Presence Of Selfish Nodes Research Articles

An artificial immune system‐based algorithm for selfish node detection in Mobile Ad Hoc Networks (MANETs)

AbstractThe Mobile Ad Hoc Network (MANET) depending on dynamic distributed topology presents several challenges such as decentralized infrastructure. In MANET, each node act as a host as well as a router to exchange packet. From Source to destination, the MANET nodes offer the ability of transmission to send, receive, and route traffic. Moreover, the presence of selfish nodes or malicious nodes in MANETs significantly degrades network performance. Identifying and isolating such nodes poses a formidable challenge. Consequently, this research introduces a security model founded on the principles of an Artificial Immune System (AIS) to detect and defend against Selfish Node (SN) attacks. This research work employs the principles of AIS to categorize a node's behavioral state based on the Mature Context Immune Antigen Rate (MCIAR). Subsequently, a hybrid protocol named Reliable History‐dependent Resource Conscious Clustered and Defensive AODV (RRCC‐DAODV) is introduced to detect Selfish Nodes (SNs) and counteract their attacks. Within the RRCC algorithm, the identification of selfish nodes relies on both Trust Value (TV) and Residual Energy (RE). Additionally, the proposed DAODV protocol incorporates the V‐detector algorithm to enhance defense mechanisms against potential attacks. The simulation of the proposed model is carried out in NS3. The proposed mechanism achieves a detection ratio of 94.05%. The simulation outcomes demonstrate the excellence of the implemented system. This superiority is observed when compared to other standard protocols, as indicated by the parameters of throughput, residual energy, packet delivery ratio, and delay.

Identification and Mitigation of the Selfish Node and Its Behavior in WMN

In Wireless Sensor Network (WSN) communication, every node transmits data packets to further nodes and spend its resources like battery power, CPU time and memory. In ideal situation all the nodes forward packets to other nodes according to their requirements .Presence of selfish nodes is a very big issue in WSNs. A selfish node doesn't forward packets and utilize to its own profit but it is hesitating using personal resources for others. If such activities occurs within most of the nodes in the network, the network is disrupted. Selfish behavior detection and punishment is an essential requirement in wireless sensor networks. In our paper we have described an efficient algorithm for detection and punishment of a selfish node and the necessary action to be taken if the node is a critical node.

Enhancing the Communication of IoT Using African Buffalo Delay Tolerant and Risk Packet Jump Approach

The Internet of Things is used in many sectors for different applications in an efficient way. However, sharing huge data to distant destinations is a difficult task such as sending large data from remote area for healthcare application. So that the Delay Tolerant Network is used but, in some cases, the presence of selfish nodes in Delay Tolerant Network may drop all the packets. To overcome this problem the current research affords a novel African Buffalo Delay Tolerant Network with Risk Packet Jump (ABDTN –RPJ) mechanism to improve the communication channel by predicting the selfish and misbehavior node in an earlier stage. Besides, RPJ is introduced to split the huge data to the other neighboring nodes to reduce packet load on the node if the load is greater than the capacity of the node. Finally, the ABDTN –RPJ is implemented and evaluated using the NS2 simulator. The comparison results proved the efficiency of the proposed model by reducing the delay and drop rate.

PUSR: Position Update Secure Routing protocol for MANET

Mobile ad hoc network is a self-organizing wireless network, which is formed by the wireless mobile devices without any centralized infrastructure. The mobile nodes in the network are mainly affected by the inherent characteristics such as unpredictable network topology and open wireless medium. Especially, the presence of selfish nodes in the network creates the packet loss and affects an entire communication system. In this paper, the hash function with position updating algorithm is proposed in the Ad hoc On-Demand Distance Vector (AODV) routing protocol for improving the security against the selfish nodes. The AODV routing protocol is used to transmit the data packets from the source to the destination. Therefore, the Prevention of Selfish Node using Hash Function (PSNHF) with position update algorithm is proposed for minimizing the packet loss through the network. The performances of proposed AODV-PSNHF method are analysed in terms of energy consumption, throughput, Packet Delivery Ratio (PDR), packet loss and normalized routing load. In addition, the AODV-PSNHF method is compared with the existing trust-aware ad-hoc routing protocol (T2AR). The selfish node identification using hash function and positioning update using AODV-PSNHF method provides reliable and secure data transmission under selfish nodes and shows better performance in terms of throughput, packet delivery ratio and packet loss. For 2% of malicious nodes the PDR of the AODV-PSNHF method is 89%, it is 9% higher when compared to the T2AR protocol whose PDR% is only 80% for the same.

DEFENSE STRATEGY AGAINST SELFISH NODES TAKING INTO ACCOUNT TRAFFIC DIFFERENTIATION IN VEHICULAR DELAY-TOLERANT NETWORKS

Vehicular Delay-Tolerant Networks (VDTNs) are vehicle networks where there is no end-to-end connectivity between source and destination. As a result, VDTNs rely on cooperation between the different nodes to improve its performance. However, the presence of selfish nodes that refuse to participate in the routing protocol causes a deterioration of the overall performance of these networks. In order to reduce the impact of these selfish nodes, proposed strategies, on the one hand, use the nodes transmission rate that does not take into account the message priority class of service, and on the other hand, are based on traditional buffer management systems (FIFO, Random). As a result, quality of service is not guaranteed in this type of network where different applications are derived from messages with different priorities. In this paper, we propose a strategy for detecting selfish nodes and taking action against them in relation to priority classes in order to reduce their impacts. The operation of this strategy is based, on a partitioned memory management system taking into account the priority and the lifetime of messages, on the calculation of the transmission rate of the node with respect to the priority class of the node with the highest delivery predictability, on a mechanism for calculating the nodes degree of selfishness with respect to the priority class, and on the monitoring mechanism. . The simulations carried out show that the proposed model can detect selfish nodes and improve network performance in terms of increasing the delivery rate of high-priority messages, reducing the delivery delay of high-priority messages, and reducing network overload.

282 Published By: Blue Eyes Intelligence Engineering and Sciences Publication Retrieval Number: 100.1/ijitee.A4813119119 DOI: 10.35940/ijitee.A4813.1091220 Journal Website: www.ijitee.org An Accurate Identification of Packet Dropping Attacks Using Cat Swarm Optimization (Cso) to Ensure Better Intrusion Detection in Manet Environment

Mobile Ad hoc Network (MANET), which is comprised of a number of self-organized and battery equipped mobile nodes, is used widely in different applications, like private sectors and military. However, security is a major issue in MANET routing, as the network is prone to attacks. The main objective of intrusion detection system is for categorizing normal and suspicious activities in network. This paper introduce the intrusion detection scheme for establishing the secured path in MANET. For mobile ad hoc networks, swarm optimization approach based novel intrusion detection system is proposed in this paper. The proposed system is based on Cat swarm optimization (CSO) for detecting, one of vey possible attack, i.e. packet dropping attack in mobile ad hoc networks. Also Failure node discovery can be optimized by considering nodes historical information along with the neighbor node information. Before using the swarm optimization for findingsensor node’s trust values and for improving provenance data transmission security, an Extend the secure provenance scheme with Side Channel Monitoring – Information gaining ability (SCM) for detecting packet drop attacks staged by malicious data forwarding nodes is used. It assist in finding presence of selfish nodes as well as packet drop behaviours. With low false positive rate and high true positive rate, packet dropping attacks are detected effectively using proposed technique as shown in simulation results.

Social‐based reputation‐aware data forwarding for improved multicast delivery in the presence of selfish nodes in DTNs

SummaryDelay/disruption tolerant networks (DTNs) are potentially applicable in the challenged scenarios like post‐disaster environments. In such networks, data forwarding generally relies on the mutual cooperation of the nodes. However, in reality, despite the availability of necessary resources for data forwarding, a node could misbehave by dropping messages received from other nodes with whom it has no strong social ties. Such a node is called a socially selfish node, which would cause a poor delivery ratio in the network. In this paper, we aim to address the problem of multicast data forwarding in the presence of such selfish nodes, by means of efficient relay selection in DTNs. First, we define a realistic reputation model, in contrast to existing models, to define the socially selfish/misbehaving nodes in the network. Further, a game‐theoretic analysis is carried out that implies data forwarding cost is also an influential parameter in handling selfishness/misbehavior. Subsequently, the problem is formulated as a constrained optimization problem, which is NP hard. Therefore, a heuristic is proposed by combining the reputation of a node and the cost of message forwarding to appropriately identify relay nodes, thus improve the performance of the multicast message delivery in the network. We utilize a social metric, centrality to minimize the message forwarding cost in terms of the number of relay nodes. Finally, the comparative performance evaluation in ONE simulator with practical scenarios shows the superiority of the proposed scheme over the other prominent schemes.

An Artificial Immune System-Based Strategy to Enhance Reputation in MANETs

In Mobile Ad hoc Networks (MANETs) the nodes act as a host as well as a router, thereby forming a self-organizing network that does not rely upon fixed infrastructure, other than gateways to other networks. Security is important for MANETs and trust computation is used to improve collaboration between nodes. This paper proposes an Artificial Immune System-based reputation (AISREP) algorithm to compute trust and thereby provide a resilient reputation mechanism. In this paper, the presence of selfish nodes are considered. Selfish nodes are known to enhance the reputation of their selfish peers which in turn causes packet loss. In the event of the packet being routed using the AISREP algorithm, even though the number of selfish nodes increases, this algorithm identifies the selfish nodes and avoids using the selfish nodes from the routing path thereby improving the overall performance of the network.

A novel dynamic reputation-based source routing protocol for mobile ad hoc networks

Routing in mobile ad hoc networks is based on the cooperation of the network’s nodes. The presence of selfish nodes that do not cooperate in this task drastically reduces the number of delivered packets. In order to find the better paths that include nodes willing to cooperate, we propose a new routing algorithm based on the reputation of the nodes. In our proposal, each node locally assigns a reputation value to the rest of the nodes in the network and next it uses the assigned reputation values to find out the better routing paths, in order to minimize the overall packet loss ratio. We assume that nodes have a stationary routing behavior, but we also include a mechanism to detect changes in their behavior. Our approach has been evaluated in the presence of selfish nodes, in order to compare it with the dynamic source routing algorithm, obtaining a reduction in the packet loss ratio at the expenses of a small increase in the number of hops taken by the packets to reach their destinations.

Algebraic connectivity aided energy-efficient topology control in selfish ad hoc networks

Topology control is a technique to assign per-node's transmit parameters so as to get the network topology with the best possible network performance given some optimization criteria, such as energy-efficient connectivity. In this paper, we investigate energy-efficient topology control for wireless ad-hoc networks in the presence of selfish nodes. A non-cooperative game aided topology control approach is developed for minimizing the potential transmit power, whilst maintaining the network connectivity. The utility function is conceived by virtue of algebraic connectivity, which is a fine metric to measure the connectivity redundancy of a network. We prove the existence of Nash Equilibrium (NE) and demonstrate that the NE is Pareto optimal as well. Specifically, two fully distributed topology controls--algebraic connectivity-based Max-Improvement (ACMI) algorithm and $$\delta$$ź-Improvement (ACDI) algorithm--are proposed to find the NE topologies. Both ACMI and ACDI can easily construct the stable topologies with a low information-overhead of the order O(n), where n is the number of nodes. Simulations demonstrate that our algorithms observably eliminate the redundancy of the maximum power topology and embrace several other attractive topological features.

An Erlang factor-based conditional reliability mechanism for enforcing co-operation in MANETs

Reputation is considered to be one of the vital entities for maintaining collaboration among wireless mobile nodes present in an ad hoc environment. The nodes in MANET are dynamic and could change its behaviour drastically, but establishing maximum level of cooperation between these nodes is highly crucial. Moreover, the presence of selfish nodes has a greater impact on the resilience of the network. Hence, a need arises for formulating a mechanism that deals with these selfish nodes. In this paper, we contribute an Erlang distribution based Conditional Reliability Mechanism (ECRCM) that aids in detecting and isolating the selfish nodes present in an ad hoc environment. This mathematical model makes the routing decision with the help of a parameter called Erlang factor based Conditional Reliability Coefficient (ECRC) determined for each and every mobile node present in the ad hoc network. Extensive simulations were carried out through ns-2 simulator and the analysis was based on performance metrics such as packet delivery ratio, throughput, control overhead and total overhead. ECRCM also helps in framing an optimal threshold range for selfish node detection. From the results, it is obvious that the threshold range derived in our study remarkably identifies maximum number of selfish nodes when compared to the selfishness detecting parameters available in the literature.

Opportunistic Routing in Presence of Selfish Nodes for MANET

Opportunistic Routing protocols use broadcast nature of wireless communication to improve packet delivery from source to destination in mobile ad hoc network (MANET). In traditional routing protocols for MANET, each node uses the best neighbor for forwarding packet to destination. In opportunistic routing, a node selects and prioritizes multiple nodes which can act as potential packet forwarders. Similar to traditional routing protocols, opportunistic routing assumes that all nodes participating in the network are honest and cooperative. However, this is practically difficult in an open MANET. Few nodes participating in the network may behave selfishly; these nodes drop packets and do not offer service to other nodes. Such behavior exhibited by the nodes may cause a collapse of MANET communication. The selfish behavior attack is addressed by researchers for many existing MANET routing protocols. There are just a few works, which address selfish nodes attack for opportunistic routing protocols. The paper proposes an opportunistic routing protocol which can overcome the presence of selfish nodes. The proposed protocol discovers reliable candidate nodes for packet forwarding using a new metric called `path goodness'. The path goodness metric takes into account trustworthiness of the nodes on a path to the destination. The protocol decides trustworthiness of the nodes using packet forwarding behavior of the nodes. The work is a trust based extension of CORMAN opportunistic routing protocol. Simulation results show that, the proposed opportunistic routing protocol improves the packet delivery ratio by approximately 10 % in the presence of selfish nodes.

A Job Market Signaling Scheme for Incentive and Trust Management in Vehicular Ad Hoc Networks

In collaborative wireless networks with low infrastructure, the presence of misbehaving nodes can have a negative impact on network performance. In particular, we are interested in dealing with this nasty presence in road safety applications, based on vehicular ad hoc networks (VANETs). In this paper, we consider as harmful the presence of malicious nodes, which spread false and forged data, and selfish nodes, which cooperate only for their own benefit. To deal with this, we propose a distributed trust model $(DTM^{2})$ , which is adapted from the job market signaling model. $DTM^{2} $ is based on allocating credits to nodes and securely managing these credits. To motivate selfish nodes to cooperate more, our solution establishes the cost of reception to access data, forcing them to earn credits. Moreover, to detect and exclude malicious nodes, $DTM^{2} $ requires the cost of sending, using signaling values inspired from economics and based on the node's behavior so that the more malicious a node is, the higher its sending cost, thus limiting their participation in the network. Similarly, rewards are given to nodes whose sent messages are considered truthful and that paid a sending cost considered correct. The latter is a guarantee for the receivers about the truthfulness of the message since, in the case of message refusal, the source node is not rewarded, despite its payment. We validated $DTM^{2} $ via a theoretical study using Markov chains and with a set of simulations in both urban and highway scenarios. Both theoretical and simulation results show that $DTM^{2} $ excludes from the network 100% of malicious nodes without causing any false-positive detection. Moreover, our solution guarantees a good ratio of reception, even in the presence of selfish nodes.

Integrated social network reputation inspired routing for effective data forwarding

Wireless sensor networks face many threats which drain the energy. The performance of sensor network routing is much affected in the presence of selfish nodes with messages being delivered with a longer delay. Social network routing is a method in which the messages are selectively forwarded through the nodes where the encounters between these nodes are more likely to occur. Network reputations clearly speak about the quality of nodes involved in data forwarding. The idea is to utilise social network reputations of source or destinations for effective data forwarding in farmland sensor networks.

Congestion Controlled d-Adapt-OR for Adhoc Networks

Opportunistic routing scheme is used to route data packet from source to destination. Broadcasting nature of the wireless networks is utilized here to send data packets. A suitable forwarder node is selected from the neighboring node based on the rank ordering of the nodes. The nodes are ranked according to a score called Estimated Best Score (EBS). This score is calculated by considering the network congestion which is one of the major problems in adhoc networks. Probability of unsuccessful delivery of the packet become very less. Different types of packets are used to communicate between different nodes. A distributed and asynchronous routing scheme is introduced to route the packet. The proposed routing scheme doesn't require any initial knowledge about the network topology. Another problem with adhoc wireless networks is the presence of selfish nodes. For the successful delivery of the packet at the destination we have to avoid the presence of selfish nodes in the networks. So each node calculate the selfishness of its neighboring nodes. The data packet is forwarded by considering the selfishness of the node. I. Introduction Wireless adhoc networks are decentralized type of networks. A node in wireless adhoc networks communicate with the node which is in the range of the node. Wireless adhoc networks are considered in this work. Routing in adhoc networks is very important in order to communicate with the node which is not directly reachable. Different conventional routing scheme is now used to direct packet from source to destination. But most of them is not deal with the network congestion. They always result in unnecessary packet retransmission. Conventional routing scheme always find a fixed path along source to destination. So it always requires maintaining the knowledge about the network topology and statistics to find a path. Here a routing scheme called opportunistic routing is used. Opportunistic routing scheme doesn't require any previous knowledge about the networks and statistics. It dynamically route the packet from source to destination without any initial knowledge about the networks. This routing scheme exploits the broadcast nature and the opportunities available in the networks. It selects a node from its neighbors as next relay node based on some conditions. According to these conditions order the neighboring nodes and select one node as the relay node. And this process continues until it reaches the destination. The selection of next relay node may based on some geographical location or shortest path etc. Here proposed a routing framework called d-Adapt-OR that is distributed adaptive, asynchronous opportunistic routing scheme to route the packet. This routing scheme has low complexity and low overhead. While routing the routing scheme considered the congestion in the network and finds a path with less congestion. And it assumes no knowledge about network topology. One of the major problems in wireless adhoc networks is the presence of selfish nodes. A node is said to be selfish if it doesn't provides its own resources to forward others packet. But it takes the advantage of other node's resources and memory to forward its own packets. The nodes that drop the packet without forwarding it is a selfish node. A node may selfish even if it doing some other tasks at the packet arrival time. So the presence of selfish nodes reduces the packet success probability and deteriorates the performance of the network. So we have to avoid this type of nodes from the networks for improving the probability of successful delivery of the packet.

A Dempster–Shafer Based Tit-for-Tat Strategy to Regulate the Cooperation in VANET Using QoS-OLSR Protocol

In this paper, we address the problem of cooperation among vehicles in VANET using QoS-OLSR protocol in the presence of selfish nodes. QoS-OLSR is a proactive protocol that considers the Quality of Service (QoS) of the nodes while electing the cluster-heads and selecting the Multi-Point Relay (MPRs) nodes. Cluster-heads and MPRs might misbehave on the roads by over-speeding or under-speeding. Classical and generous Tit-for-Tats are proposed to analyze the interaction among vehicles. However, both strategies are not able to enforce the cooperation due the fact that they (1) count on individual watchdogs monitoring, (2) rely on the node-to-node cooperation decision, (3) and ignore the high mobility and packet collisions. Therefore, we propose a Dempster---Shafer based Tit-for-Tat strategy that is able to improve the decision and regulate the cooperation in the vehicular network. This is done by (1) launching a cooperative watchdogs monitoring, (2) correlating the observations of the different watchdogs using Dempster---Shafer theory, and (3) propagating the decisions among clusters. Thereafter, we compare the Dempster---Shafer based strategy with several strategies derived from the original Tit-for-Tat. Simulation results prove that the Dempster---Shafer based strategy is able to maintain the survivability of the vehicular network in the presence of high mobility and packet collisions with minimal time and overhead.

Reputation-Based Cooperative Detection Model of Selfish Nodes in Cluster-Based QoS-OLSR Protocol

The QOLSR is a multimedia protocol that was designed on top of the optimized link state routing (OLSR) protocol for mobile ad hoc network. It considers the quality of service (QoS) of the nodes during the selection of the multi-point relay (MPRs) nodes. One of the drawbacks of this protocol is the presence of selfish nodes that degrade the network lifetime. The limited energy and resources, and the absence of any motivation mechanism cause mobile nodes to behave selfishly during the MPRs selection. A new MPR selection based on cluster head election was proposed in previous work to increase network lifetime. In this paper, we consider the selfishness during the election and selection process by proposing the use of reputation system that will motivate nodes to participate during the selection of MPRs, where the reputation is calculated based on VCG mechanism design. After solving the selfishness during network formation, we have discovered that nodes can misbehave after being selected/elected. Such a passive malicious behavior could lead to a denial of service attack due to the drop of packets. As a solution, we propose a hierarchal cooperative watchdog detection model for the cluster-based QOLSR, where nodes cooperate in a hierarchical manner to detect selfish nodes. Moreover, to motivate watchdogs to monitor and cooperate with each other, incentives are given and calculated using cooperative game theory, where Shapley value is used to compute the contribution of each watchdog on the final decision. Simulation results show that the novel cluster-based QoS-OLSR model can give incentive to nodes to behave normally without sacrificing the quality of service of the network. In addition, the hierarchical cooperative detection model shows a more reliable and efficient detection of selfish nodes.

Impact of node distance on selfish replica allocation in a mobile ad-hoc network

Many data replication techniques have been proposed to minimize performance degradation caused by network partitioning in a mobile ad-hoc network. Most of them assume that all mobile nodes collaborate fully in terms of sharing their memory space. However, in reality, some nodes may selfishly decide to only cooperate partially, or not at all, with other nodes. Recently, a new approach to selfish replica allocation has been proposed to handle node selfishness. However, there is still much room for improvement. We empirically observe that the previous selfish replica allocation strategy suffers from long query delay and poor data accessibility, because it utilizes only non-selfish nodes that may be faraway nodes. In this paper, we propose a novel replica allocation strategy in the presence of selfish nodes, that takes into account both selfish behavior and node distance. Moreover, through a novel node leveling technique, we utilize the memory space of all connected nodes, including selfish nodes. The conducted simulations demonstrate that the proposed strategy outperforms existing replica allocation techniques in terms of data accessibility, query delay, and communication cost.

Improving QoS and security in wireless ad hoc networks by mitigating the impact of selfish behaviors: a game‐theoretic approach

ABSTRACTSelfish users are known to be a severe security threat for wireless ad hoc networks. In particular, they can exploit mechanisms designed to assure quality of service (QoS) in the network. In this paper, the problem of backoff misbehavior in IEEE 802.11 enhanced distributed channel access (EDCA) networks is studied using a game‐theoretic approach. First, it is shown how this selfish behavior can disrupt traffic differentiation. Then, a solution is proposed, which encourages standard‐compliant behavior and thus proper QoS provisioning. This solution is based on punishing selfish nodes by degrading their throughput proportionally to the degree of misbehavior. A practical application of the solution is proposed, which is verified through simulations. Results show that the suggested mechanism considerably improves QoS provisioning in IEEE 802.11 EDCA ad hoc networks in the presence of selfish nodes. Furthermore, it is shown that the mechanism is adaptive, does not have a negative impact on the throughput of well‐behaving nodes, and provides legacy node support. Copyright © 2012 John Wiley & Sons, Ltd.

Virtual Game-Based Energy Balanced Topology Control Algorithm for Wireless Sensor Networks

In topology control (TC), game theory is an efficient approach to analyze the conflicting objectives of nodes to enable the topology with certain global properties in the presence of selfish nodes. But in many existing game-based TC algorithms, every node has to make others aware of its changes by transmitting the control information repeatedly, which results in much unnecessary energy waste and network lifetime reduction. To solve the problem, the concept of virtual game is introduced, which virtualizes the game process to avoid the repeated information exchange in the game process. In addition, considering that unbalanced distribution of energy consumption also restricts the network lifetime, a distributed Virtual Game-based Energy Balanced TC algorithm (VGEB) with incomplete information is proposed, which is mathematically analyzed. The analysis results show that the TC virtual game is a potential game and the virtual game algorithm can converge to the state of Nash Equilibrium, which is Pareto Optimal. Moreover, VGEB can easily construct the topology with a low information complexity of O(n) and the induced topology can maintain the network connectivity, where n is the number of nodes in network. Simulation results demonstrate that VGEB can effectively balance the nodes' energy consumption, greatly reduce the energy waste in the game process and has many other attractive topological features.