Misbehaving Nodes Research Articles

Trust-based co-operative routing for secure communication in mobile ad hoc networks

The working of a Mobile Ad hoc NETwork (MANET) relies on the supportive cooperation among the network nodes. But due to its intrinsic features, a misbehaving node can easily lead to a routing disorder. This paper presents two trust-based routing schemes, namely Trust-based Self-Detection Routing (TSDR) and Trust-based Co-operative Routing (TCOR) designed with an Ad hoc On-demand Distance Vector (AODV) protocol. The proposed work covers a wide range of security challenges, including malicious node identification and prevention, accurate trust quantification, secure trust data sharing, and trusted route maintenance. This brings a prominent solution for mitigating misbehaving nodes and establishing efficient communication in MANET. It is empirically validated based on a performance comparison with the current Evolutionary Self-Cooperative Trust (ESCT) scheme, Generalized Trust Model (GTM), and the conventional AODV protocol. The extensive simulations are conducted against three different varying network scenarios. The results affirm the improved values of eight popular performance metrics overcoming the existing routing schemes. Among the two proposed works, TCOR is more suitable for highly scalable networks; TSDR suits, however, the MANET application better with its small size. This work thus makes a significant contribution to the research community, in contrast to many previous works focusing solely on specific security aspects, and results in a trade-off in the expected values of evaluation parameters and asserts their efficiency.

Modified Adhoc On-Demand Distance Vector for Trust Evaluation And Attack Detection

Recently, Wireless Sensor Network (WSN) becomes most potential technologies for providing improved services to several data gathering and tracking applications. Because of the wireless medium, multi-hop communication, absence of physical protectivity, and accumulated traffic, WSN is highly vulnerable to security concerns. Therefore, this study explores a specific type of DoS attack identified as a selective forwarding attack where the misbehaving node in the network drops packet on a selective basis. It is challenging to determine if packet loss is caused by a collision in the medium access path, poor channel quality, or a selective forwarding assault. Identifying misbehaving nodes at the earliest opportunity is an acceptable solution for performing secure routing in such networks. As a result, in this study effort, we present a unique Modified Ad Hoc On-Demand Distance Vector (AODV) Routing protocol depending upon the One time password (OTP) method that employs the RSA algorithm. Finally, a trust evaluation process determines which approach is the most optimal. According to the simulation findings of the suggested routing protocol and comparison with existing routing protocols provided in this article, the proposed work is both efficient and cost-effective.

Local Trust in Internet of Things Based on Contract Theory.

Autonomous trust mechanisms enable Internet of Things (IoT) devices to function cooperatively in a wide range of ecosystems, from vehicle-to-vehicle communications to mesh sensor networks. A common property desired in such networks is a mechanism to construct a secure, authenticated channel between any two participating nodes to share sensitive information, nominally a challenging proposition for a large, heterogeneous network where node participation is constantly in flux. This work explores a contract-theoretic framework that exploits the principles of network economics to crowd-source trust between two arbitrary nodes based on the efforts of their neighbors. Each node in the network possesses a trust score, which is updated based on useful effort contributed to the authentication step. The scheme functions autonomously on locally adjacent nodes and is proven to converge onto an optimal solution based on the available nodes and their trust scores. Core building blocks include the use of Stochastic Learning Automata to select the participating nodes based on network and social metrics, and the formulation of a Bayesian trust belief distribution from the past behavior of the selected nodes. An effort-reward model incentivizes selected nodes to accurately report their trust scores and contribute their effort to the authentication process. Detailed numerical results obtained via simulation highlight the proposed framework’s efficacy and performance. The performance achieved near-optimal results despite incomplete information regarding the IoT nodes’ trust scores and the presence of malicious or misbehaving nodes. Comparison metrics demonstrate that the proposed approach maximized the overall social welfare and achieved better performance compared to the state of the art in the domain.

Blockchain-based reporting protocols as a collective monitoring mechanism in DAOs

As a recent decentralized business model, Distributed Autonomous Organization (DAO) challenges the management paradigms of conventional organizations and represents the future of democracy-based systems. However, DAOs are facing challenges that can be divided into two categories, including policy-based and technical challenges. Detecting misbehaving nodes is a crucial challenge that is considered in both categories. Designing mechanisms to report malicious behaviors while maintaining anonymity is essential for the survival and efficiency of DAOs. In this paper, we clarify the problem, and introduce Blockchain-Based Anonymous Reporting (BBAR) as a collective monitoring mechanism in DAOs with its requirements and implementation methods.

Multiagent Networks with a Misbehaving Node: Control without the Knowledge of Global Network Objective*

In this paper, we study multiagent networks that involve nodes exchanging local information through a fixed, connected, and undirected graph. In the presence of a leader node knowing the global network objective (i.e., the synchronization command) and a misbehaving node being subject to a disturbance, we focus on control synthesis to suppress the effect of misbehaving node in the multiagent network. Specifically, the proposed control architecture is applied to a control node based on the sensing information (i.e., state) received from itself as well as from another auxiliary sensing node, where neither the control node nor the auxiliary sensing node have to be the leader node. In contrast to the similar studies in the literature, the key contribution of our control architecture is that it does not rely on the knowledge of global network objective being only available to the leader node. Stability and convergence properties of the closed-loop multiagent network are also analyzed, where we reveal how the control node and the auxiliary sensing node need to be selected for suppressing the effect of misbehaving node in a certain portion of the multiagent network such that the nodes in this portion perform the given global objective (i.e., approach to the synchronization command of the leader node). Finally, we demonstrate the efficacy of the proposed control architecture in a numerical example.

Control of Homogeneous Linear Multiagent Networks in the Presence of a Misbehaving Node*

This paper focuses on a multiagent network with homogeneous linear time-invariant node dynamics, where nodes exchange their local state information with each other. Specifically, we consider the case when there exists a misbehaving node in this multiagent network that is subject to a disturbance. To suppress the undesired effects of this misbehaving node in the overall multiagent network, we propose a control architecture to be executed by the driver node. A detailed closed-loop system analysis is presented that reveals how the driver node needs to be selected to allow the states of nodes belonging to a portion of the multiagent network (or all nodes) approach a desired synchronization state generated by an exosystem. The efficacy of the proposed control architecture is also demonstrated through illustrative numerical examples.

A New Cooperation Model for Dynamic Networks

Technological evolution has revealed new types of dynamic networks with decentralized architectures and autonomous services. Research on this impressive area has provided great objectives and benefits. However, providing some services related to security and routing protocols are major problems in this domain. All nodes in the networks need to cooperate and relay packets for other nodes, but some misbehaving nodes due to selfish reasons may significantly reduce the network performances. In this paper, a novel technique of enforcement cooperation is proposed. It aims to control the role of each node in the network and evaluate their participation during the routing function. The model includes important features that force node cooperation and discard the selfish ones. Simulation results showed that the proposed model is efficient in detecting and removing misbehaving nodes and enhancing cooperation between nodes while routing data.

A Secure Protocol against Selfish and Pollution Attacker Misbehavior in Clustered WSNs

Wireless sensor networks (WSNs) have been widely used for applications in numerous fields. One of the main challenges is the limited energy resources when designing secure routing in such networks. Hierarchical organization of nodes in the network can make efficient use of their resources. In this case, a subset of nodes, the cluster heads (CHs), is entrusted with transmitting messages from cluster nodes to the base station (BS). However, the existence of selfish or pollution attacker nodes in the network causes data transmission failure and damages the network availability and integrity. Mainly, when critical nodes like CH nodes misbehave by refusing to forward data to the BS, by modifying data in transit or by injecting polluted data, the whole network becomes defective. This paper presents a secure protocol against selfish and pollution attacker misbehavior in clustered WSNs, known as (SSP). It aims to thwart both selfish and pollution attacker misbehaviors, the former being a form of a Denial of Service (DoS) attack. In addition, it maintains a level of confidentiality against eavesdroppers. Based on a random linear network coding (NC) technique, the protocol uses pre-loaded matrices within sensor nodes to conceive a larger number of new packets from a set of initial data packets, thus creating data redundancy. Then, it transmits them through separate paths to the BS. Furthermore, it detects misbehaving nodes among CHs and executes a punishment mechanism using a control counter. The security analysis and simulation results demonstrate that the proposed solution is not only capable of preventing and detecting DoS attacks as well as pollution attacks, but can also maintain scalable and stable routing for large networks. The protocol means 100% of messages are successfully recovered and received at the BS when the percentage of lost packets is around 20%. Moreover, when the number of misbehaving nodes executing pollution attacks reaches a certain threshold, SSP scores a reception rate of correctly reconstructed messages equal to 100%. If the SSP protocol is not applied, the rate of reception of correctly reconstructed messages is reduced by 90% at the same case.

A Trust-Based Security Model to Detect Misbehaving Nodes in Internet of Things (IoT) Environment using Logistic Regression

Ensuring authentication in the Internet of Things (IoT) environment is a crucial task because of its unique characteristics which include sensing, intelligence, large scale, selfconfiguring, connectivity, heterogeneity, open and dynamic environment. Besides, every object in the IoT environment should trust other devices with no recommendation or prior knowledge for any network operations. Hence, those characteristics and blindness in communication make security violations in the form of various attacks. Therefore, a trustbased solution is necessary for ensuring security in the IoT environment. Trust is considered as a computational measure represented through a relationship between trustor and trustee, explained in a particular context valued through trust metrics and evaluated by a trust mechanism. The proposed logistic regression-based trust model provides an efficient way to identify and isolate the misbehaving nodes in the RPL (Routing Protocol for Low Power Lossy Networks) based IoT network. It is one of the popularly used routing protocols in IoT, that builds a path especially for the constrained nodes in IoT environments. However, it is vulnerable to many attacks. The proposed model classifies and predicts the node’s behavior (trusted or malicious). This model uses the logistic regression model to predict the node’s behavior based on the integrated trust value which is computed from the direct trust, reputation score, and experience trust. It is primarily designed to address the black hole attack in the IoT environment. The mathematical analysis shows the possibility of the proposed work and the simulation results show the proposed model is better than the existing similar work.

Adaptive DSR to mitigate packet dropping attacks in WMNs using cross layer metrics

Wireless Mesh network (WMN) is a form of Wireless Ad hoc network, where mesh topology is used to connect the radio nodes together and it is prone to vulnerabilities due to its open architecture. Packet loss is the major issue due to its open wireless physical media, frequent topological changes, scalability and power constraints. The most common blackhole and grayhole attacks besieged on network layer degrade the performance of WMN by dropping packets during transmission. In general, packet drops in WMN during transmission may happen due to mobility or buffer overflow or power depletion or malicious behavior of the intermediate nodes. This paper proposes an Adaptive Dynamic Source Routing protocol (ADSR) to detect the actual cause for packet drops, identify and isolate the misbehaving nodes using the cross layer metrics. It employs proactive, reactive mode of detection of packet dropping nodes and the packets are rerouted through alternate paths using packet salvaging technique. Bait-RREQ with virtual IP address is used to detect the blackhole nodes proactively and node behavior analysis is used to detect the packet dropping nodes reactively. The performance of ADSR is analyzed using a mathematical model by considering the characteristics of a node’s behavior. Using extensive simulations the performances are thoroughly analyzed, evaluated and compared with traditional DSR, WatchDog (WD), Bait-DSR (BDSR) protocols. Simulation results show that ADSR is better than other mentioned protocols with negligible increase in network overhead (less than 2%) which is due to the use of Bait-RREQ and packet salvaging technique. The proper identification of actual cause for packet drops significantly reduces the false positive rate of detection of malicious nodes with an increased packet delivery ratio (not lower than 95%) and throughput.

Novel Multiparameter Detection and Recovery Technique for Diverse Network Systems

Recent research works have engendered the existence of temporary misbehaving sensor nodes in both conventional wireless sensor and modern multilayered Internet of Things (IoT) networks. This article addresses the coexistence of misbehaving things (sensors) along with properly working ones, which altogether form a diverse network. We model the performance of a diverse network using stochastic modeling and introduce a multiparameter detection technique (MDT) to detect the existence of temporary misbehaving nodes in the network. MDT offers two separate algorithms for periodic and aperiodic response networks. We also propose a simple healing mechanism to alleviate the temporary disconnections of the misbehaving nodes from the network. With a simple recovery mechanism, MDT can provide 18% extra throughput benefiting 20% less energy consumption compared to a diverse network. The proposed scheme not only alleviates the effects of network diversity, but also outperforms the other solutions like self-detection and healing.

Detection and Prevention of Blackhole Attack in the AOMDV Routing Protocol

Mobile ad-hoc network is a collection of dynamically organized nodes where each node acts as a host and router. Mobile ad-hoc networks are characterized by the lack of preexisting infrastructures or centralized administration. So, they are vulnerable to several types of attacks, especially the Blackhole attack. This attack is one of the most serious attacks in this kind of mobile networks. In this type of attack, the malicious node sends a false answer indicating that it has the shortest path to the destination node by increasing the sequence number and decreasing the number of hops. This will have a significant negative impact on source nodes which send their data packets through the malicious node to the destination. This malicious node drop received data packets and absorbs all network traffic. In order overcome this problem, securing routing protocols become a very important requirement in mobile ad-hoc networks. Multipath routing protocols are among the protocols affected by the Blackhole attack. In this paper, we propose an effective and efficient technique that avoids misbehavior of Blackhole nodes and facilitates the discovery for the most reliable paths for the secure transmission of data packets between communicating nodes in the well-known Ad hoc On-demand multi-path routing protocol (AOMDV). We implement and simulate our proposed technique using the ns 2.35 simulator. We also compared on how the three routing protocols AOMDV, AOMDV under Blackhole attack (BHAOMDV), and the proposed solution to counter the Blackhole attack (IDSAOMDV) performs. The results show the degradation on how AOMDV under attack performs, it also presents similarities between normal AOMDV and the proposed solution by isolating misbehaving node which has resulted in increase the performance metrics to the standard values of the AOMDV protocol.

Enhanced Reliable ACK (ERACK) Scheme for Detecting Misbehaving Nodes in MANETs

In Mobile Ad Hoc Networks (MANETs), the process of sending end-to-end acknowledgement (ACK) for each packet by the destination, causes unnecessary overhead. This paper proposes an Enhanced Reliable ACK (ERACK) scheme for detecting misbehaving attacks in MANET. Initially, reliable multiple paths are established by measuring the path reliability. For defending the data transferred from the dispatcher, one-way hash chain based Message Authentication Code (MAC) is utilised. If the packet loss count is above a threshold, then Secure ACK (S-ACK) mode is activated which identifies the misbehaving node. The source then generates a Misbehavior Report Authentication (MRA) message which is transmitted to the destination using the path with next higher reliability. By experimental results it is shown that the ERACK method decreases the packet loss and delay while ensuring the successful delivery of MRA to the destination.

TBCS: A Trust Based Clustering Scheme for Secure Communication in Flying Ad-Hoc Networks

In Flying Ad hoc Networks (FANETs), coordination and cooperation among nodes are important for efficient data transmission. Cooperation among the nodes hinges on the node behavior and the behavior of the node can be quantified using the concept of trust. Trust helps in segregation of non-cooperative and malicious network nodes, thus increasing the reliability of information exchanged among nodes. In this paper, a Trust Based Clustering Scheme (TBCS) has been proposed for FANETs. TBCS use a multi-criteria fuzzy method for the classification based on the node’s behavior in the fuzzy and complex environment. The proposed scheme makes use of Takagi–Sugeno–Kang fuzzy inference method. The reward and punishment mechanism has been introduced to convert the node’s behavior into trust, and to segregate malicious and misbehaving nodes in the FANET. Furthermore, a secure Cluster Head has been selected based on calculated trust values that is responsible for communication with ground control station and inter-cluster communication. TBCS is compared with existing trust models and the experiment results revealed that the proposed TBCS model has high accuracy, better performance, and adaptability in FANETs.

SGF-MD: Behavior Rule Specification-Based Distributed Misbehavior Detection of Embedded IoT Devices in a Closed-Loop Smart Greenhouse Farming System

Smart farming is rapidly revolutionizing the agricultural sector where embedded Internet of Things (IoT) devices are integrated into the field to maintain or improve the quality of products as well as increase food production. Despite the tremendous benefits, various cybersecurity threats of IoT can also be inherited by the sector. In this paper, we propose a lightweight specification-based distributed detection to identify the misbehavior of heterogeneous embedded IoT nodes efficiently and effectively in a closed-loop smart greenhouse farming system. To expand the monitoring space of a node, we exploited the Kalman-filter algorithm and simple statistical operations to obtain estimates of data. Accordingly, this enables a monitoring node to assess a target node that has distinct physical characteristics and access to natural phenomena. Along with this, we derive the behavior-rules that are specific to the target system and carefully translate these rules into a state machine diagram. Besides, we formally verify the functional correctness of the monitoring processes as well as ensure that the behavior specifications are completely covered by using the model checker tool UPPAAL. Through extensive experimental simulation using Proteus, we verify its applicability to resource-constrained embedded devices, e.g., Arduino-Uno, as well as show high accuracy in detecting misbehaving nodes while having low false alarms.

Data dependability based bimodal encryption scheme for distributed routing in wireless sensor networks

The development of smart cities and their fast-paced deployment leads to the creation of massive amount of data at exceptional rates. Due to the data gathering and tracking nature of wireless sensor networks (WSN), it finds applications in various domains. Presently, security is considered as an important design issue of developing multipath routing protocols in WSN. The existing routing techniques either concentrate on energy efficiency or security issues with maximum resource utilization. This paper focuses on the idea of incorporating encryption algorithms on multihop routing mechanism in WSN. Here, routing takes place by the Augmented Tree Based Routing (ATR) which is a tree-based multipath routing method. To attain higher level of security, two encryption algorithms namely lightweight encryption algorithm (LEA) and two phase hybrid cryptography algorithm (THCA) are employed based on the data dependability. The encryption algorithms are utilized based on data dependability where general data is encrypted by LEA and other confidential data are encrypted by THCA. i.e. the LEA is used to send proactive data and the important reactive data is encrypted by THCA. For routing purposes, Augmented Tree Based Routing (ATR) is used. From experimentation, it is evident that the presented method exhibits enhanced performance by means of throughput, control overhead and network lifetime even though there exist some misbehaving nodes in the network.

A Collaborative Intrusion Detection System for Cognitive Radio Networks with Trust and Reputation Management

Systems administration cognitive radios and hubs from primary system (PS) results in a heterogeneous existing together multi radio remote system, with the goal that critical system throughput addition can be accomplished. Be that as it may, by exploring cognitive radio networks (CRN) engineering, the connections in CRNs are probably not going to help total security check because of connection elements, crafty accessibility, and uni-directional in accessible time window, so trust and reputation system is required. CORE is a reputation based security mechanism which enforces cooperation of nodes in CRN. CONFIDANT is based on selective unselfish and belief in mobile nodes and it aims to detect and isolate misbehaving nodes. Both CORE and CONFIDANT mechanism give the trustworthiness of all mobile nodes in the network and it punishes misbehaving nodes once it detected. This paper gives the comparative study of trust based neighbor monitoring CORE and CONFIDANT on secured routing protocols. The simulation results shows that our work provides better detection efficiency, better detection coverage and packet delivery ratio in routing protocols with neighbor monitoring scheme.

Performance Analysis of Enhanced Ad-Hoc on-Demand Distance Vector Routing Protocol in Smart Environment

MANETs have specific features that can satisfy the mobility and heterogeneous requirement of the smart environment. Smart applications need high Mobility, Bandwidth, Reliability and less Packet Loss and Delays; therefore, it is important to provide good Quality of Service (QoS) in such applications. So there is a dire need of identifying and exploring the relevant protocols that may be adapted for IoT enabled the smart environment. The routing protocols in smart environments are accountable for connectivity among nodes, fairness, quality of service, etc. Protocol & path selection is the main strategies to design any mobile network. The chosen protocol must have the best in term of data integrity and data delivery. Hence the analysis of the protocols become an essential step. This paper presents various securities and safety-related issues of MANET-IoT system, and also advocate the requirement of enhancing routing protocols in a smart environment. In this research, a new enhanced cache update technique is introduced in MANET protocol to make it enable for the upcoming smart environment. The enhanced algorithm helps to detect the malicious node and remove the stale route present in the network, no matter which traffic mode is used and in which direction nodes are moving. Cache is upgraded in such manner that all nodes in the way are notified about the misbehaving node and its adjacent neighbors’ nodes will not use misbehaving node while searching for the route. Here the analysis has been done taking a various number of nodes. Packet Delivery and Packet Lost are two key parameters taken for analysis purpose.

A survey of black-hole attack mitigation techniques in MANET: merits, drawbacks, and suitability

Mobile Ad-hoc Network (MANET) is a prominent technology in the wireless network in which the mobile nodes operate in a distributed manner and collaborate with each other in order to provide the multi-hop communication between the source and the destination node. Generally, the main assumption considered in the MANET is that each node is a trusted node. However, in a real scenario, there are some unreliable nodes which misbehave and launch the attack in network like black-hole in which the misbehaving nodes attract all the traffic towards itself by giving false information of having a shortest path towards the destination with a very high destination sequence number. In this paper, we discussed different possible nature of the nodes in the network that can lead to the different possible attacks. We have also presented the different classification of the techniques and discussed the merits, drawbacks, and suitability of the various techniques in different scenarios which need to be taken into consideration while designing an efficient protocol.

Intentional and unintentional misbehaving node detection and prevention in mobile ad hoc network

Adaptation and self-forming are the two main qualities of MANET that create various types of sensitive and critical applications, and a single incorrect message may directly or indirectly affect human life. Hence, data communication in this area should be secure. Routing protocol establishes Route selection in MANET based on the assumption that all the nodes present in a network are cooperative, but this assumption is not valid in a hostile environment. Misbehaving activities in network layer are caused by packet drop or refusal to forward the packets by intermediate nodes. However, packets may also be dropped by intermediate nodes due to constrained resources. In this paper, initially we study the routing misbehaviour activities in MANET. Further we propose the mechanism to determine and mitigate the malicious node accurately. Analytical and simulation results show that the proposed work mitigates misbehaving node with less overhead in comparison with existing work.