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

Peer-to-Peer Networks and Computation: Current Trends and Future Perspectives

This research papers examines the state-of-the-art in the area of P2P networks/computation. It attempts to identify the challenges that confront the community of P2P researchers and developers, which need to be addressed before the potential of P2P-based systems, can be effectively realized beyond content distribution and file-sharing applications to build real-world, intelligent and commercial software systems. Future perspectives and some thoughts on the evolution of P2P-based systems are also provided

A mathematical framework for analyzing incentives in peer-to-peer networks

The existence and performance of peer-to-peer systems depend on thecontribution of resources from interacting peers. One of the challenges ofresource sharing in peer-to-peer systems is free riding. A situation usersattempt to exploit the system by utilizing the resources of others withoutcontributing. We view this from rationality perspective that every peer inthe network will attempt to maximize their utility of the system. In thispaper, we approach the problem of free riders mitigation from utilityoptimization point of view, by modeling each peer's interest as UtilityMaximization Problem (UTP). We propose analytical model for the wholenetwork as a mixed integer linear programming model. The super peers inthe network are given the responsibility of maximizing the utility of all peers connected to them. This is to ensure fairness among the interacting peers and the stability of the entire system. This technique allows peers to either upload or download resources based on their best strategy and interest.Keywords: Free rider, Utility, Peer-to-Peer, Incentives, Maximization,Resource

A connection management protocol for promoting cooperation in Peer-to-Peer networks

Cataloged from PDF version of article.The existence of a high degree of free riding in Peer-to-Peer (P2P) networks is an important threat that should be addressed while designing P2P protocols. In this paper we propose a connection-based solution that will help to reduce the free riding effects on a P2P network and discourage free riding. Our solution includes a novel P2P connection type and an adaptive connection management protocol that dynamically establishes and adapts a P2P network topology considering the contributions of peers. The aim of the protocol is to bring contributing peers closer to each other on the adapted topology and to push the free riders away from the contributors. In this way contribution is promoted and free riding is discouraged. Unlike some other proposals against free riding, our solution does not require any permanent identification of peers or a security infrastructure for maintaining a global reputation system. It is shown through simulation experiments that there is a significant improvement in performance for contributing peers in a network that applies our protocol. © 2007 Elsevier B.V. All rights reserved

Cloud provider capacity augmentation through automated resource bartering

© 2017 Elsevier B.V. Growing interest in Cloud Computing places a heavy workload on cloud providers which is becoming increasingly difficult for them to manage with their primary data centre infrastructures. Resource scarcity can make providers vulnerable to significant reputational damage and it often forces customers to select services from the larger, more established companies, sometimes at a higher price. Funding limitations, however, commonly prevent emerging and even established providers from making a continual investment in hardware speculatively assuming a certain level of growth in demand. As an alternative, they may opt to use the current inter-cloud resource sharing systems which mainly rely on monetary payments and thus put pressure on already stretched cash flows. To address such issues, a new multi-agent based Cloud Resource Bartering System (CRBS) is implemented in this work that fosters the management and bartering of pooled resources without requiring costly financial transactions between IAAS cloud providers. Agents in CRBS collaborate to facilitate bartering among providers which not only strengthens their trading relationships but also enables them to handle surges in demand with their primary setup. Unlike existing systems, CRBS assigns resources by considering resource urgency which comparatively improves customers’ satisfaction and the resource utilization rate by more than 50%. The evaluation results verify that our system assists providers to timely acquire the additional resources and to maintain sustainable service delivery. We conclude that the existence of such a system is economically beneficial for cloud providers and enables them to adapt to fluctuating workloads

Counteracting free riding in pure peer-to-peer networks

Ankara : The Department of Computer Engineering and The Institute of Engineering and Science of Bilkent University, 2008.Thesis (Ph.D.) -- Bilkent University, 2008.Includes bibliographical references leaves 119-127.The peer-to-peer (P2P) network paradigm has attracted a significant amount of interest as a popular and successful alternative to traditional client-server model for resource sharing and content distribution. However, researchers have observed the existence of high degrees of free riding in P2P networks which poses a serious threat to effectiveness and efficient operation of these networks, and hence to their future. Therefore, eliminating or reducing the impact of free riding on P2P networks has become an important issue to investigate and a considerable amount of research has been conducted on it. In this thesis, we propose two novel solutions to reduce the adverse effects of free riding on P2P networks and to motivate peers to contribute to P2P networks. These solutions are also intended to lead to performance gains for contributing peers and to penalize free riders. As the first solution, we propose a distributed and localized scheme, called Detect and Punish Method (DPM), which depends on detection and punishment of free riders. Our second solution to the free riding problem is a connection-time protocol, called P2P Connection Management Protocol (PCMP), which is based on controlling and managing link establishments among peers according to their contributions. To evaluate the proposed solutions and compare them with other alternatives, we developed a new P2P network simulator and conducted extensive simulation experiments. Our simulation results show that employing our solutions in a P2P network considerably reduces the adverse effects of free riding and improves the overall performance of the network. Furthermore, we observed that P2P networks utilizing the proposed solutions become more robust and scalable.Karakaya, K MuratPh.D