Hybrid Trust Model Research Articles

Hybrid Trust Model for Identifying Malicious Attacks in Underwater Acoustic Sensor Network

Hybrid Trust Model for Identifying Malicious Attacks in Underwater Acoustic Sensor Network

A Hybrid Trust Model against Insider Packet Drop Attacks in Wireless Sensor Networks.

Quick and accurate detection of inside packet drop attackers is of critical importance to reduce the damage they can have on the network. Trust mechanisms have been widely used in wireless sensor networks for this purpose. However, existing trust models are not effective because they cannot distinguish between packet drops caused by an attack and those caused by normal network failure. We observe that insider packet drop attacks will cause more consecutive packet drops than a network abnormality. Therefore, we propose the use of consecutive packet drops to speed up the detection of inside packet drop attackers. In this article, we describe a new trust model based on consecutive drops and develop a hybrid trust mechanism to seamlessly integrate the new trust model with existing trust models. We perform extensive OPNET (Optimized Network Engineering Tool) simulations using a geographic greedy routing protocol to validate the effectiveness of our new model. The simulation results show that our hybrid trust model outperforms existing trust models for all types of inside packet drop attacks, not only in terms of detection speed and accuracy as it is designed for, but also in terms of other important network performance metrics, such as packet delivery rate, routing reliability, and energy efficiency.

A Novel Multifaceted Trust Management Framework for Vehicular Networks

Maintaining interconnectivity between dynamic vehicular nodes and ensuring trust in vehicular networking is still a challenging issue. It is crucial for the vehicular environments to maintain a stable interconnectivity between the vehicular nodes and further to prevent the vehicular nodes from broadcasting fake messages and simultaneously protect the vehicles against tracking attacks. An efficient Trust Management System (TMS) is proposed in this paper that will ensure trustworthiness and stable interconnectivity between vehicular entities to assure road safety and reliable communication. The proposed approach incorporates a novel timestamp mechanism and block chain concepts to ensure the steady inter-connectivity between the dynamic vehicular nodes. Further, the framework leverages block chain concepts to verify the correctness of the events stored in the Road Side Units (RSUs). It also proposes a versatile hybrid trust model that uses innovative direct and recommended trust evaluation techniques to compute trust between the vehicular entities. Moreover, the framework integrates a threading mechanism to schedule message execution in direct trust evaluation, and clustering techniques to group similar messages in indirect trust evaluation. Various experimental and comparative analyses with other related studies are carried out in a simulated environment to evaluate the performance of the proposed hybrid trust model. The findings show that the proposed trust model produces an accuracy of 92% in identifying malicious nodes.

A hybrid trust model based on communication and social trust for vehicular social networks

Vehicular social networks are emerging hybrid networks that combine traditional vehicular networks and social networks, with two key types of nodes, that is, vehicles and drivers. Since vehicle behaviors are controlled or influenced by drivers, the trustworthiness of a vehicle node is essentially determined by its own communication behaviors and its driver’s social characteristics. Therefore, human factors should be considered in securing the communication in vehicular social networks. In this article, we propose a hybrid trust model that considers both communication trust and social trust. Within the proposed scheme, we first construct a communication trust model to quantify the trust value based on the interactions between vehicle nodes, and then develop a social trust model to measure the social trust based on the social characteristics of vehicle drivers. Based on these two trust models, we compute the combined trust assessment of a vehicle node in vehicular social networks. Extensive simulations show that the proposed hybrid trust model improves the accuracy in evaluating the trustworthiness of vehicle nodes and the efficiency of communication in vehicular social networks.

A Temperature-Aware Trusted Routing Scheme for Sensor Networks: Security Approach

This paper presents a hybrid trust model, and a multifactor, depending on trust value of sensor nodes, remaining energy, and hop count, routing strategy known as Temperature-Aware Trusted Routing Scheme (TTRS). In fact, it establishes the shortest and most trusted routing path. The multifactor strategy selects trustworthy nodes to forward data and reduce energy utilization due to secure shorter routing paths. TTRS incorporates an efficient multifactor hotspot node detection algorithm (HNDA) along with route discovery as well as route maintenance mechanism to detect malicious relay nodes for consistent data delivery in an unattended environment. Experimental results express the admirable average performance gain of TTRS in terms of accurate trust evaluation, network lifetime, packet delivery rate, and average energy consumption per node, as compared to ATRP, EOSR, and SQEER. Consequently, TTRS is more accurate than the aforementioned competitive schemes under different loads in a hostile environment.

TASRP: a trust aware secure routing protocol for wireless sensor networks

Trust-based security models are efficient and reliable over traditional cryptographic schemes (e.g., encryption, key management schemes) to detect and alleviate various internal threats by estimating the trust scores of sensor nodes in a quantitative way. Trust models analyse the trustworthiness of each sensor node to improve reliability, quality of data, prevent damage, and adversely affect. This paper presents a realistic trust-based reliable routing (communication) strategy to counter selfish nodes based on the hybrid trust model. The proposed scheme (TASRP) is a multifactor routing approach that employs trust scores of nodes, residual energy, and path length to provide reliable routing paths among trusted nodes with reduced energy consumption. This multi-factor strategy helps in selecting trusted nodes to forward data and minimise energy consumption due to shorter routing paths. Simulation results show better performance in terms of robust trust values, throughput, packet delivery rate, and energy consumption of nodes.

TASRP: a trust aware secure routing protocol for wireless sensor networks

Trust-based security models are efficient and reliable over traditional cryptographic schemes (e.g., encryption, key management schemes) to detect and alleviate various internal threats by estimating the trust scores of sensor nodes in a quantitative way. Trust models analyse the trustworthiness of each sensor node to improve reliability, quality of data, prevent damage, and adversely affect. This paper presents a realistic trust-based reliable routing (communication) strategy to counter selfish nodes based on the hybrid trust model. The proposed scheme (TASRP) is a multifactor routing approach that employs trust scores of nodes, residual energy, and path length to provide reliable routing paths among trusted nodes with reduced energy consumption. This multi-factor strategy helps in selecting trusted nodes to forward data and minimise energy consumption due to shorter routing paths. Simulation results show better performance in terms of robust trust values, throughput, packet delivery rate, and energy consumption of nodes.

A Framework to Systematically Analyse the Trustworthiness of Nodes for Securing IoV Interactions

Trust plays essential role in any securing communications between Vehicles in IOV. This motivated us to design a trust model for IoV communication. In this paper, we initially review literature on IoV and Trust and present a hybrid trust model that separates the malicious and trusted nodes to secure the interaction of vehicle in IOV. Node segregation is done using value of statistics (St). If St of each node lies in the range of mean (m) plus/minus 2 standard deviation (SD) of PDR then nodes behaviour is considered as normal otherwise malicious. The simulation is conducted for different threshold values. Result depicts that PDR of trusted node is 0.63 that is much higher than the PDR of malicious node that is 0.15. Similarly, the average no. of hops and trust dynamics of trusted nodes are higher than that of malicious node. So, on the basis of values of PDR, number of available hops and trust dynamics, the malicious nodes can be clearly identified and discarded.

Introduction to the Special Issue on Evolving IoT and Cyber-Physical Systems: Advancements, Applications, and Solutions

Introduction to the Special Issue on Evolving IoT and Cyber-Physical Systems: Advancements, Applications, and Solutions

Trusted Secure Routng for Mobile Adhoc Networks using Hybrid Trust Model

Mobile ad ho network is a self-prepared network, in which each node acts as a router. In traditional routing methods for MANETs, optimization method is not considered for security. This paper, proposes the Hybrid Trust Model (HTM) in MANETs, here optimization techniques is used that is Ant Colony Optimization (ACO). ACO algorithm provides optimization method for emerging routing algorithms for mobile ad hoc networks. This ACO algorithm, find shortest path from the initial node to neighboring nodes and it will provide key for each and every nodes. This method is realistic to the mobile ad hoc. This paper carried out of some features as well as performance analysis of the proposed ACO based DSR routing protocols. In our simulation work considering the some parameters such as connectivity, Energy, Average Delay, Overhead, Packet delivery ratio, Throughput and Storage area. The simulation result shows performance analysis of the reliable security of HTM, increase the system efficiency and improve the security in data transmission.

Hybrid Trust Model for Worm Mitigation in P2P Networks

Passive worms spread so quickly in P2P networks that they can cause significant damage and serious security problems. To mitigate worm spreading, we used two classes of trust models: file-based trust and peer-based trust models. Peer-based trust provides to a peer the global trust values of all the other peers using the peers history of uploads. File trust provides to a peer the trust level of its sought file thanks to a process of voting. An hybrid trust model is introduced where we hybridize file-based and peer-based trust models. In this hybrid trust model, a requester peer checks firstly on the safety of the sought file (file trust) and then choose the most reputed peer from the set of peers that own the file (peer-based trust) for the downloading. A detailed simulation analysis is performed to study the performance of these trust models in terms of fraction of infected peers and number of infected downloaded files. Our results show that peer-based trusts could be used to mitigate the spread of worms in P2P networks because they limit downloading from malicious peers; but they are not effective in reducing the download rate of infected files from normal peers. Furthermore, we find that hybrid trust is an adequate security solution for mitigation of worm spreading in P2P network. Moreover, with comparison of several examples of peer-based trusts, we show that if we hybridize any peer-based trust with file trust, we obtain that the hybrid model is more efficient than this peer-based trust.

Trust model for secure group leader-based communications in VANET

VANET aims to improve safety for all road users. Vehicles exchange safety messages over wireless communication links which are prone to multiple attacks. To enhance the existing security of V2V communications, we propose in this paper a security framework based on vehicles behavior analysis. We define a Hybrid Trust Model (HTM) and a misbehavior detection system (MDS) where a trust metric is assigned to every vehicle depending on its behavior. Using this trust metric, a classification of the vehicles into malicious or honest is done. HTM is based on-the-fly group formation which helps to manage the communication between vehicles and the back-end system by selecting the most trustworthy node as group leader (GL). Vehicles and GL will cooperate with each other within the group and with the back-end system to detect the malicious node and to notify the Misbehavior Authority. The latter takes appropriate actions to limit the consequences of the malicious behaving node. Performance evaluation of HTM and MDS is carried out using Groovenet Simulator. Results show the efficiency of the proposed model to select the trustworthy vehicles and to monitor their behaviors, as well as to classify them and to deactivate the malicious ones.

A hybrid trust model using reinforcement learning and fuzzy logic

AbstractMultiagent systems (MASs) are increasingly popular for modeling distributed environments that are highly complex and dynamic, such as e‐commerce, smart buildings, and smart grids. Typically, agents assumed to be goal driven with limited abilities, which restrains them to working with other agents for accomplishing complex tasks. Trust is considered significant in MASs to make interactions effectively, especially when agents cannot assure that potential partners share the same core beliefs about the system or make accurate statements regarding their competencies and abilities. Due to the imprecise and dynamic nature of trust in MASs, we propose a hybrid trust model that uses fuzzy logic and Q‐learning for trust modeling. as an improvement over Q‐learning‐based trust evaluation. Q‐learning is used to estimate trust on the long term, fuzzy inferences are used to aggregate different trust factors, and suspension is used as a short‐term response to dynamic changes. The performance of the proposed model is evaluated using simulation. Simulation results indicate that the proposed model can help agents select trustworthy partners to interact with. It has a better performance compared to some of the popular trust models in the presence of misbehaving interaction partners.

An EigenTrust-based Hybrid Trust Model in P2P File Sharing Networks

Reputation systems have been proposed to distinguish malicious peers and ensure the quality of services in P2P networks. How-ever, only relying on global reputation scores to assess the reliability of file providers can weaken the subjective opinions of file requesters, which is vulnerable to some malicious attacks, e.g., camouflage attack. To address this issue, in this paper, we propose a novel hybrid trust model, namely HTM, based on the EigenTrust reputation management system. In HTM, a file requester utilizes a two-phase reference method to take both the global reputation and the direct trust of a file provider into consideration when deciding whether to download from it or not. In particular, in the first phase, a requester selects a provider from the responders based on the roulette wheel selection algorithm; while in the second phase, the requester considers the direct trust on the selected provider with our proposed direct trust evaluation approach. The extended simulation results show that our mechanism can identify and isolate the malicious peers both under individual attack and camouflage attack effectively, thus improving the performance of P2P file sharing networks.

PerContRep: a practical reputation system for pervasive content services

Social network has extended its popularity from the Internet to mobile domain. Personal mobile devices can be self-organized and communicate with each other for instant social activities at any time and in any places to achieve pervasive social networking (PSN). In such a network, various content information flows. To which extent should mobile users trust it, whilst user privacy can also be preserved? Existing work has not yet seriously considered trust and reputation management, although trust plays an important role in PSN. In this paper, we propose PerContRep, a practical reputation system for pervasive content services that can assist trustworthy content selection and consumption in a pervasive manner. We develop a hybrid trust and reputation management model to evaluate node recommendation trust and content reputation in the context of frequent change of node pseudonyms. Simulations show the advantages of PerContRep in assisting user decisions and its effectiveness with regard to unfair rating attack, collaborative unfair rating attack, on-off attack and conflict behavior attack. A prototype system achieves positive user feedback on its usability and social acceptance.

Dynamic trust enhanced security model for trusted platform based services

Binary attestation in trusted computing platforms provide the ability to reason about the state of a system using hash measurements. Property based attestation, an extension of binary attestation enables more meaningful attestation by abstracting low level binary values to high level security properties or functions of systems. In this paper, we propose TESM: A Trust Enhanced Secure Model for trusted computing platforms. We argue that given the nature of both binary and property based attestation mechanisms, an attestation requester cannot be absolutely certain if an attesting platform will behave as it is expected to behave. TESM uses a hybrid trust model based on subjective logic to combine ‘hard’ trust from measurements and properties and ‘soft’ trust from past experiences and recommendations to reduce such uncertainties. We believe that such a model will enable better reasoning about the trustworthiness of attesting platforms and thereby facilitate better security decision making.

A secure double auction protocol against false bids

M. Yokoo et al. analyzed some weaknesses in McAfee's double auction (MCD) protocol and proposed a robust threshold price double auction (TPD) protocol against false-name bids. Unfortunately, as their protocol strongly depends on the trust of auctioneer, the auctioneer's misbehavior may fail an auction process. In addition, their scheme is in fact not robust in terms of comprehensive false bids. In this paper, we further investigate weaknesses in both MCD and TPD protocols, and then propose an improved double auction protocol against false bids. We also extend it for a practical and secure double auction implementation. This is based on a hybrid trust model, where computation load is distributed to buyers and sellers while a semi-trusted manager handles the registration phase. A prominent feature of the extended protocol is its high robustness, achieved by using a publicly verifiable secret sharing scheme with threshold access structure.

Improved Double Auction Protocol based on a Hybrid Trust Model

Recently, Wang et al. proposed a set of double auction protocols with full privacy protection based on distributed ElGamal encryption. Unfortunately, their protocols are expensive in computation, and are not robust in dealing with system malfunction or user misbehavior. In this paper, we propose a secure and practical double auction protocols based on a hybrid trust model, where computation load is distributed to buyers and sellers while a semi-trusted manager handles the registration phase. A prominent feature of the proposed protocol is its high robustness, achieved by using a publicly verifiable secret sharing scheme with threshold access structure.