Selfish Nodes Research Articles

ARAG: A Routing Algorithm Based on Incentive Mechanisms for DTN With Nodes’ Selfishness

A delay tolerant network (DTN) is a mobile ad hoc network with extremely limited network resources. When DTN is applied in the urban environment, nodes are not willing to consume their limited resources to forward messages for other nodes, or they prefer a relay node that encounters the destination node with a higher probability to forward messages for themselves owing to the characteristics of sociality and selfishness of nodes, which results in poor network performance. To address this issue, a routing algorithm based on incentive mechanisms was proposed in this paper, which is called ARAG. In the process of forwarding message, the algorithm determines the probability of messages received by relay nodes based on the resource consumption of the sender node. Simultaneously, when a source node generates a message, the threshold of copies is set based on the consumption of its resources, and the total number of the same message in the network will not exceed the threshold. Simulation results show that the algorithm is superior to the existing Epidemic algorithm, Prophet algorithm, and GTMEA algorithm in terms of the delivery ratio, the average delay, and network overhead.

A Survey on Human-Centric Communications in Non-Cooperative Wireless Relay Networks

The performance of data delivery in wireless relay networks (WRNs), such as delay-tolerant networks and device-to-device communications heavily relies on the cooperation of mobile nodes (i.e., users and their carried devices). However, selfish nodes may refuse to relay data to others or share their resources with them due to various reasons, such as resource limitations or social preferences. Meanwhile, misbehaving nodes can launch different types of internal attacks (e.g., blackhole and trust-related attacks) to disrupt the normal operation of the network. Numerous mechanisms have been recently proposed to establish secure and efficient communications in WRNs in the presence of selfish and malicious nodes (referred as non-cooperative WRNs). In this paper, we present an in-depth survey on human-centric communication challenges and solutions in the non-cooperative WRNs that focuses on: (1) an overview of the non-cooperative WRNs and introduction to various types of node selfish and malicious behaviors, (2) the impact analysis of node selfish and malicious behaviors on the performance of data forwarding and distribution, (3) selfish and malicious node detection and defense systems, and (4) incentive mechanisms. Finally, we discuss several open problems and future research challenges.

Retaliation-based secured model for enhanced weighted clustering algorithm in mobile ad-hoc network

Mobile Ad-hoc Networks (MANETs) are wireless networks without any fixed infrastructure, consisting of autonomous mobile devices that are interconnected via wireless media. In the recent years MANETs have become one of the most prevalent areas of research because of their inevitable characteristics. However, resource limitations, energy efficiency, scalability and security are the major challenging concerns in MANETs. In this paper, we propose a novel methodology for a secure and fair weighted clustering algorithm using a combination of four parameters: stability factor, degree deviation, sum of distances to a node's neighbours and energy depletion. Our proposed algorithm revolves around three important advantages for clustering. The first is to eliminate the non-eligible nodes to become a cluster head at the initial stage of clustering, which reduces the computation and communication overhead. The second is to elect that node to be a cluster head, which retains its neighbourhood for a longer time period which maintains cluster stability. The third is to retaliate against a selfish node in case of any misbehaviour or non-cooperation using the punishment algorithm and enforcing it to behave normally rather than simply blacklisting that node. The simulation results demonstrate the efficacy of the proposed algorithm compared with the other existing algorithms in terms of different performance metrics.

Trust Awaken Routing for Improving The Reliable Communication in WSN

Wireless Sensor Networks (WSN) is of ubiquitous importance in the present day wireless communication. While disseminated architecture delights a more security and fault-tolerant WSN, such architecture also places a number of security challenges particularly when employed in vital applications such as health care, environment monitoring and battlefield. In this paper, we propose Trust Awaken Routing for Improving the Reliable Communication in WSN. The main objective of this paper is to develop trust management for WSNs, and this technique is used to improve the reliability of data transmission in the network. In this scheme, the trust Awaken Factor is used to select the reliable path from source to destination in the system. trust Awaken Factor computed by node interaction, node recommendation, quick response and node selfishness. The simulation results show the better improvement in throughput and reduce the network delay in the network.

A trust management based on a cooperative scheme in VANET

VANET is a vehicular ad hoc network, which is highly dynamic, self-organised and without a preexisting infrastructure. VANET works properly if the participating vehicles cooperate to ensure the exchange of packets. This special network confronts many constraints, such as attacks of malicious entity and absence of trust between nodes. To solve these problems, we proposed an approach having a decentralised architecture combining two models: the cluster model and the trust management model. Our approach encourages cooperation between vehicles by broadcast packets using the reward concept. It also ensures the detection of selfish nodes using the trust concept. By applying the punishment mechanism, our approach aimed to prevent malicious nodes from disrupting the network by injecting false information. Besides, in our network, we guaranteed authentic forwarding packets which were controlled by the group leader which takes the function of 'watchdog'. Our approach is based on asymmetric cryptography, which used RSA encryption and digital signature to ensure security. The simulation results provided by the NS3 simulator showed that our approach has better performance.

UAV-assisted technique for the detection of malicious and selfish nodes in VANETs

Detecting malicious and selfish nodes is an important task in Vehicular Adhoc NETworks (VANETs). Various proposals adopted trust management as an alternative solution since it is less costly than cryptography-based solution in terms of computation delay and mobility support. However, the existing solutions assume that, in general, the attackers have always a dishonest behavior that persists over time. This assumption may be misleading, as the attackers can behave intelligently to avoid being detected. Moreover, pseudonyms changing strategies to preserve vehicles' privacy are another issue to take into account. In this paper, a new solution for the detection of intelligent malicious behaviors based on the adaptive detection threshold is proposed. In addition to the detection of malicious nodes, our solution relies on Unmanned Aerial Vehicles to face the negative impact of pseudonym changes on the detection process. Our solution also incites attackers to behave well since any malicious behavior will be immediately detected thanks to the adaptive detection threshold adopted. Simulation results depict the high efficiency of our proposal at ensuring high ratios for both detection and packet delivery.

An Energy-Efficient Proactive Routing Scheme for MANET: Game Theoretical Approach of Forwarding with Selfish Nodes

Abstract In Mobile Ad-hoc Networks, nodes exchange packets with each other using intermediate nodes as relays. Since nodes in MANETs are battery powered, energy conservation is a crucial issue. Accepting relay all request may not be in the best interest of a node. But if many nodes prefer not to consume energy in relaying packets on behalf of others, the overall performance of routing in network will be influenced. In this paper we address the energy-efficient routing problem in MANETs with selfish nodes. We modeled this problem as a game-theoretic constraint optimization; we defined the utility of each node as a weighted difference between a performance metric and some transmission costs. A motivate mechanism is proposed in order to induce nodes to forwarding cooperation. Each node independently implements the optimal equilibrium strategy under the given constraints. Simulation results by NS3 simulator show that our proposed approach can improve system performance in network lifetime and packet delivery ratio.

A social-based watchdog system to detect selfish nodes in opportunistic mobile networks

Detecting selfish nodes in opportunistic mobile networks can reduce the loss of network resources, thus improve the data delivery performance. Most of existing detection schemes primarily rely on the nodes’ contact records and do not consider their individual and social preferences in their data relaying behavior, which result in long detection time and high communication overhead. In addition, they cannot distinguish the nodes’ selfishness type and degree, which is important because the charge and rewarding mechanisms applied to stimulate different nodes may not be the same. In this paper, we propose a Social-based Watchdog system (SoWatch) in which watchdog nodes analyze messages received from their encountered nodes with respect to their social tie information to identify the nodes’ selfish behavior in message relaying. Meanwhile, the watchdog nodes apply the second-hand watchdog information received from other nodes to improve the detection time and accuracy. Next, we design a reputation system in which watchdog nodes identify selfish nodes based on their direct and indirect watchdog information and distinguish individually and socially selfish nodes. Furthermore, we design a watchdog evaluation module to protect SoWatch against wrong watchdogs disseminated by malicious nodes in which a watchdog node investigates the truthfulness of the indirect watchdogs before applying them. Our experiments using real-world datasets illustrate that SoWatch outperforms a benchmark contact-based watchdog system in terms of detection time by 45% and detection ratio by 10% with less communication overhead.

Incentive Mechanisms for Data Dissemination in Autonomous Mobile Social Networks

This work focuses on the incorporation of incentive stimulations into data dissemination in autonomous mobile social networks with selfish nodes. The key challenge of enabling incentives is to effectively track the value of a message under such a unique network setting with intermittent connectivity and multiple interest data types. We propose two data dissemination models: the data pulling model where mobile users pull data from data providers, and the data pushing model where data providers generate personalized data and push them to the intended users. For data pulling, we present effective mechanisms to estimate the expected credit reward of a message that helps intermediate nodes to evaluate the potential reward of it. Nodal message communication is formulated as a two-person cooperative game, whose solution is found by a heuristic approach which achieves Pareto optimality. Under the data pushing model, “virtual checks” are introduced to eliminate the needs of accurate knowledge about whom and how many credits data providers should pay. The check buying process is formulated as an online auction model to further accelerate the circulation of credits. Extensive simulations carried out based on real-world traces show the proposed schemes achieve better performance than fully cooperative scheme, but significantly reduce communication cost.

A Location Privacy-Preserving Scheme for VANETs Based on Virtual Mix Zone

The location of vehicles, which may contain some sensitive information, is critical for VANETs security.The literature location privacy-preserving scheme suffers from either selfish vehicle node orvehicle density issues. In this paper, a novel location privacy-preserving scheme for VANETs isproposed based on virtual mix zone which is created dynamically when the pseudonyms of vehiclenodes are going to be expired. Moreover, a reputation model and mechanism is introduced to encouragethe selfish node to join the mix zone. The evaluation and analysis show that the proposedscheme performs better than the typical ones in terms of privacy strength and energy cost.

Self-Organized Relay Selection for Cooperative Transmission in Vehicular Ad-Hoc Networks

Cooperation is a promising paradigm to improve spatial diversity in vehicular ad-hoc networks. In this paper, we pose a fundamental question: How the greediness and selfishness of individual nodes impact cooperation dynamics in vehicular ad-hoc networks. We map the self-interest-driven relay selection decision-making problem to an automata game formulation and present a noncooperative game-theoretic analysis. We show that the relay selection game is an ordinal potential game. A decentralized self-organized relay selection algorithm is proposed based on a stochastic learning approach where each player evolves toward a strategic equilibrium state in the sense of Nash. Furthermore, we study the exact outage behavior of the multirelay decode-and-forward cooperative communication network. Closed-form solutions are derived for the actual outage probability of this multirelay system in both independent and identically distributed channels and generalized channels, which need not assume an asymptotic or high signal-to-noise ratio. Two tight approximations with low computational complexity are also developed for the lower bound of the outage probability. With the exact closed-form outage probability, we further develop an optimization model to determine optimal power allocations in the cooperative network, which can be combined with the decentralized learning-based relay selection. The analysis of the exact and approximative outage behaviors and the convergence properties of the proposed algorithm toward a Nash equilibrium state are verified theoretically and numerically. Simulation results are also given to demonstrate that the resulting cooperative network induced by the proposed algorithm achieves high energy efficiency, transmission reliability, and network-wide fairness performance.

Delay Analysis of Epidemic Schemes in Sparse and Dense Heterogeneous Contact Networks

Epidemic algorithms have found their way into many areas of computer science, such as databases and distributed systems, and recently for communication in Opportunistic or Delay Tolerant Networks (DTNs). To ensure analytical tractability, existing analyses of epidemic spreading predominantly consider homogeneous contact rates between nodes. However, this assumption is generally not true in real scenarios. In this paper, we consider classes of contact/mobility models with heterogeneous contact rates. Through an asymptotic analysis, we prove that a first-order, mean value approximation for the basic epidemic spreading step becomes exact in the limiting case (large network size). We further derive simple closed form approximations, based on higher order statistics of the mobility heterogeneity, for the case of finite-size networks. To demonstrate the utility of our results, we use them to predict the delay of epidemic-based routing schemes and analyze scenarios with node selfishness. We validate the analytic results through extensive simulations on synthetic scenarios, as well as on real traces to demonstrate that our expressions can be useful also in scenarios with significantly more complex structure. We believe these results are an important step forward towards analyzing the effects of heterogeneity (of mobility and/or other characteristics) on the performance of epidemic-based algorithms.

Coexistence with malicious and selfish nodes in wireless ad hoc networks: A Bayesian game approach

Mobile ad hoc networks are self-organized systems of nodes or installations, all cooperating to provide network functions such as routing and forwarding. Utilized in open environments, mobile ad ho...

A Hybrid Trust Management Scheme for Wireless Sensor Networks

Wireless sensor network (WSN) consists of wireless small sensor nodes deployed in the terrain for continuous observation of physical or environmental conditions. The data collected from the WSN is used for making decisions. The condition for making critical decision is to assure the trustworthiness of the data generated from sensor nodes. However, the approaches for scoring the sensed data alone is not enough in WSN since there is an interdependency between node and data item. If the overall trust score of the network is based on one trust component, then the network might be misguided. In this work, we propose the hybrid approach to address the issue by assigning the trust score to data items and sensor nodes based on data quality and communication trust respectively. The proposed hybrid trust management scheme (HTMS) detects the data fault with the help of temporal and spatial correlations. The correlation metric and provenance data are used to score the sensed data. The data trust score is utilized for making decision. The communication trust and provenance data are used to evaluate the trust score of intermediate nodes and source node. If the data item is reliable enough to make critical decisions, a reward is given by means of adding trust score to the intermediate nodes and source node. A punishment is given by reducing the trust score of the source and intermediate nodes, if the data item is not reliable enough to make critical decisions. Result shows that the proposed HTMS detects the malicious, faulty, selfish node and untrustworthy data.

Cross-Layer Resource Optimization for Wireless Relay Networks Under Dynamic Node Selfishness

In this paper, we investigate the cross-layer resource optimization for wireless relay networks with dynamic node-selfishness information. The degree of intrinsic selfishness (DeIS) and the degree of extrinsic selfishness (DeES) of the relay node (RN) are defined as the effects of its own residual energy resource and the incentive in an incentive mechanism, respectively. A model of two-timescale node-selfishness dynamics is constructed to describe the time-varying characteristics of the RN's DeIS and DeES. Based on the two-timescale node-selfishness dynamics of the RNs, a two-timescale resource-optimization dynamical algorithm (TRODA) is employed to control the transmit powers of both RNs and end users (EU), as well as the flow rates of the data packets injected by all EUs. Meanwhile, the stability and the tracking error of the TRODA under the two-timescale node-selfishness dynamics are analyzed by Lyapunov theory. Our simulation results demonstrate that the two-timescale optimization algorithm is stable and has trivial tracking error.

Co-operation Enforcing Reputation-Based Detection Techniques and Frameworks for Handling Selfish Node Behaviour in MANETs: A Review

In Mobile Ad hoc Network, co-operation between mobile nodes is inevitable for enabling reliable network connectivity due to the absence of pre-deployed infrastructure. In such a network, mobile nodes spend significant amount of energy for detecting routes and forwarding packets in order to enforce co-operation. The energy drain of mobile nodes due to the above fact induces them to refuse forwarding of packets for their neighbouring nodes in order to participate in the network. The mobile nodes that forward their own packets but drop the packets received from neighbours are known as selfish nodes. Detecting selfish nodes is one of the most challenging issues that need to be addressed for enforcing co-operation. The core objective of this research work is to essentially identify and highlights various reputation-based selfish node mitigation approaches available in the literature with their merits and limitations. This paper presents context-aware reputation-based selfish node mitigation approaches that are classified into three categories viz., History-based reputation mechanism, Condition probability-based reputation mechanism and Futuristic probability-based reputation mechanism. This paper further presents a review on a number of selfish node mitigation frameworks and also aims in emphasizing the role of statistical reliability co-efficient that could aid in effective and efficient mitigation of selfish nodes.

A New Trusted Routing Protocol for Vehicular Ad Hoc Networks Using Trusted Metrics.

Trusted routing in VANET is a challenging task due to highly dynamic network topologies and openness of wireless architecture. To provide secure routing among the Vehicular Ad-hoc Networks (VANET) and to avoid selfish nodes, an Optimized Node Selection Routing Protocol (Trusted-ONSRP) of VANET has been designed based on trusted metrics using a Trusted Computing Algorithm. The results stated that the T-ONSRP routing shows higher performance in security measures than the existing routing protocols.

Selfish Node Detection in Wireless Networks

Selfish Node Detection in Wireless Networks

TCABRP: A Trust-Based Cooperation Authentication Bit-Map Routing Protocol Against Insider Security Threats in Wireless Ad Hoc Networks

In recent years, threats in wireless ad hoc networks (WANETs) could be further divided into outside and insider threats. It is important to consider that the majority of insider threats come from the users who are fully authorized to use the systems they are accessing. This new situation would greatly inhibit the normal activity for data communications, and cause the WANETs to spend a longer time for delivering the same data volumes. Therefore, a Trust-Based Cooperation Authentication Bit-Map Routing Protocol (TCABRP) against insider threats in WANETs is proposed in this paper. It could reduce the damages away from the insider threats in a WANET. Specifically, the cooperation evaluations are employed that include three factors: cooperative scores, cooperative trust values and authenticated codes. The routing protocol is not only a type of behavioral-based technique but also a kind of efficient cryptographic protocol. The cooperative evaluations route vector could protect the chain of the router vector authentication codes for verifying the delivery process and determining whether it is correct or incorrect. Moreover, the proposed routing protocol in WANET could not only prevent InTs efficiently, but also evaluate the behaviors of the compromised node or a selfish node as well.

Geographic information and node selfish-based routing algorithm for delay tolerant networks

In Delay Tolerant Networks (DTNs), some routing algorithms ignore that most nodes are selfish, i.e., nodes are willing to use their own resources to forward messages to nodes with whom they have a relationship. In view of this phenomenon, we propose a routing algorithm based on Geographic Information and Node Selfishness (GINS). To choose a forwarding node, GINS combines nodes' willingness to forward and their geographic information to maximize the possibility of contacting the destination. GINS formulates the message forwarding process as a 0-1 Knapsack Problem with Assignment Restrictions to satisfy node demands for selfishness. Extensive simulations were conducted, and results show that GINS can achieve a high delivery ratio and a lower hop count compared with GRONE and LPHU. Furthermore, its overhead ratio is 25% and 30% less than that of GRONE and LPHU, respectively.