources, e.g., network bandwidth, CPU capability, storage space. However, as nodes are autonomous entities, they may be tempted to behave in a selfish manner by not contributing their fair share, potentially causing system performance degradation and instability. Addressing selfish nodes is, therefore, key to building efficient and reliable cooperative systems. Yet, it is a challenging task, as current techniques for analysing selfishness and designing effective countermeasures remain manual and time-consuming, requiring multi-domain expertise. In this thesis, we aim to provide practical and conceptual tools to help system designers in dealing with selfish nodes. First, based on a comprehensive survey of existing work on selfishness, we develop a classification framework to identify and understand the most important selfish behaviours to focus on when designing a cooperative system. Second, we propose RACOON, a unifying framework for the selfishness-aware design and configuration of cooperative systems. RACOON provides a semi-automatic methodology to integrate a given system with practical and finely tuned mechanisms to meet specified resilience and performance objectives, using game theory and simulations to predict the behaviour of the system when subjected to selfish nodes. An extension of the framework (RACOON++) is also proposed to improve the accuracy, flexibility, and usability of RACOON. Finally, we propose SEINE, a framework for fast modelling and evaluation of various types of selfish behaviour in a given cooperative system. SEINE relies on a domain-specific language for describing the selfishness scenario to evaluate and provides semi-automatic support for its implementation and study in a state-of-the-art simulator.Les syst\ue8mes distribu\ue9s collaboratifs, en particulier les syst\ue8mes pair-\ue0-pair, forment l\u2019infrastructure sous-jacente de nombreuses applications Internet, certaines parmi les plus populaires (ex\ua0: partage de fichiers, streaming multim\ue9dia). Ils se situent \ue9galement \ue0 la base d\u2019un ensemble de technologies \ue9mergentes telles que la blockchain et l\u2019Internet des Objets. Le succ\ue8s de ces syst\ue8mes repose sur la contribution volontaire, de la part des n\u153uds participants, aux ressources partag\ue9es (ex : bande passante r\ue9seau, puissance de calcul, stockage de donn\ue9es). Or ces n\u153uds sont des entit\ue9s autonomes qui peuvent consid\ue9rer comme plus avantageux de se comporter de mani\ue8re \ue9go\uefste, c\u2019est-\ue0- dire de refuser de collaborer. De tels comportements peuvent fortement impacter les performances et la stabilit\ue9 op\ue9rationnelles du syst\ue8me cible. Prendre en compte et pr\ue9venir les comportements \ue9go\uefstes des n\u153uds est donc essentiel pour garantir l\u2019efficacit\ue9 et la fiabilit\ue9 des syst\ue8mes coop\ue9ratifs. Cependant, cela exige du d\ue9veloppeur, en d\ue9pit de la grande quantit\ue9 de techniques et d\u2019approches propos\ue9es dans la litt\ue9rature, des connaissances multisectorielles approfondies. L'objectif de cette th\ue8se est de concevoir et \ue9tudier de nouveaux outils th\ue9oriques et pratiques pour aider les concepteurs de syst\ue8mes distribu\ue9s collaboratifs \ue0 faire face \ue0 des n\u153uds \ue9go\uefstes. La premi\ue8re contribution, bas\ue9e sur une analyse exhaustive de la litt\ue9rature sur les comportements \ue9go\uefstes dans les syst\ue8mes distribu\ue9s, propose un mod\ue8le de classification pour identifier et analyser les comportements \ue9go\uefstes les plus importants sur lesquels il est important de se concentrer lors de la conception d'un syst\ue8me coop\ue9ratif. Dans la deuxi\ue8me contribution, nous proposons RACOON, un framework pour la conception et la configuration de syst\ue8mes coop\ue9ratifs r\ue9silients aux comportements \ue9go\uefstes. Outre un ensemble de m\ue9canismes d'incitation \ue0 la coop\ue9ration, RACOON fournit une m\ue9thodologie semi-automatique d\u2019int\ue9gration et de calibration de ces m\ue9canismes de mani\ue8re \ue0 garantir le niveau de performance souhait\ue9. RACOON s\u2019appuie sur une analyse du syst\ue8me cible fond\ue9e sur la th\ue9orie des jeux et sur des simulations pour pr\ue9dire l\u2019existence de n\u153uds \ue9go\uefstes dans le syst\ue8me. RACOON a \ue9t\ue9 \ue9tendu en un deuxi\ue8me framework, RACOON++. Plus pr\ue9cis, plus flexible, RACOON++ offre \ue9galement une plus grande facilit\ue9 d'utilisation. Une derni\ue8re contribution, SEINE, propose un framework pour la mod\ue9lisation et l'analyse des diff\ue9rents types de comportements \ue9go\uefstes dans un syst\ue8me coop\ue9ratif. Bas\ue9 sur un langage d\ue9di\ue9, d\ue9velopp\ue9 pour d\ue9crire les sc\ue9narios de comportement \ue9go\uefstes, SEINE fournit un support semi-automatique pour la mise en \u153uvre et l'\ue9tude de ces sc\ue9narios dans un simulateur choisi sur la base de l\u2019\ue9tat de l\u2019art (PeerSim)