Selfish Nodes Research Articles

Reputation and Plausibility Verification based System for Providing Secure Vehicular Networks

In a Vehicular Ad Hoc Network (VANET), node cooperation in packet forwarding is required for the network to function properly. However, since nodes in this networks usually have limited resources, some selfish nodes might intend not to forward packets to save resources for their own use. To discourage such behaviour, we propose a reputation and plausibility verification based system to detect selfish nodes and isolate them. The trustworthiness of the messages are decided upon using sensors, decision making phase and the previous trust value of the node. In the proposed work, depending upon the kind of reputation information a source is attributed with a sender-based reputation level. Only if the event is thought to be prevalent, the trust opinion generator announces this event to the applications. First a node checks whether the event is in its own detection range. If not the decision is made on either the rule of majority or on the trust levels already assigned to the nodes. In case the event is not prevalent, the proposed algorithm also sends a malicious intent information packet in order to inform the neighbour nodes about the detection of a malicious activity. It is likely to be susceptible to more sophisticated attacks, such as collision attacks, because the situation-oriented reputation level allows long-lasting groups of attackers to manipulate a node’s reputation database. The proposed algorithm is better equipped to handle such attacks. It can detect at least such attacks if the node is itself in the detection range. It eliminates attacks pertaining to false event generation completely by utilizing the plausibility of data collected through sensors as well as the trust value of the sending nodes. Reputation value based on mobility is contributed. If the neighbour is having high stability its reputation value is increased..

Trusted GPSR protocol without reputation faking in VANET

In vehicular ad hoc network (VANET), misbehaviors of internal nodes, such as discarding packets, may lead to a rapid decline in packet delivery ratio. To solve this problem, an improvement of greedy perimeter stateless routing (GPSR) protocol is presented. In the new protocol, trustworthiness is considered in the route selection process. The trustworthiness is measured by an objective trust model based on the subjective trust model DyTrust. And the reputation value which reflects the trustworthiness of each node is calculated and broadcasted by the intersection nodes. Specially, besides resisting the packet-discarding behavior of selfish nodes, this protocol also includes a location detection process to resist the location-faking behavior of malicious nodes. As a result, the selfish nodes and the malicious nodes can be excluded from the network. In addition, compared with improved GPSR protocol, the presented one is able to resist one kind of reputation-faking attack and has better performance in simulation.

Game theoretic analysis for pricing-based incentive mechanism in non-dedicated cooperative relay networks

In non-dedicated cooperative relay networks, each node is autonomous and selfish in nature, and thus spontaneous cooperation among nodes is challenged. To stimulate the selfish node to participate in cooperation, a pricing-based cooperation engine using game theory was designed. Firstly, the feasible regions of the charge price and reimbursement price were deduced. Then, the non-cooperative and cooperative games were adopted to analyze the amount of bandwidth that initiating cooperation node (ICN) forwards data through participating cooperation node (PCN) and the amount of bandwidth that PCN helps ICN to relay data. Meanwhile, the Nash equilibrium solutions of cooperation bandwidth allocations (CBAs) were obtained through geometrical interpretation. Secondly, a pricing-based cooperation engine was proposed and a cooperative communication system model with cooperation engines was depicted. Finally, an algorithm based on game theory was proposed to realize the cooperation engine. The simulation results demonstrate that, compared with the system without pricing-based incentive, the proposed system can significantly improve the ICN’s metric measured by bit-per-Joule and increase the PCN’s revenue.

A study on hybrid trust evaluation model for identifying malicious behavior in mobile P2P

P2P network has been widely used because of advantages such as efficient use of network bandwidth, saving of computing resources, and quick information exchange. In particular, the infra that manages each nodes centrally in P2P network does not exist and each node is a structure performing the sender and receiver roles. The service applying P2P technique in MANET is increased because this structure is very similar to the structure of MANET. However, the reliability may be lower by providing an erroneous service from malicious nodes because the supervision of management for nodes participating in P2P does not perform. In this paper, we propose hybrid trust evaluation technique based on Trust Zone structure to improve the reliability between nodes. TZM node is elected for trust evaluation of member nodes internal each TrustZone. The certificate of member nodes is issued in the elected TZM and the information is stored in TZMT. The data transmission of malicious nodes is blocked by limiting the data transmission of nodes that do not issued the certificate. The reputation-based trust management technique was applied to perform the fair file transmission of nodes and block the behavior of selfish nodes. The excellent performance of the proposed technique in this paper was confirmed through experiments.

Modelling of A Trust and Reputation Model in Wireless Networks

Security is the major challenge for Wireless Sensor Networks (WSNs). The sensor nodes are deployed in non controlled environment, facing the danger of information leakage, adversary attacks and other threats. Trust and Reputation models are solutions for this problem and to identify malicious, selfish and compromised nodes. This paper aims to evaluate varying collusion effect with respect to static (SW), dynamic (DW), static with collusion (SWC), dynamic with collusion (DWC) and oscillating wireless sensor networks to derive the joint resultant of Eigen Trust Model. An attempt has been made for the same by comparing aforementioned networks that are purely dedicated to protect the WSNs from adversary attacks and maintain the security issues. The comparison has been made with respect to accuracy and path length and founded that, collusion for wireless sensor networks seems intractable with the static and dynamic WSNs when varied with specified number of fraudulent nodes in the scenario. Additionally, it consumes more energy and resources in oscillating and collusive environments.

On the evaluation of reputation and trust‐based schemes in mobile ad hoc networks

AbstractIn multihop networks such as mobile ad hoc networks selfish or misbehaving nodes can degrade network performance. Reputation and trust‐based schemes have been proposed in order to enforce cooperation and to discourage misbehaving nodes. These schemes detect and isolate selfish nodes and maintain network throughput by enabling nodes to construct paths that only include good nodes. In order to punish selfish nodes and restrict their services, selfish nodes are not provided with packet forwarding services anymore by the good nodes in the network. The aim of these schemes is to increase good nodes' benefit (throughput and utility) and to decrease malicious nodes' benefit. In this paper, we demonstrate that the commonly adopted simulation parameters used by the research community for the evaluation of reputation or trust‐based schemes in mobile environments usually produce biased results. We further demonstrate this fact by adopting a widely used reputation‐based scheme as our case study using the commonly used metrics, such as throughput, utility, delay, and overhead. The simulation parameters are analyzed analytically and via simulations in order to demonstrate their main reason of producing inaccurate and biased results. Finally, we compare simulation and analytical results to corroborate our claim and discuss how to mitigate the resulted inaccuracy and biasness. Copyright © 2015 John Wiley & Sons, Ltd.

Communication based Clustering to Detect Selfish Nodes in MANET

Objective: The main intent of this research is to detect the selfish node in Mobile Ad-hoc Networks (MANETs) and to select the Cluster Head (CH) based on the energy level and Node Communication Ratio (NCR). Methods/Analysis: In this paper, a new mechanism is developed to identify the selfish nodes in the communication network. Based on the level of energy and the Node Communication Ratio, the Cluster Head is selected. The cluster head in turn is used to contribute to the network within its infrastructure range. The sink node will be noticing the behavior of each and every communicating node in the network. Results: The communication based clustering has proved better performance in terms of packet delivery rate, packet loss rate, packet delay rate and better energy efficiency during data transmission. Conclusion: The simulation results show that this scheme has improved quality of service compared to the existing scheme 2Ack. This scheme can be applied in the areas of military operations, emergency and disaster management in order to ensure reliable data delivery on-the-move.

CAMF: Context-Aware Message Forwarding in Mobile Social Networks

In mobile social networks (MSN), with the aim of conserving limited resources, egotistic nodes might refuse to forward messages for other nodes. Different from previous work which mainly focuses on promoting cooperation between selfish nodes, we consider it from a more pragmatic perspective in this paper. Be specific, we regard selfishness as a native attribute of a system and allow nodes to exhibit selfish behavior in the process of message forwarding. Apparently, selfishness has a profound influence on routing efficiency, and thus novel mechanisms are necessary to improve routing performance when self-centered nodes are considered. We first put forward a stateless approach to measure encounter opportunities between nodes, and represent forwarding capabilities of nodes by combining the acquired encounter opportunities with node selfishness. We then quantify receiving capabilities of nodes based on their available buffer size and energy. Taking both forwarding and receiving capabilities into account, we finally present a forwarding set mechanism, which could be deduced to a multiple knapsack problem to maximize the forwarding profit. Consequently, we take all the above studies into the design of a context-aware message forwarding algorithm (CAMF). Extensive trace-driven simulations show that CAMF outperforms other existing algorithms greatly. In fact, it achieves a surprisingly high routing performance while consumes low transmission cost and resource in MSN.

Com-BIS: A Community-Based Barter Incentive Scheme in Socially Aware Networking

Socially aware networking (SAN) provides a new paradigm for intermittently connected networks which exploits social properties of mobile users to guide the design of protocols. In SAN, data forwarding performance will be degraded dramatically due to the existence of users' selfish behaviors. To address the selfishness problem, barter-based incentive scheme is a fair approach in which two encounter nodes exchange the same amount of data with one another. However, it is a challenging issue for nodes to decide when two nodes contact and how many messages they will exchange for their next contacts. We consider this problem as a resource allocation problem and propose a community-based Barter incentive scheme for SAN paradigm (Com-BIS). In this method, network nodes are grouped into communities and they allocate their forwarding services for different communities optimally using 0-1 knapsack algorithm. The simulation results show that Com-BIS stimulates selfish nodes to cooperate in data delivery for other nodes effectively which improves the forwarding performance considerably.

Hash based Technique to Identify the Selfish Node in Mobile Ad-hoc Network

Mobile Ad-hoc NETwork (MANET) is a collection of mobile nodes that communicate with other node without any defined network. The node which decline to share its resource with other nodes is a selfish node. The main idea of selfish node is to drop the data packets and preserve the resource for its own use. The co-operation between the nodes is not guaranteed when the node behaves as selfish nodes. Most of the existing techniques use cryptographic algorithm such as Message Authentication Code (MAC), Rivest Shamir Adelman (RSA) etc, in identifying the selfish node. All of those techniques are take more time to find out the selfish node behavior. This paper applies hash function to identify the misbehaving node. The Hash function is a technique used in the Route Reply (RREP) to authenticate the message, which works in an efficient way. The result shows the better performance in terms of packet delivery ratio up to 70% and time delay has been reduced up to 80% compared to the existing Dynamic Source Routing (DSR) protocol.

Exponential Reliability Coefficient based Reputation Mechanism for isolating selfish nodes in MANETs

In mobile ad hoc networks, cooperation among active mobile nodes is considered to play a vital role in reliable transmission of data. But, the selfish mobile nodes present in an ad hoc environment refuse to forward neighbouring nodes’ packet for conserving its own energy. This intentional selfish behaviour drastically reduces the degree of cooperation maintained between the mobile nodes. Hence, a need arises for devising an effective mechanism which incorporates both energy efficiency and reputation into account for mitigating selfish behaviour in MANETs. In this paper, we propose an Exponential Reliability Coefficient based reputation Mechanism (ERCRM) which isolates the selfish nodes from the routing path based on Exponential Reliability Coefficient (ExRC). This reliability coefficient manipulated through exponential failure rate based on moving average method highlights the most recent past behaviour of the mobile nodes for quantifying its genuineness. From the simulation results, it is evident that, the proposed ERCRM approach outperforms the existing Packet Conservation Monitoring Algorithm (PCMA) and Spilt Half Reliability Coefficient based Mathematical Model (SHRCM) in terms of performance evaluation metrics such as packet delivery ratio, throughput, total overhead and control overhead. Further, this ERCRM mechanism has a successful rate of 28% in isolating the selfish nodes from the routing path. Furthermore, it also aids in framing the exponential threshold point of detection as 0.4, where a maximum number of selfish nodes are identified when compared to the existing models available in the literature.

TR-SDTN: Trust Based Efficient and Scalable Routing in Hostile Social DTNs

A delay tolerant network (DTN) presents a new communication model, which uses a store-carry-forward approach to deliver messages due to the nature of the network. With the development of the mobile internet, the research on DTNs becomes a hot topic. One critical issue in the DTNs with social characteristics is that there could exist selfish and malicious nodes which block important data and as a result intentionally disturb the communication. Although there are many research works which address the issue and adopt various trust models to encourage nodes to forward information, most of them have not considered the social characteristics of the mobile nodes and they have not handled the selfish behaviors and attacks in a systematic way. In view of these defects, we propose a novel solution to address the selfish and security issues in social DTNs. Based on nodes’ social characteristics, a dynamic trust model is proposed to prevent bad-mouthing and ballot stuffing attacks and the Shannon entropy function is introduced to avoid blackhole and greyhole attacks. The simulation results show that our proposed scheme can significantly improve the performance of social DTNs. And the simulation is proved to be consistent with the results from theoretical analysis.

Design and implementation of Not So Cooperative Caching system

Not So Cooperative Caching (NSCC) considers a network comprised of selfish nodes; each is with caching capability and an objective of reducing its own access cost by fetching data from its local cache or from neighboring caches. These nodes would cooperate in caching and share cached content if and only if they each benefit. The challenges are to determine what objects to cache at each node and to implement the system in the context of Information Centric Networking (ICN). This work includes both a solution for the NSCC problem and a design and implementation of an NSCC system in Named Data Networking (NDN), a large effort that exemplifies ICN. Our design applies NDN synchronization protocol to facilitate the information exchange among nodes, adopts group key encryption to control data access within the NSCC group, and offers an error checker to detect error events in the system. Our approach is validated by deploying the system we developed on PlanetLab.

English

English

Efficient elimination of erroneous nodes in cooperative sensing for cognitive radio networks

Cooperative spectrum sensing is a process of achieving spatial diversity gain to make global decision for cognitive radio networks. However, accuracy of global decision effects owing to the presence of malicious users/nodes during cooperative sensing. In this work, an extended generalized extreme studentized deviate (EGESD) method is proposed to eliminate malicious nodes such as random nodes and selfish nodes in the network. The random nodes are carried off based on sample covariance of each node decisions on different frames. Then, the algorithm checks the normality of updated soft data using Shapiro–Wilk test and estimates the expected number of malicious users in cooperative sensing. These are the two essential input parameters required for classical GESD test to eliminate significant selfish nodes accurately. Simulation results reveal that the proposed algorithm can eliminate both random and frequent spectrum sensing data falsification (SSDF) attacks in cooperative sensing and outperforms the existing algorithms.

A Reputation-based Incentive Framework for Mobile Ad Hoc Networks

In mobile ad hoc networks (MANIT), nodes forward the packet to other with the help of intermediate nodes within the transmission range and as they are expected to cooperate to make the networks reliably. In ad hoc network, node may have limited resources. Due to this, some nodes (selfish node) may not to forward packets to save resources for their own use. To discourage such misbehaviour, we propose reputation-based incentive mechanism to motivate the selfish nodes to cooperate in order to packet forwarding. Incentive will be earned by the intermediate nodes which are responsible for forwarding the packet. In this paper, a cluster head will be used as reputation management of each node in the network. This paper highlights various views of cooperation enforcement mechanism and reliability. We perform an overall analysis of our paper by simulation using the network simulator (NS- 2) with the help of AODV protocol. Keywordsncentive scheme; reputation; ad hoc network

Dynamically constructing and maintaining virtual access points in a macro cell with selfish nodes

With the appearance of wireless applications generating a huge volume of traffic, the low-power access points (e.g., pico base stations) are introduced to cellular systems to improve system capacity. However, network operators must make a huge investment in the installation and maintenance. The added relays require flexible site acquisition, which is important yet intractable for network service providers. Therefore, we propose an economical and effective alternative scheme for some outdoor scenarios (e.g., outdoor festivals). The basic idea is that, inspired by a class of cell-based clustering approaches, we partition a macro cell into a number of small cells, such that a connected backbone network can be constructed and maintained by electing a wireless client device from each small cell to build its inter-subcell links (i.e., the links between the neighboring small cells). Also, a new game-based incentive mechanism is proposed and integrated into our cell-based approach to stimulate selfish devices to participate in the construction and maintenance of network backbone. The correctness of this incentive mechanism has been proved. Furthermore, we have also proved that the topology derived from our scheme has the property of robustness. The simulation results indicate that our scheme achieves less control messages and longer network lifetime, compared with the existing cell-based clustering schemes.

A futuristic trust coefficient-based semi-Markov prediction model for mitigating selfish nodes in MANETs

In mobile ad hoc networks (MANETs), network survivability is considered as a potential factor required for maintaining maximum degree of connectivity among the mobile nodes even during failures and attacks. But, the selfish mobile nodes pose devastating influence towards network survivability. Hence, a prediction model that assesses network survivability through stochastic properties derived from nodes’ behaviour becomes essential. This paper proposes a futuristic trust coefficient-based semi-Markov prediction model (FTCSPM) that investigates and quantifies the impact of selfish behaviour towards the survivability of the network. This FTCSPM approach incorporates a non birth-death process for manipulating futuristic trust coefficient since it does not consider the transition of a mobile node from the failed state to a selfish state into account. This semi-Markov prediction model also aids in framing a lower and upper bound for network survivability. Extensive simulations were carried out through ns-2 and the results indicates that FTCSPM show better performance than the existing benchmark mitigation mechanisms like correlated node behaviour model (CNBM), probabilistic behavior model (PBM) and epidemic correlated node behavioural model (ECNBM) proposed for selfish nodes. Further, FTCSPM isolates the selfish nodes rapidly at the rate of 33 % than the considered benchmark systems. Furthermore, the validation of this prediction model performed through Weibull distribution has a high degree of correlation with the simulation results and thus assures the reliability and correctness of the proposed approach. In addition, this approach computes the mean transition time incurred by a mobile node to transit from cooperative to selfish mode as 6.49 s and also identifies the minimum and maximum selfish behaviour detection time as 140 and 180 s, respectively.

GTRF: a game theory approach for regulating node behavior in real-time wireless sensor networks.

The selfish behaviors of nodes (or selfish nodes) cause packet loss, network congestion or even void regions in real-time wireless sensor networks, which greatly decrease the network performance. Previous methods have focused on detecting selfish nodes or avoiding selfish behavior, but little attention has been paid to regulating selfish behavior. In this paper, a Game Theory-based Real-time & Fault-tolerant (GTRF) routing protocol is proposed. GTRF is composed of two stages. In the first stage, a game theory model named VA is developed to regulate nodes’ behaviors and meanwhile balance energy cost. In the second stage, a jumping transmission method is adopted, which ensures that real-time packets can be successfully delivered to the sink before a specific deadline. We prove that GTRF theoretically meets real-time requirements with low energy cost. Finally, extensive simulations are conducted to demonstrate the performance of our scheme. Simulation results show that GTRF not only balances the energy cost of the network, but also prolongs network lifetime.

CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes

Mobile ad-hoc networks (MANETs) assume that mobile nodes voluntary cooperate in order to work properly. This cooperation is a cost-intensive activity and some nodes can refuse to cooperate, leading to a selfish node behaviour. Thus, the overall network performance could be seriously affected. The use of watchdogs is a well-known mechanism to detect selfish nodes. However, the detection process performed by watchdogs can fail, generating false positives and false negatives that can induce to wrong operations. Moreover, relying on local watchdogs alone can lead to poor performance when detecting selfish nodes, in term of precision and speed. This is specially important on networks with sporadic contacts, such as delay tolerant networks (DTNs), where sometimes watchdogs lack of enough time or information to detect the selfish nodes. Thus, we propose collaborative contact-based watchdog (CoCoWa) as a collaborative approach based on the diffusion of local selfish nodes awareness when a contact occurs, so that information about selfish nodes is quickly propagated. As shown in the paper, this collaborative approach reduces the time and increases the precision when detecting selfish nodes.