R-bUCRP: A Novel Reputation-Based Uneven Clustering Routing Protocol for Cognitive Wireless Sensor Networks

Energy of nodes is an important factor that affects the performance of Wireless Sensor Networks (WSNs), especially in the case of existing selfish nodes, which attracted many researchers’ attention recently. In this paper, we present a reputation-based uneven clustering routing protocol (R-bUCRP) considering both energy saving and reputation assessment. In the cluster establishment phase, we adopt an uneven clustering mechanism which controls the competitive scope of cluster head candidates to save the energy of WSNs. In the cluster heads election phase, the residual energy and reputation value are used as the indexes to select the optimal cluster head, where the reputation mechanism is introduced to support reputation assessment. Simulation results show that the proposed R-bUCRP can save node energy consumption, balance network energy distribution, and prolong network lifetime

SocialLink: a Social Network Based Trust System for P2P File Sharing Systems

In peer-to-peer (P2P) file sharing systems, many autonomous peers without preexisting trust relationships share files with each other. Due to their open environment and distributed structure, these systems are vulnerable to the significant impact from selfish and misbehaving nodes. Free-riding, whitewash, collusion and Sybil attacks are common and serious threats, which severely harm non-malicious users and degrade the system performance. Many trust systems were proposed for P2P file sharing systems to encourage cooperative behaviors and punish non-cooperative behaviors. However, querying reputation values usually generates latency and overhead for every user. To address this problem, a social network based trust system (i.e., SocialTrust) was proposed that enables nodes to first request files from friends without reputation value querying since social friends are trustable, and then use trust systems upon friend querying failure when a node\u27s friends do not have its queried file. However, trust systems and SocialTrust cannot effectively deal with free-riding, whitewash, collusion and Sybil attacks. To handle these problems, in this thesis, we introduce a novel trust system, called SocialLink, for P2P file sharing systems. By enabling nodes to maintain personal social network with trustworthy friends, SocialLink encourages nodes to directly share files between friends without querying reputations and hence reduces reputation querying cost. To guarantee the quality of service (QoS) of file provisions from non-friends, SocialLink establishes directionally weighted links from the server to the client with successful file transaction history to constitute a weighted transaction network , in which the link weight is the size of the transferred file. In this way, SocialLink prevents potential fraudulent transactions (i.e., low-QoS file provision) and encourages nodes to contribute files to non-friends. By constraining the connections between malicious nodes and non-malicious nodes in the weighted transaction network, SocialLink mitigates the adverse effect from whitewash, collusion and Sybil attacks. By simulating experiments, we demonstrate that SocialLink efficiently saves querying cost, reduces free-riding, and prevents damage from whitewash, collusion and Sybil attacks

TrustedKad - Application of Trust Mechanisms to a Kademlia-Based Peer-to-Peer Network

Peer-to-Peer-Netzwerke (P2P) sind verteilte Systeme, die aus gleichberechtigten Knoten („Peers“) bestehen. Im Gegensatz zu klassischen Client-Server-Systemen gibt es in P2P-Netzwerken keine hierarchischen Ebenen oder zentrale Kontrolleinheiten: Alle Peers bieten gleichzeitig Dienste an und nutzen sie. Im vergangenen Jahrzehnt ist eine Vielzahl verschiedener P2P-Anwendungen entwickelt worden – Filesharing-Anwendungen wie BitTorrent und eMule und Kommunikations-Anwendungen wie Skype gehören zu den bekanntesten von ihnen. Forschungsarbeiten haben gezeigt, dass P2P-Netzwerke anfällig für verschiedene Arten von Angriffen sind. Bekannte Angriffe sind z.B. die Sybil- und die Eclipse-Attack. Die üblichen Gegenmaßnahmen gegen die Angriffe sind Replikation und das Verwenden von disjunkten Routing-Pfaden, um die Wahrscheinlichkeit zu reduzieren, während einer Routing- oder Storage-Operation mit bösartigen Knoten zu interagieren. Seit einiger Zeit wird die Anwendung von Vertrauensmechanismen auf P2P-Netzwerke untersucht. Existierende Arbeiten betrachten meist unstrukturierte P2P-Netzwerke – in realen Umgebungen überwiegen jedoch die strukturierten Netzwerke. Insbesondere Implementierungen des Kademlia-Algorithmus‘ sind weit verbreitet, da er von BitTorrent und eMule genutzt wird. Dennoch versucht keiner der vertrauensbasierten Ansätze, die strukturierte Netzwerke behandeln, speziell die Sicherheit von Kademlia zu verbessern. Aufgrund der Verbreitung von Kademlia wird TrustedKad vom Autor entwickelt, um die Sicherheit des Kademlia-Algorithmus‘ zu verbessern. In dieser Arbeit wird TrustedKad eingeführt und die Funktionsweise erläutert. TrustedKad bewertet das Verhalten von Knoten nach Routing- oder Storage-Operationen als entweder positiv oder negativ. Dafür definiert TrustedKad unter Berücksichtigung der Funktionsweise von Kademlia die Regeln, nach denen gut- und bösartiges Verhalten identifiziert wird. Basierend auf diesen Bewertungen werden Vertrauenswerte für Routing und Storage berechnet, um gutartige und bösartige Knoten zu erkennen. Jeder Knoten nutzt Schwellwerte für diese Vertrauenswerte, um zu entscheiden, welche Knoten er als vertrauenswürdig ansieht. Nicht vertrauenswürdige Knoten werden während der eigenen Operationen eines Knotens vermieden. Darüber hinaus nutzt TrustedKad zusätzliche Sicherheitsfunktionen, um die Sicherheit des Systems weiter zu erhöhen. Diese werden im Verlauf dieser Arbeit vorgestellt. Um TrustedKad zu evaluieren, wird es in einer Simulationsumgebung implementiert und analysiert. Die in dieser Arbeit präsentierten Ergebnisse zeigen, dass TrustedKad in der Lage ist, gutartige und bösartige Knoten zu unterscheiden. Es wehrt verschiedene Variationen von bekannten Angriffen ab und verbessert die Sicherheit von Kademlia-basierten Netzwerken deutlich.Peer-to-peer networks (P2P) are distributed systems that consist of equal nodes (“peers”). In contrast to classic client/server systems, there is no hierarchy or central entity: All peers offer services and use them at the same time. In the past decade, a multitude of different P2P applications has been developed – filesharing applications such as BitTorrent and eMule and communication applications such as Skype are among the most popular of them. Research has shown that P2P networks are vulnerable to different kinds of attacks. Known attacks include, e.g., the Sybil attack and the Eclipse attack. Traditional countermeasures against the attacks are replication and the usage of disjoint routing paths to reduce the probability of interacting with malicious nodes during a routing or storage operation. More recently, trust mechanisms have been proposed and analyzed for applicability to P2P networks. The existing related work mostly targets unstructured P2P networks – however, in real-world environments, the structured networks prevail. Especially implementations of the Kademlia algorithm are widely spread, as it is used by BitTorrent and eMule. Nevertheless, none of the trust-based approaches that aim at structured networks specifically attempts to enhance Kademlia’s security. Due to Kademlia’s prevalence, TrustedKad is particularly designed by the author to improve the security of the Kademlia algorithm. In this thesis, TrustedKad is introduced and its functioning is explained. TrustedKad rates the behavior of nodes after routing and storage operations as either positive or negative. To do so, it defines the rules by which inoffensive and malicious behavior is identified in dependence of the functioning of the Kademlia algorithm. Based on the ratings, routing and storage trust values are calculated to identify inoffensive and malicious nodes. Every node uses thresholds for these trust values to decide which nodes it regards as trustworthy. Non-trustworthy nodes are avoided during a node’s own operations. Furthermore, TrustedKad uses additional security features to further increase the security of the system. They are introduced in this thesis. In order to evaluate TrustedKad, it is implemented and analyzed in a simulation environment. The results presented in this thesis show that TrustedKad is able to distinguish inoffensive and malicious nodes. It counters miscellaneous variations of known attacks and improves the security of Kademlia-based networks considerably