Trust Value Of Node Research Articles

Malicious vehicle node detection mechanism based on repeated game and trust evaluation in VANET

In order to solve the problem of malicious vehicle nodes attack in VANET system and improve the security of VANET communication, the paper proposes a method of malicious vehicle nodes detection based on repeated games and trust evaluation. First of all, according to vehicle nodes communicating, a repeated game model is established to generate vehicle nodes revenue by punishing attack behavior nodes and rewarding normal behavior nodes. Secondly, a trust evaluation mechanism is introduced to convert vehicle nodes revenue into nodes trust value. Finally, the optimal dynamic threshold is calculated through multiple iterations, comparing and analyzing nodes trust value and dynamic threshold to screen out the malicious vehicle nodes. Simulation experiments show that this mechanism improves the detection rate of malicious nodes and reduces the error detection rate, effectively isolates malicious vehicle nodes according to the change of node trust value, and improves the security of VANET communication.

A Trust-Based Security System for Data Collection in Smart City

The authenticity and integrity of sensed data in the data collection stage is a very critical aspect for the smart city industrial environment. They impact the accuracy of data analysis and the objectivity of making decisions. However, how to identify attack behaviors from environmental interference and establish a secure route to transmit data for resource-constrained terminals are challenging problems. To address these problems, in this article, we propose a trust-based security system (TSS). In TSS, we first design a trust model using binomial distribution for calculating the node's trust value and a third-party recommendation scheme for improving the objectivity of trust value. Then, we propose a trust management scheme for preventing the <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on–off</small> attack. After that, we design a secure routing protocol, which is used to balance the security, transmission performance, and energy efficiency. Finally, the analytical results of the TSS are evaluated with extensive simulation experiment.

SDSR A New Hybrid Secure Routing Protocol using Trust Recommendations in MANET

A mobile ad hoc network is a dynamic network which can be established when there is no possibility or if it is practically impossible to establish a standard cellular infrastructure for communication. It is a form of decentralized wireless network where nodes are independent of each other and operate on their own. Every node is free to move in and out of the network as and when needed. This also introduces many concerns about security of data being forwarded through these nodes as there is no fixed dedicated mechanism to verify the authenticity of the nodes that join and leave the network at varied times. As MANET is a multi-hop network, data should be forwarded through many intermediate nodes, before it actually arrives at the intended destination. So data on transit through these intermediate nodes should be protected from any malicious nodes. Different protocols were proposed in literature that address the security concerns of routing considering varying parameters. This paper illustrates a hybrid routing protocol, SDSR Secure Dynamic Source Routing Protocol which takes the recommendations of neighbour nodes to judge about node’s authenticity and uses that information to calculate the trust value of a node. Using trust values of nodes, malicious nodes are identified and those nodes are excluded from data transmission path between the source and destination. The performance of SDSR is also evaluated in terms of efficiency parameters like Packet Delivery Ratio, Packet Loss, Communication Overhead, Throughput etc., and results are presented. This protocol can also be compared with existing routing protocols proposed for MANETS in terms of various quality of service parameters.

ELPC-Trust Framework for Wireless Sensor Networks

Wireless Sensor Network (WSN) and its security concern play a vital part in its effecting functioning. WSN routing layer attacks pose a great threat to its functionality, whereas if a situation arises in which multiple attacks co-exist, then the scenario will become worse. In such cases the reliability of the network deployed is greatly questionable. Thus an Intrusion detection cum Trust based framework is mandatory to detect such co existing malicious activities in order to maintain the network reliability. Energy packed Cluster heads and sink nodes are utilized for this kind of trust computation process. To achieve this, an energy based abnormality detection of malicious nodes is proposed, upon which based on the packet rate and the lifetime of sensor nodes a trust value is computed. The trust framework involves two phases namely Threat Detection phase which performs attack categorization based on Energy, Packet Count and Z scores followed by the second phase which computes the trust values for each node. Trust scores are computed based on the intensity of the attack in terms of their network performance degradation. Attacks such as Gray hole, Black hole, Wormhole, Flooding and Data Modification attacks are addressed. Data Modification attacks are detected uniquely based on the Z scores values of the sensed data set and upon the location of the nodes. If any node is found to consume abnormal energy either below or above certain threshold, identified nodes are categorized into two groups based on their threshold. Hierarchical decision making is introduced, which implies only the abnormal energy consuming nodes (among the total sensor nodes deployed in the network) are considered for further packet count based attack categorization. This way we can reduce the computational overhead of traditional trust models in which each node is checked for its reliability against multiple trust factors. Upon detecting the attacks and computing the trust values of nodes, only the nodes which have a nominal trust value are included in the routing process. Simulations were carried out in NS2 Mannasim Framework with static and mobile sensor nodes. Proposed Energy-Lifetime-Packet Count (ELPC)-Trust framework was tested under five different types of attack scenarios in a co-existing manner. Performance of the network by including the proposed ELPC trust and by ignoring the detected malicious nodes increases the throughput by 500 and PDR by 40% when compared with the attack scenario. But on the other hand introduces a delay of 0.5 seconds. Network Performance is improved in case of static networks. Under mobile scenarios proposed ELPC trust incurs high amount of delay.

Blockchain Powered Secure Range-Free Localization in Wireless Sensor Networks

A novel trust-based range-free secure algorithm using blockchain technology is considered in hostile WSNs for localization. The trust values of beacon nodes are evaluated against reputation value, mobility, residual energy and neighbor node list. The blockchain technology is implemented then to share the beacon nodes trust value with neighbor nodes. The highly trustworthy beacon nodes are subsequently elected as a miner for the mining process of blocks so that unknown nodes get information from highly honest beacon nodes to perform the localization process correctly. A set of simulations is conducted to validate the effectiveness of the proposed algorithm compared to the existing one.

IC-MADS: IoT Enabled Cross Layer Man-in-Middle Attack Detection System for Smart Healthcare Application

Smart healthcare is one of the core applications of the Internet of Things (IoT) technology in which the body sensors capture the patient's periodic data and transmit seamlessly over the wireless communications to remote monitoring stations. Due to the open nature of wireless communications, privacy-preserving and security are the biggest concern for IoT enabled healthcare systems. Several trust-based and cryptography-based solutions proposed to achieve the privacy-preserving and data security, however, such layered solutions failed to address the cross-layer attacks such as Man-in-Middle Attack (MIMA). Thus we believe that cross-layer attack detection methods achieve effective protection against such attacks. This paper proposed the novel lightweight cross-layer trust computation algorithm for MIMA attacker detection called IC-MADS. The IC-MADS consists of two main contributions such as energy-efficient clustering and cross-layer attack detection. The clustering algorithm proposed for optimal Cluster Head (CH) selection using the probability computation and evaluation approach. Each sensor node probability is computed using the parameters like residual energy, distance to Base Station, and node degree parameters. The node with a higher probability value becomes the CH. This solves the energy imbalance and load balancing problems. The cross-layer trust evaluation approach introduced node evaluation to detect the MIMA attackers in the network. The trust computation of each node is performed by using the sensor nodes parameters across the different layers such as network, physical, and MAC layers. The aggregate trust value of each sensor node is then compared with the threshold value to check whether the node is an attacker. The simulation results prove that IC-MADS achieves better protection against MIMA attacks with minimum overhead and energy consumption.

Trust Computation using Belief Model in Mobile Ad Hoc Network Avoiding Ballot Stuffing and Bad Mouthing

Trusted path in MANET ensures packet delivery and reduces the packet dropping which results in a saving of bandwidth and energy of the mobile node. Trust path finding mechanism has been proposed in the literature based on direct and indirect observations and applying Bayesian theory, Dempster-Shafer theory involving probability logic. In this paper, we studied trust computation problem in MANET with predefined fixed movement and random movement (frMANET) to compute trust to get over bad mouthing and ballot stuffing. Our scheme(frMANET scheme) is based on subjective logic based belief model involving uncertainty in behavior. We use consensus for parallel paths and discounting for transitive paths. We use public key based digital signature to deal with nonrepudiation. This identifies the node if denying that it is bad mouthing or ballot stuffing. Unlike trust management in a conventional scheme that computes trust based on packet dropping and forwarding, we have added a parameter - state of the node indicating priority work and unable to participate notification. We include service rating as well considering file sharing and file downloading as service rating parameter. We have evaluated University case study of a course offered by a professor in university to the enrolled and not enrolled students. The simulation results show an increase in packet delivery ratio with marginal overhead in average message transmission. The scheme helps in avoiding unnecessary fluctuations in trust values of trustworthy nodes and also ensures less computational overhead. This research is helpful when communication is frequent and failure of delivery of message is not tolerable in MANET and nodes need to be rated for goodness.

Trust Routing Protocol Based on Cloud-Based Fuzzy Petri Net and Trust Entropy for Mobile Ad hoc Network

The trust-based routing mechanisms are proposed to enhance the security of the mobile ad hoc network (MANET), which use the performance metrics of a node to evaluate the trust value of the node. However, some performance metrics are fuzzy, which are easier to be described qualitatively than to be expressed quantitatively. Therefore, the inability to quantitatively express these performance metrics leads to the inaccuracy in the calculation of the trust values of nodes. Meanwhile, some routing mechanisms add the path with the highest credibility to routing table without considering the hop counts of the route in route selection, which reduces quality of service (QoS) of the routing. Aiming at the above problems, firstly, we use cloud model to deal with the fuzziness of performance metrics. Specifically, a trust reasoning model based on cloud model and fuzzy Petri net (FPN) is presented to evaluate the credibility of nodes. Then we propose a routing algorithm based on trust entropy. Routes with the minimum trust entropy are selected to add to routing table. This routing algorithm can reflect the comprehensive effect of route hops and the trust values of nodes on routing selection, thus improving QoS in MANET. Finally, the TUE-OLSR protocol is established based on the trust entropy routing algorithm and the optimized link state routing (OLSR) protocol. What’s more, the effectiveness of TUE-OLSR protocol is verified by simulation experiments, which illustrate that TUE-OLSR protocol performs better than existing trust-based OLSR protocols in terms of packet delivery ratio and average latency.

Secure encryption algorithms for wireless sensor networks based on node trust value

The data transmission in the wireless sensor network is affected by the forwarding randomness of the relay node, resulting in poor security encryption performance. In order to improve the security encryption capability of wireless sensor network, a wireless sensor network security encryption algorithm based on node trust value is proposed. The linear coding design of sensor network transmission data is carried out according to the trust degree and the composite chaotic model is used for recursive analysis of vector quantisation in wireless sensor network encryption process and then the linear block code design of encryption key and decryption key is realised. The regression analysis results of node trust value are used to realise wireless sensor network security encryption. Simulation results show that the security of wireless sensor network encryption used proposed method is better, the distortion of encrypted transmission is lower and the performance is better.

Trusted Opportunistic Routing Based on Node Trust Model

In vehicular ad hoc networks, opportunistic routing can effectively improve the reliability and throughput. However, opportunistic routing also has security issues. For example, malicious nodes can easily mix into node candidate sets, which can interfere with network performance. In this paper, a trust model based on node behavior is proposed for solving the problem of malicious nodes in the opportunistic routing and forwarding candidate set. The proposed trust model uses pruning and filtering mechanisms to remove malicious suggestions,and uses dynamic weight calculation methods to combine direct trust and indirect trust when calculating the comprehensive trust value, which can screen and filter low-trust nodes in the network. Then, combining the ETX (Expected Transmission Count) value and the node trust value, an opportunity routing algorithm based on trust model (BTOR) is proposed. Extensive simulation results represent that the algorithm can significantly improve the network performance and reduce the interference of malicious nodes to the network system.

Secure encryption algorithms for wireless sensor networks based on node trust value

Secure encryption algorithms for wireless sensor networks based on node trust value

An algorithm for determining data forwarding strategy based on recommended trust value in MANET

In mobile ad hoc networks (MANET) with selfish nodes and malicious nodes, the network performance is seriously affected. We propose an algorithm based on the recommended trust value, i.e., collaborative computing trust model (CCTM) algorithm, to decide the data forwarding strategy. In the algorithm, the carrier node carrying the message collects recommended data of neighbour nodes adopts K-nearest neighbour (KNN) algorithm principle to filter the false recommended data and select K neighbour nodes as collaborative computing nodes to calculate the recommended trust value of neighbour nodes respectively, and then selects the neighbour node with the highest recommended trust value as the next hop node. The simulation experiments show that when the selfish and malicious nodes number is 10, CCTM is higher than Epidemic algorithm and MDT about 3% and 8% respectively in terms of transmission success rate; CCTM is higher than Epidemic about 14% and lower than MDT about 15% in terms of average transmission delay; CCTM is lower than MDT about 3% in terms of routing overhead. Overall, CCTM algorithm not only has better performance in terms of transmission success rate, delay and routing overhead, but also improves the security of data transmission.

Secure Access Control Model for Cloud Computing Environment with Fuzzy Max Interval Trust Values

Cloud computing needs service provider with reliable communication for increasing the user trust. As existence of cloud depends on quality of services, evaluation of this trust value needs to be carried out by the cloud. Many of the web services provided by E-commerce, social sites, digital platform maintain this for the faith of user by estimating the reliability of service provider. This paper focuses on a model that can identify real nodes by its behavior in cloud. Here fuzzy max interval values have been evaluated from the transactional behavior of the node in fixed interval. By increase in transaction count, trust value of real node trust increases and trust value of malicious nodes decreases. The work is based on Role based Access Control (RBAC), which has three type of roles (Admin, Data owner, Node). Data owner content security was achieved by AES algorithm and only trusted node can access those resources. Experiment was performed by carrying out simulations on ideal and environment under attack. Analysis of evaluation parameters values shows that proposed model of fuzzy max interval trust is better as compared to other existing Domain Partition Trust Model (DPTM), for identification of malicious nodes.

An Energy-Balanced Trust Cloud Migration Scheme for Underwater Acoustic Sensor Networks

As a candidate trust management scheme, trust models based on the cloud theory are always taken into account when detecting malicious attacks in Underwater Acoustic Sensor Networks (UASNs). To evaluate the trust values of nodes accurately, the evidence of trust ought to be collected frequently. As a result, continual trust update results in excessive energy consumption or premature death of some sensor nodes that are close to the trust cloud node. To address the above issues, in this paper, we propose an Energy-balanced Trust Cloud Migration scheme (ETCM) for UASNs, which consists of Destination Node Determination (DND), trust cloud migration and trust cloud update. Particularly, DND is performed hierarchically to obtain the destination node for trust cloud migration by selecting the candidate destination clusters, determining the destination cluster and the destination node, respectively. First, the candidate destination clusters are selected based on the distribution for the overall residual energy in UASNs using the simulated annealing algorithm. Then, an indicator of Cluster Ability (CA) is proposed to seek the destination cluster. Particularly, to calculate CA, the improved standardized Euclidean distance formula is employed to evaluate the connectivity between clusters and their neighboring clusters. Finally, on the basis of the defined node density reachability and the residual energy, the Node Ability (NA) is presented to indicate the capacity of nodes for trust cloud storage, calculation and update. The destination node in the destination cluster can be determined as the new trust cloud node using the NA. Simulation results demonstrate that the proposed ETCM scheme can balance energy consumption, increase node survival ratio and prolong lifetime effectively.

Energy based incentive scheme for secure opportunistic routing in vehicular delay tolerant networks

Opportunistic forwarding mechanism in delay tolerant networks (DTN) makes the network exposed to vulnerabilities. Providing security to existing routing protocols available for delay tolerant network becomes very difficult due to unavailability of sufficient contacts. It is necessary to design a secure routing protocol to overcome these issues. Energy is one of the crucial parameters in data forwarding and incentives should be offered to vehicular DTN nodes on the basis of energy spent for a particular message. This paper presents the secure routing mechanism which is based on the trust value of the vehicular DTN nodes. Incentive scheme is based on energy spent by the vehicular DTN node for forwarding data successfully. Routing is based on the trust value of the vehicular DTN nodes and incentive will be offered on successful delivery of the message. A source node offers the payment for successful delivery based on the time in which the message is delivered. The trust authority evaluates the credit and trust value for the participating vehicular DTN nodes based on energy and efforts put in successful delivery of the message.

CTRUST: A Dynamic Trust Model for Collaborative Applications in the Internet of Things

Security through trust presents a viable solution for threat management in the Internet of Things (IoT). Currently, a well-defined trust management framework for collaborative applications on the IoT platform does not exist. In order to estimate reliably the trust values of nodes within a system, the trust should be measured by suitable parameters that are based on the nodes’ functional properties in the application context. Existing models do not clearly outline the parametrization of trust. Also, trust decay is inadequately modeled in most current models. In addition, trust recommendations are usually inaccurately weighted with respect to previous trust, thereby increasing the effect of bad recommendations. A new model, CTRUST, is proposed to resolve these shortcomings. In CTRUST, trust is accurately parametrized while recommendations are evaluated through belief functions. The effects of trust decay and maturity on the trust evaluation process were studied. Each trust component is neatly modeled by appropriate mathematical functions. CTRUST was implemented in a collaborative download application and its performance was evaluated based on the utility derived and its trust accuracy, convergence, and resiliency. The results indicate that IoT collaborative applications based on CTRUST gain a significant improvement in performance, in terms of efficiency and security.

Application of Grey Relation Analysis Theory to Choose High Reliability of the Network Node

The research on resource sharing network safety problem mainly refers to the concept of trust management in distributed systems, and uses trust management method to realize secure access to shared services and data, etc. This paper describes the method of the grey correlation analysis theory that is used to calculate a reliable resource node trust value, and applies it in the access nodes feedback recommendation algorithm to adjust the recommended resource node trust value. The simulation results show that the method can obviously improve the success rate of resource searching.

BTEM: Belief based trust evaluation mechanism for Wireless Sensor Networks

With the emergence of WSNs in the recent times, providing trustworthy and reliable data delivery is challenging task due to unique characteristics and constraints of nodes. Malicious node can easily disrupt the integrity of network through the inclusion of false and malicious data and initiate internal attacks. Detection of malicious nodes using trust-based security is an effective and lightweight countermeasure as compared to key based security schemes which incurs higher overhead costs. The WSNs will play greater role in the next-generation IoT systems and a compromised node can jeopardize the availability and authenticity of sensory layer. In this paper, an efficient Belief based trust evaluation mechanism (BTEM) is proposed which isolates the malicious node from trust-worthy nodes and defend against Bad-mouth, On–Off and Denial of Service (DoS) attacks. Bayesian estimation approach is used in gathering direct and In-direct trust values of the sensor nodes which further considers the correlation of the data collected over the time and then estimate imprecise knowledge in decision making for secure delivery of data thus avoiding the malicious nodes. Compared with existing approaches, the proposed BTEM performs better in the detection of malicious node (MN), with lesser delay and improved network throughput.

Multimedia detection algorithm of malicious nodes in intelligent grid based on fuzzy logic

Intelligent grid transmits data by means of wireless communication. The wireless communication network is vulnerable to multiple kinds of network attacks. Trust model is considered to be an important way to defend against malicious network attacks in large-scale communication networks. Concerning the problem of node attack in smart grid, a trust model FLTM based on fuzzy logic is proposed. FLTM model makes full use of fuzzy logic system to deal with uncertainties, estimates the overall trust value of nodes, and then detects malicious nodes. Taking direct trust, indirect trust and historical trust as inputs, the output is the overall trust of the node. Experimental data show that the proposed FLTM model can detect malicious nodes effectively. In the later stage, the FLTM model is applied to routing, thus improving the performance of data transmission.

Secure Data Aggregation Mechanism based on Constrained Supervision for Wireless Sensor Network

The data aggregation process of wireless sensor networks faces serious security problems. In order to defend the internal attacks launched by captured nodes and ensure the reliability of data aggregation, a secure data aggregation mechanism based on constrained supervision is proposed for wireless sensor network, which uses the advanced LEACH clustering method to select cluster heads. Then the cluster heads supervise the behaviors of cluster members and evaluate the trust values of nodes according to the communication behavior, data quality and residual energy. Then the node with the highest trust value is selected as the supervisor node to audit the cluster head and reject nodes with low trust values. Results show that the proposed mechanism can effectively identify the unreliable nodes, guarantee the system security and prolong the network lifetime.