Node Trust Research Articles

Robust and Accurate Trust Establishment Scheme for Wireless Sensor Network

The success of the mission assigned to a Wireless Sensor Network (WSN) depends heavily on the cooperation between the nodes of this network. Indeed, given the vulnerability of wireless sensor networks to attack, some entities may engage in malicious behavior aimed at undermining the proper functioning of the network. As a result, the selection of reliable nodes for task execution becomes a necessity for the network. To improve the cooperation and security of wireless sensor networks, the use of Trust Management Systems (TMS) is increasingly recommended due to their low resource consumption. The various existing trust management systems differ in their methods of estimating trust value. The existing ones are very rigid and not very accurate. In this paper, we propose a robust and accurate method (RATES) to compute direct and indirect trust between the network nodes. In RATES model, to compute the direct trust, we improve the Bayesian formula by applying the chaining of trust values, a local reward, a local penalty and a flexible global penalty based on the variation of successful interactions, failures and misbehaviors frequency. RATES thus manages to obtain a direct trust value that is accurate and representative of the node behavior in the network. In addition, we introduce the establishment of a simple confidence interval to filter out biased recommendations sent by malicious nodes to disrupt the estimation of a node's indirect trust. Mathematical theoretical analysis and evaluation of the simulation results show the best performance of our approach for detecting on-off attacks, bad-mouthing attacks and persistent attacks compared to the other existing approaches.

Trust-based Routing Optimization using Learning Automata in Wireless Sensor Network

The use of wireless sensor networks is becoming more and more important due to the COVID-19 pandemic and the living conditions of human beings today. The three main goals in designing this type of network are to reduce energy consumption, choose the shortest route and choose a reliable route for data transmission. In this paper, these three goals are considered in routing. Due to the fact that this type of network is exposed to many attacks, identifying malicious nodes and removing them creates security in this type of network. This paper presents an energy-aware and trusted-based routing method using learning automata and an evaluation function. Learning automata identifies trusted nodes (to send data) and malicious nodes using the corresponding evaluation function. The evaluation function considers the residual energy, the node's trust and the number of hops to the sink parameters. Thus, the data reaches its destination in a safe and reliable way. The evaluation results of the proposed method show an improvement in the performance of this method compared to other relevant methods. .

Quantum web of trust

AbstractAuthentication is the foremost requirement for any online secure transaction. In post quantum era, public key encryption is considered no longer a safe option. The research is therefore, progressing toward providing a quantum resistant solution using both classical as well as quantum computing medium. The paper proposes a quantum based mutual authentication protocol for autonomous system, utilizing the properties of quantum mechanics for exchange, storage and validation of confidential data. The protocol so designed evolves into a chain of mutually trusted nodes to form quantum web of trust. The protocol cater for devices infected with malware by utilizing physically unclonable function inside trusted platform module. The mathematical expressions conveying the correctness of operations has been demonstrated on a quantum machine to verify the efficacy of the protocol. The security analysis demonstrates the ability of the proposed protocol to mitigate cyber attacks and eavesdropping in the network.

A Redeemable SVM-DS Fusion-Based Trust Management Mechanism for Underwater Acoustic Sensor Networks

Underwater acoustic sensor networks (UASNs) have gradually received attention due to their widespread applications, such as in disaster prevention, environmental monitoring and military activities, and they simultaneously face security challenges. In recent years, trust management mechanisms have become important tools for responding to internal attackers. However, most of the existing trust management mechanisms do not consider the adverse influence of complex underwater environment on node evaluation, and do not deal with the case that normal nodes are misjudged as malicious nodes. To achieve accurate trust evaluation of nodes and reduce the possibility of misjudgment of normal nodes, a redeemable Support Vector Machine-Dempster-Shafer (SVM-DS) fusion-based trust management mechanism (SDFTM) is proposed for UASNs in this paper. First, according to the characteristics of attacks, three kinds of trust evidence are selected: packet-based evidence, data-based evidence and energy-based evidence. Then the support vector machine (SVM) is applied to classify the trust of node from the aspect of each kind of trust evidence, while Dempster-Shafer (DS) evidence theory is used to fuse the different trust classification results of nodes. Second, to deal with cases where a normal node may be misclassified as a malicious node, trust redemption process is carried out based on the historical performance and environmental influence (unreliable acoustic channel, weak link connectivity). Finally, the trust value is calculated and updated. The simulation results prove that the proposed scheme yields satisfactory performance in malicious detection and reduce the possibility of misjudgment of normal nodes.

Trust Mechanism of Feedback Trust Weight in Multimedia Network

It is necessary to solve the inaccurate data arising from data reliability ignored by most data fusion algorithms drawing upon collaborative filtering and fuzzy network theory. Therefore, a model is constructed based on the collaborative filtering algorithm and fuzzy network theory to calculate the node trust value as the weight of weighted data fusion. First, a FTWDF (Feedback Trust Weighted for Data Fusion) is proposed. Second, EEFA (Efficiency unequal Fuzzy clustering Algorithm ) is introduced into FTWDF considering the defects of the clustering structure caused by ignoring the randomness of node energy consumption and cluster head selection in the practical application of the existing data fusion algorithm. Besides, the fuzzy logic is applied to cluster head selection and node clustering. Finally, an FTWDF-EEFA clustering algorithm is constructed for generating candidate cluster head nodes, which is verified by simulation experiments. The comparative analysis reveals that the accuracy of the FTWDF-EEFA clustering algorithm is 4.1% higher than that of the TMDF (Trust Multiple attributes Decision-making-based data Fusion) algorithm, and 8.3% higher than that of LDTS ( Larger Data fusion based on node Trust evaluation in wireless Sensor networks) algorithm. It performs better in accuracy and recommendation results during the processing of ML100M dataset and NF5M dataset. Besides, the new clustering algorithm increases the survival time of nodes when analyzing the number of death nodes to prolong networks’ lifespan. It improves the survival period of nodes, balances the network load, and prolongs networks’ lifespan. Furthermore, the FTWDF-EEFA clustering algorithm can balance nodes’ energy consumption and effectively save nodes’ overall energy through analysis. Therefore, the optimized algorithm can increase the lifespan of network and improve the trust mechanism effectively. The performance of the algorithm has reached the expected effect, providing a reference for the practical application of the trust mechanism in networks.

A context-aware information-based clone node attack detection scheme in Internet of Things

The rapidly expanding nature of the Internet of Things (IoT) networks is beginning to attract interest across a range of applications, including smart homes, smart transportation, smart health, and industrial contexts such as smart robotics. This cutting-edge technology enables individuals to track and control their integrated environment in real-time and remotely via a thousands of IoT devices comprised of sensors and actuators that actively participate in sensing, processing, storing and sharing information. Nonetheless, IoT devices are frequently deployed in hostile environments, wherein adversaries attempt to capture them in order to seize control of the entire network. One such example of potentially malicious behaviour is the cloning of IoT devices, in which an attacker can physically capture the devices, obtain some sensitive information, duplicate the devices, and intelligently deploy them in desired locations to conduct various insider attacks. A device cloning attack on IoT networks is a significant security concern since it allows for selective forwarding, sink-hole, black-hole, and warm-hole attacks. To address this issue, this paper provides an efficient scheme for detecting clone node attack on mobile IoT networks that uses semantic information of IoT devices known as context information to locate them securely. We design the location proof mechanism by combining location proofs and batch verification of the extended elliptic curve digital signature technique (ECDSA*) to accelerate the verification process at selected trusted nodes. Furthermore, we present a model for selecting trustworthy IoT devices based on their profile capabilities, enabling them to be chosen from the other IoT devices for the location proof-verification procedure. Compared with existing studies, the performance analysis and experimental results suggest that our proposed scheme provides a high degree of detection accuracy with minimal detection time and significantly reduces the computation, communication, energy and storage overheads.

False Data Injection Attack Detection and Improved WLS Power System State Estimation Based on Node Trust

False Data Injection Attack Detection and Improved WLS Power System State Estimation Based on Node Trust

Trusted Network Evaluation Model Based on Comprehensive Trust

Trusted network is currently evaluated based on the trustworthiness of the nodes in the network; thus, trust in the nodes is required to achieve trust in the network. The methods for calculating node trust mainly utilize the following three types of models: node behavior model, multiple-attribute decision-making model and reputation model. User behavior model always determines trust values based on harmful node behaviors. Multi-attribute decision-making model can be regarded as refinements of node behavior model. The trust values of the nodes are determined based on compromised trust attribute data and not just harmful behavior data. Reputation model calculates the trust values of nodes using subjective evaluation data for nodes. This paper presents a comprehensive trust model that combines subjective evaluation data and objective attribute data to calculate node trust. The experimental results show that malicious nodes can be effectively identified, which improves the service success rate of the system.

Trustee: A Trust Management System for Fog-Enabled Cyber Physical Systems

In this paper, we propose a lightweight trust management system (TMS) for fog-enabled cyber physical systems (Fog-CPS). Trust computation is based on multi-factor and multi-dimensional parameters, and formulated as a statistical regression problem which is solved by employing random forest regression model. Additionally, as the Fog-CPS systems could be deployed in open and unprotected environments, the CPS devices and fog nodes are vulnerable to numerous attacks namely, collusion, self-promotion, bad-mouthing, ballot-stuffing, and opportunistic service. The compromised entities can impact the accuracy of trust computation model by increasing/decreasing the trust of other nodes. These challenges are addressed by designing a generic trust credibility model which can countermeasure the compromise of both CPS devices and fog nodes. The credibility of each newly computed trust value is evaluated and subsequently adjusted by correlating it with a standard deviation threshold. The standard deviation is quantified by computing the trust in two configurations of hostile environments and subsequently comparing it with the trust value in a legitimate/normal environment. Our results demonstrate that credibility model successfully countermeasures the malicious behaviour of all Fog-CPS entities i.e., CPS devices and fog nodes. The multi-factor trust assessment and credibility evaluation enable accurate and precise trust computation and guarantee a dependable Fog-CPS system.

Energy based random repeat trust computation approach and Reliable Fuzzy and Heuristic Ant Colony mechanism for improving QoS in WSN

The furthermost important issues in WSN are to provide a multi-path and multi-constraint Qualify of Service (QoS) routing for uninterrupted communications between the nodes. On one hand, multi-constrained QoS routing deals with identifying paths that assure numerous autonomous QoS limitations, and on the other hand, multi-path refers to the identification of multiple paths. The EB-RRTC (Energy based random repeat trust computation) algorithm is employed for encountering trusted nodes with destination node. The proposed method also employs the Reliable Fuzzy and Heuristic Concurrent ACO (RF-HEACO) QoS Routing Protocol to improve QoS. The HEACO-RF QoS Routing Protocol includes two phases. In the first phase, the Ant Colony Optimization algorithm is modified to identify a deposit of candidate routes among a pair of source and destination. While identifying the candidate routes along with the QoS metrics, heuristic factors and Reliable Fitness Functions are considered. In the second phase, the reliability technique is used to measure each path, and the paths with high reliability is selected by the ant agents using Fuzzy logic based on the metrics link stability, residual energy, and packet loss rate. Simulation outcomes prove that RF-HEACO QoS routing protocol can decrease the energy consumption and improve the packet delivery ratio, and packet loss rate with the minimum delay when compared with the techniques. In other words, our method is well capable of offering improved QoS (Quality of Service).

GT-Bidding: Group Trust Model of P2P Network Based on Bidding

Due to the lack of trusted third parties as guarantees in peer-to-peer (P2P) networks, how to ensure trusted transactions between peers has become a research hotspot. However, the open and distributed characteristics of P2P networks have brought challenges to network security, and there are problems such as node fraud and unavailability of services in the network. To solve the problem of how to select trusted transaction peers in P2P groups, a new trust model, GT-Bidding, is proposed in this paper. This model follows the bidding process of human society. First, each service peer applies for a group of guarantee peers and carries out credit mortgages for this service. Second, based on the entropy and TOPSIS method (Technology for Order Preference by Similarity to an Ideal Solution) approaching the ideal solution, a set of ideal trading sequences is selected. Then, the transaction impact function is used to assign weights to the selected guarantee peers and service nodes, respectively; thus, the comprehensive trust of each service node can be calculated. Finally, the service peer is verified using feedback based on the specific confidence level, which encourages the reputation of the service and its guarantee peers to update. Experiments show that GT-Bidding improves the successful transaction rate and resists complex attacks.

A secure localization scheme based on trust assessment for WSNs using blockchain technology

Wireless Sensor Network (WSN) is one of the integral part of the present ubiquitous and pervasive computing. The smartness of the applications is incomplete without WSNs. Almost all the scenarios of WSNs require efficient and accurate localization process. However, the main disadvantage of the existing frameworks and algorithms is that they are not so much significant with the trust of the beacon nodes which are integral part of WSNs. This must be ensured for localization. In our present solution, we consider this issue.It is obvious to have the malicious nodes in the hostile environment of WSN operations. Our proposed solution, therefore, address this challenge and provides a trust-based framework for secure localization. It focus on the trust assessment algorithm and blockchain generation. In the localization process, trust values of each beacon node are computed based on different trust metrics and the corresponding weights are dynamically adjusted. Subsequently, for the mining process, higher trusty beacon nodes are only selected. This two-step approach ensures an updated blockchain with reliability and consistent trust values of all beacon nodes. We perform a set of simulations to validate the performance and effectiveness of the proposed algorithm. The results are comparatively analyzed based on localization accuracy, detection of malicious activities, False Positive Rate (FPR), and False Negative Rate (FNR). In all the aspects our solution outperforms the other algorithms.

An Enhanced Trust-Based Kalman Filter Route Optimization Technique for Wireless Sensor Networks

Wireless Sensor Networks are generally employed for observing and monitoring specific environments. WSNs are made from a huge amount of low-cost sensor nodes separated and distributed in different environments for distributing data through sensor nodes. The collection of data by the various sensors were transmitted into the Base Station. An enhanced Trust-Based Adaptive Acknowledgment based Intrusion-Detection System was proposed from positive distributions in WSNs. A Kalman filter algorithm is used in Multi-objective Particle Swarm Optimization to predict trust nodes over the WSN. Simulations were carried out for non-malicious (0% malicious) networks, and various ranges of malicious nodes in the network were investigated. The outcomes show that the proposed MPSO achieves an improvement of 3.3% than PSO at 0% malicious nodes concerning the PDR. Similarly, at 30% malicious, the PDR of MPSO achieves better by 3.5% than PSO in WSN.

Secure and Shortest Path Routing Bypassing Attackers in Wireless Sensor Networks

In wireless sensor networks (WSNs), energy constraint of node is the major issue, as the sensor may be deployed in the area where energy backup or quick replacements may not be available. In such cases, preserving the node energy and prolonging the network life time play crucial role in wireless sensor networks. Similarly, sensor nodes are highly vulnerable to attacks, attackers can easily tamper the sensor node and compromise it. Thus to overcome above stated two problems, the proposed work ensures shortest path routing, which ensures network life time of sensor nodes and the trust based routing, which avoids node compromise attacks. The proposed shortest path routing algorithms takes route through multi-hop nodes to corresponding sink. The shortest path based on the geographical routing strategy chooses the nodes nearest to the routing node and sink node. The novel routing framework proposed in this work considered shortest path with trust based routes. The node's energy is considered to taking reliable node on the routing path, which ensure the packet delivery and avoids any node failure due to less energy. The node's trust value is evaluated with three type, which ensure that the paths created are more reliable

Trust-Aware Fuzzy Evaluation Method for Preventive Route Generation in Mobile Network

The existence of a non-cooperative or black hole node as an intermediate node in a mobile network can degrade the performance of the network and affects the trust of neighbor nodes. In this paper, a trust-aware routing protocol is defined for improving the routing reliability against black hole attacks. A new Trust aware and fuzzy regulated AODV (TFAODV) protocol is investigated in this work as an improvement over the existing AODV protocol. The session-driven evaluation of stability, communication-delay, and failure-ratio parameters are conducted for evaluating the trust of nodes. The fuzzy rules apply to these parameters for computing the degree of trust. This trust vector isolates the attack-suspected and trustful nodes. The proposed TFAODV protocol used the trustful mobile nodes as the intermediate path nodes. The proposed protocol has been experimented with in the NS2 simulation environment. The analytical results are obtained in terms of PDR ratio, Packet Communication, Loss rate parameters. The comparative results are derived against the AODV, Probabilistic AODV, PDS-AODV, PSAODV, and Juneja et al. protocols. The analysis is performed on different scenarios varied in terms of network density, degree of stability, and the number of attackers. The simulation results ensured the proposed TFAODV protocol has improved the PDR ratio and reduced the communication loss significantly against these state-of-art protocols.

Secure disjoined multi-hop communication in wireless sensor network using trust nodes based data transmission technique

Secure disjoined multi-hop communication achieved in Wireless Sensor Network (WSN) has a prominent part to play and it can be accomplished with the help of Trust nodes based data transmission technique. In this proposed technique is communicating any kinds of information to make them secure and trust node verification for the sender and receiver within the WSN. Cluster Based Trust Management schemes are helpful in identifying unauthenticated user in WSN. First, it finds the trustworthy nodes in networks, and later transmits the packets via those trusted nodes. These trusted nodes are discovered in accordance with the trust values to find the neighborhood nodes during the authentication process for achieving improvement in the values of the metrics including Packet Delivery Ratio, End To End delay time, Remaining Energy, communication link and Throughput.

DATA TRAFFIC TRUST MODEL FOR CLUSTERED WIRELESS SENSOR NETWORK

Trust is an essential parameter among sensor nodes to provide secured and successful communication. Many trust management schemes have been proposed earlier for large scale Wireless Sensor Network (WSN) however not cooperates well in terms of low dependability, memory overheads, large communication etc, therefore a system called Data Traffic Trust Scheme (DTTS) for clustered WSN is proposed here. Here the trust nodes are identified through the data traffic sampling rate. The trust rate is identified through the number of sent and receive data packets and the malicious packets are diagnosed through the un-matching packet rate. The simulation results are evaluated to show the efficiency for the proposed scheme.

TRUST COMPUTATION USING BOTTOM-UP PARSER APPROACH IN MANET

In Mobile Ad hoc NETwork (MANET), the nodes are able to move from one point to other freely since it is a decentralized network. The objective of the proposed scheme is to remove the malicious nodes and to select the highly trusted nodes for transmitting the data. The node entering in to the network is checked for its identity either it is malicious or normal by applying bottom-up parser approach. The node is checked for their trust levels by using shift reduce operations which protects the sensed information from the malevolent node in the network. Therefore, the trusted source node sends the confidential data to the sink through the trusted nodes in the network. The simulation analysis is carried to prove the efficiency of the proposed scheme.

Wireless Sensor Missing Value Estimation Algorithm Based On Multi-Attribute

Because the wireless sensor is arranged in the environment of unmanned management and complex, in the process of collecting data and transmitting data, it often leads to data loss due to the influence of itself or external environment. The best way to reduce the impact of missing value is to estimate the missing value. In this paper, we propose a missing value estimation algorithm based on time attribute and trust mechanism. We use Arima to predict the time attribute, and use the relationship between current value, historical value and error to predict the future data. We use subjective logic to convert the interaction information between nodes into trust value, and then Linear Regression prediction value by selecting the number of trust nodes. Finally, according to the optimal fit degree, weight distribution is carried out to form the final prediction value. Because the algorithm not only considers the node data of the trusted neighbor, but also predicts the future data changes through the changes of its own historical data, it has higher accuracy and lower error when compared with other algorithms.

Fuzzy COmplex PRoportional ASsessment of alternatives‐based Node Cooperation Enforcing Trust Estimation Scheme for enhancing Quality of Service during reliable data dissemination in Mobile Ad hoc Networks

SummaryTrust is considered as the most significant factor that helps in enforcing cooperation among the autonomous nodes of Mobile Ad hoc Network (MANETs). The computation of trust is essential for assessing the level of cooperation rendered by each individual mobile toward the activity of data routing. The calculation of trust in a self‐configuring and infrastructure‐less network is a challenge due to the dynamic movement of mobile nodes. Moreover, the trust of intermediate nodes in the routing path needs to be estimated for preventing the deterioration of network performance. In this paper, a Fuzzy COPRAS‐based Node Cooperation Enforcing Trust Estimation (FCOPRAS‐NCETE) Scheme was proposed for maintaining superior Quality of Service (QoS) in the event of reliable data dissemination. This proposed FCOPRAS‐NCETE Scheme was proposed for comprehensive ranking of mobile nodes acting as intermediate nodes between the source and destination nodes. It incorporated the benefits of fuzzy set theory and COmplex PRoportional ASsessment of alternatives (COPRAS) to determine the trust of intermediate nodes for isolating them from the routing path in the uncertain routing process with the objective to maintain superior QoS in the network. The simulation experiments of the proposed FCOPRAS‐NCETE Scheme conducted using ns‐2 confirmed its predominance in improving the throughput, packet dissemination rate, packet loss rate, energy consumptions and total overhead with different number of mobile nodes, CBR traffic rate and pairs of source and destination nodes in the network.