Quantum Communication Networks and Trust Management: A Survey

This paper summarizes the state of art in quantum communication networks and trust management in recent years.As in the classical networks,trust management is the premise and foundation of quantum secure communication and cannot simply be attributed to security issues,therefore the basic and importance of trust management in quantum communication networks should be taken more seriously.Compared with other theories and techniques in quantum communication,the trust of quantum communication and trust management model in quantum communication network environment is still in its initial stage.In this paper,the core technologies of establishing secure and reliable quantum communication networks are categorized and summarized,and the trends of each direction in trust management of quantum communication network are discussed in depth.

A Method for Trust Management in Cloud Computing: Data Coloring by Cloud Watermarking

With the development of Internet technology and human computing, the computing environment has changed dramatically over the last three decades. Cloud computing emerges as a paradigm of Internet computing in which dynamical, scalable and often virtuMized resources are provided as services. With virtualization technology, cloud computing offers diverse services （such as virtual computing, virtual storage, virtual bandwidth, etc.） for the public by means of multi-tenancy mode. Although users are enjoying the capabilities of super-computing and mass storage supplied by cloud computing, cloud security still remains as a hot spot problem, which is in essence the trust management between data owners and storage service providers. In this paper, we propose a data coloring method based on cloud watermarking to recognize and ensure mutual reputations. The experimental results show that the robustness of reverse cloud generator can guarantee users＇ embedded social reputation identifications. Hence, our work provides a reference solution to the critical problem of cloud security.

Trust management-based and energy efficient hierarchical routing protocol in wireless sensor networks

The single planar routing protocol has a slow convergence rate in the large-scale Wireless Sensor Network(WSN).Although the hierarchical routing protocol can effectively cope with large-scale application scenarios,how to elect a secure cluster head and balance the network load becomes an enormous challenge.In this paper,a Trust Management-based and Low Energy Adaptive Clustering Hierarchy protocol(LEACH-TM)is proposed.In LEACH-TM,by using the number of dynamic decision cluster head nodes,residual energy and density of neighbor nodes,the size of the cluster can be better constrained to improve energy efficiency,and avoid excessive energy consumption of a node.Simultaneously,the trust management scheme is introduced into LEACH-TM to defend against internal attacks.The simulation results show that,compared with LEACH-SWDN protocol and LEACH protocol,LEACH-TM outperforms in prolonging the network lifetime and balancing the energy consumption,and can effectively mitigate the influence of malicious nodes on cluster head selection,which can greatiy guarantee the security of the overall network.

Adaptive Trust Management Framework in P2P Grid Computing

In P2P Grid computing systems, the authorization decision is often tackled by two different trust management methods： policy-based approach, where authorization are built on logical rules and verifiable properties encoded in signed credentials, and reputation-based approach, based on collecting, aggregating and disseminating reputation among the peers. However, the overhead caused by proof of compliance on authorization and the absence of certifying authorities may negate the strong and objective security advantages of policy-based approach, whilst vagueness, complexity and inaccurate characterization caused by reputation evolution may eliminate the quantitative and flexible advantages of reputation-based approach. We propose an adaptive trust management framework, which combines the merit of policy proof and reputation evolution such that authorization is aware of not only the strong and objective security traits, but also the calculability and the availability security traits. Finally, the framework of system is proposed.

A Neural Network-Based Trust Management System for Edge Devices in Peer-to-Peer Networks

Edge devices in Internet of Things(IoT)applications can form peers to communicate in peer-to-peer(P2P)networks over P2P protocols.Using P2P networks ensures scalability and removes the need for centralized management.However,due to the open nature of P2P networks,they often suffer from the existence of malicious peers,especially malicious peers that unite in groups to raise each other’s ratings.This compromises users’safety and makes them lose their confidence about the files or services they are receiving.To address these challenges,we propose a neural networkbased algorithm,which uses the advantages of a machine learning algorithm to identify whether or not a peer is malicious.In this paper,a neural network(NN)was chosen as the machine learning algorithm due to its efficiency in classification.The experiments showed that the NNTrust algorithm is more effective and has a higher potential of reducing the number of invalid files and increasing success rates than other well-known trust management systems.

A Dynamic Active Multicast Group Access Control Framework Based on Trust Management System

The current multicast model provides no access control mechanism. Any host can send data directly to a multicast address or join a multicast group to become a member, which brings safety problems to multicast. In this paper, we present a new active multicast group access control mechanism that is founded on trust management. This structure can solve the problem that exists in multicast members＇ access control and distributing authorization of traditional IP multicast.

Model of Trust Management in Open Network Environment

To keep open network more efficacious and secure, it is necessary that a nice trust model and method of trust management must be developed. The reason why traditional trust models are incomplete in their function to manage trust is explained, and a general model based on hybrid trust model and introducer protocol is provided. The hybrid model is more flexible and efficacious to manage trust compared with hierarchy model and Web model. The introducer protocol is a better solution to build, maintain and refresh the trust relationship in open network environment.

Context and Machine Learning Based Trust Management Framework for Internet of Vehicles

Trust is one of the core components of any ad hoc network security system.Trust management(TM)has always been a challenging issue in a vehicular network.One such developing network is the Internet of vehicles(IoV),which is expected to be an essential part of smart cities.IoV originated from the merger of Vehicular ad hoc networks(VANET)and the Internet of things(IoT).Security is one of the main barriers in the on-road IoV implementation.Existing security standards are insufficient to meet the extremely dynamic and rapidly changing IoV requirements.Trust plays a vital role in ensuring security,especially during vehicle to vehicle communication.Vehicular networks,having a unique nature among other wireless ad hoc networks,require dedicated efforts to develop trust protocols.Current TM schemes are inflexible and static.Predefined scenarios and limited parameters are the basis for existing TM models that are not suitable for vehicle networks.The vehicular network requires agile and adaptive solutions to ensure security,especially when it comes to critical messages.The vehicle network’s wireless nature increases its attack surface and exposes the network to numerous security threats.Moreover,internet involvement makes it more vulnerable to cyberattacks.The proposed TM framework is based on context-based cognition and machine learning to be best suited to IoV dynamics.Machine learning is the best solution to utilize the big data produced by vehicle sensors.To handle the uncertainty Bayesian machine learning statistical model is used.The proposed framework can adapt scenarios dynamically and infer using the maximum possible parameter available.The results indicated better performance than existing TM methods.Furthermore,for future work,a high-level machine learning model is proposed.

Shared Resource Quality Monitoring and Dynamic Trust Management in a Community Cloud

The collaboration tools offered by Cloud Computing have increased the need to share data and services within companies or between autonomous organizations. This has led to the deployment of community cloud infrastructures. However, several challenges will arise from this grouping of heterogeneous organizations. One of the main challenges is the management of trust between the actors of the community. Trust issues arise from the uncertainty about the quality of the resources and entities involved. The quality of a resource can be examined from a security or functional perspective. Therefore, ensuring security and monitoring the quality of resources is to ensure a high level of trust. Therefore, we propose in this paper a technique for dynamic trust management and quality monitoring of resources shared between organizations. Our approach consists, on the one hand, in evaluating the quality of resources based on quality of service measurement attributes and, on the other hand, in updating the trust values according to the information deduced from these measurements. The proposed framework is evaluated in terms of resource sharing success rate and execution time. Experimental results and comparison with TNA-SL and InterTrust models show that the framework can identify and track the behavior of malicious organizations with relatively low execution time.

A detailed study on trust management techniques for security and privacy in IoT:challenges,trends,and research directions

The Internet of Things is a modern technology that is directed at easing human life by automating most of the things used in daily life.The never-ending dependency on the network for communication is attracting adversaries to exploit the vulnerabilities of IoT.Therefore,this technology is facing some serious issues and challenges concerning security and privacy.These issues and challenges are the real motivation behind considering this study.Hence,this survey includes a discussion about security and privacy challenges as well as available solutions for IoT based wireless sensor networks.This systematic literature review(SLR)focuses particularly on a popular and applicable security approach known as Trust Management System(TMS).Firstly,all aspects of trust management,including trust indicators,trust properties,trust evaluation,trust building,trust models and the importance of those models for security and privacy,trust prediction methodologies,and ultimately trust-based attacks,are covered in this literature.Secondly,trust management schemes are classified into four groups based on the methodology used for trust-based security solutions in the IoT:cryptography-based,computational and probabilistic-based,information theory-based,and others.Then,an understanding of the problems and difficulties with current methodologies is given,along with suggestions for further research.Finally,the SLR is concluded by formulating the desirable characteristics of a trust management system in the IoT and proposing a trust model suitable for IoT networks.

CROWN:A service grid middleware with trust management mechanism

Based on a proposed Web service-based grid architecture, a service grid middleware system called CROWN is designed in this paper. As the two kernel points of the middleware, the overlay-based distributed grid resource management mechanism is proposed, and the policy-based distributed access control mechanism with the capability of automatic negotiation of the access control policy and trust management and negotiation is also discussed in this paper. Experience of CROWN testbed deployment and application development shows that the middleware can support the typical scenarios such as computing-intensive applications, data-intensive applications and mass information processing applications.

H-Trust:A Group Trust Management System for Peer-to-Peer Desktop Grid

Peer-to-Peer Desktop Grid （P2PDG） has emerged as a pervasive cyber-infrastructure tackling many largescale applications with high impacts. As a burgeoning research area, P2PDG can support numerous applications, including scientific computing, file sharing, web services, and virtual organization for collaborative activities and projects. To handle trustworthiness issues of these services, trust and reputation schemes are proposed to establish trust among peers in P2PDG. In this paper, we propose a robust group trust management system, called H-Trust, inspired by the H-index aggregation technique. Leveraging the robustness of the H-index algorithm under incomplete and uncertain circumstances, H-Trust offers a robust personalized reputation evaluation mechanism for both individual and group trusts with minimal communication and computation overheads. We present the H-Trust scheme in five phases, including trust recording, local trust evaluation, trust query phase, spatial-temporal update phase, and group reputation evaluation phases. The rationale for its design, the analysis of the algorithm are further investigated. To validate the performance of H-Trust scheme, we designed the H-Trust simulator HTrust-Sim to conduct multi-agent-based simulations. Simulation results demonstrate that H-Trust is robust and can identify and isolate malicious peers in large scale systems even when a large portion of peers are malicious.

Authorization Management Framework Based on Joint Trust-Risk Evaluation

Authorization management is important precondition and foundation for coordinating and resource sharing in open networks. Recently, authorization based on trust is widely used whereby access rights to shared resource are granted on the basis of their trust relation in distributed environment. Nevertheless, dynamic change of the status of credential and chain of trust induces to uncertainty of trust relation. Considering uncertainty of authorization and analyzing deficiency of authorization model only based on trust, we proposes joint trust-risk evaluation and build the model based on fuzzy set theory, and make use of the membership grade of fuzzy set to express joint trust-risk relation. Finally, derivation principle and constraint principle of joint trust-risk relationships are presented. The authorization management model is defined based on joint trust-risk evaluation, proof of compliance and separation of duty are analyzed. The proposed model depicts not only trust relationship between principals, but also security problem of authorization.

Enhanced Energy Efficient with a Trust Aware in MANET for Real-Time Applications

Mobile ad hoc networks (MANETs) are subjected to attack detectionfor transmitting and creating new messages or existing message modifications.The attacker on another node evaluates the forging activity in themessage directly or indirectly. Every node sends short packets in a MANETenvironment with its identifier, location on the map, and time through beacons.The attackers on the network broadcast the warning message usingfaked coordinates, providing the appearance of a network collision. Similarly,MANET degrades the channel utilization performance. Performancehighly affects network performance through security algorithms. This paperdeveloped a trust management technique called Enhanced Beacon TrustManagement with Hybrid Optimization (EBTM-Hyopt) for efficient clusterhead selection and malicious node detection. It tries to build trust amongconnected nodes and may improve security by requiring every participatingnode to develop and distribute genuine, accurate, and trustworthy materialacross the network. Specifically, optimized cluster head election is done periodicallyto reduce and balance the energy consumption to improve the lifetimenetwork. The cluster head election optimization is based on hybridizingParticle Swarm Optimization (PSO) and Gravitational Search OptimizationAlgorithm (GSOA) concepts to enable and ensure reliable routing. Simulationresults show that the proposed EBTM-HYOPT outperforms the state-of-thearttrust model in terms of 297.99 kbps of throughput, 46.34% of PDR, 13%of energy consumption, 165.6 kbps of packet loss, 67.49% of end-to-end delay,and 16.34% of packet length.

A Compact Trust Computation and Management Approach for Defending against Derailed Attacks for Wireless Sensor Networks and Its Applications

One of the most effective measurements of intercommunication and collaboration in wireless sensor networks which leads to provide security is Trust Management. Most popular decision making systems used to collaborate with a stranger are tackled by two different existing trust management systems: one is a policy-based approach which verifies the decision built on logical properties and functionalities;the other approach is reputation-based approach which verifies the decision built on physical properties and functionalities of WSN. Proofless authorization, unavailability, vagueness and more complexity cause decreased detection rate and spoil the efficacy of the WSN in existing approaches. Some of the integrated approaches are utilized to improve the significance of the trust management strategies. In this paper, a Compact Trust Computation and Management (CTCM) approach is proposed to overcome the limitations of the existing approaches, also it provides a strong objective security with the calculability and the available security implications. Finally, the CTCM approach incorporates the optimum trust score for logical and physical investigation of the network resources. The simulation based experiment results show that the CTCM compact trust computation and management approach can provide an efficient defending mechanism against derailing attacks in WSN.

Blockchain Based Consensus Algorithm and Trustworthy Evaluation of Authenticated Subgraph Queries

Over the past era,subgraph mining from a large collection of graph database is a crucial problem.In addition,scalability is another big problem due to insufficient storage.There are several security challenges associated with subgraph mining in today’s on-demand system.To address this downside,our proposed work introduces a Blockchain-based Consensus algorithm for Authenticated query search in the Large-Scale Dynamic Graphs(BCCA-LSDG).The two-fold process is handled in the proposed BCCA-LSDG:graph indexing and authenticated query search(query processing).A blockchain-based reputation system is meant to maintain the trust blockchain and cloud server of the proposed architecture.To resolve the issues and provide safe big data transmission,the proposed technique also combines blockchain with a consensus algorithm architecture.Security of the big data is ensured by dividing the BC network into distinct networks,each with a restricted number of allowed entities,data kept in the cloud gate server,and data analysis in the blockchain.The consensus algorithm is crucial for maintaining the speed,performance and security of the blockchain.Then Dual Similarity based MapReduce helps in mapping and reducing the relevant subgraphs with the use of optimal feature sets.Finally,the graph index refinement process is undertaken to improve the query results.Concerning query error,fuzzy logic is used to refine the index of the graph dynamically.The proposed technique outperforms advanced methodologies in both blockchain and non-blockchain systems,and the combination of blockchain and subgraph provides a secure communication platform,according to the findings.

An Enhanced Trust-Based Secure Route Protocol for Malicious Node Detection

The protection of ad-hoc networks is becoming a severe concern because of the absence of a central authority.The intensity of the harm largely depends on the attacker’s intentions during hostile assaults.As a result,the loss of Information,power,or capacity may occur.The authors propose an Enhanced Trust-Based Secure Route Protocol(ETBSRP)using features extraction.First,the primary and secondary trust characteristics are retrieved and achieved routing using a calculation.The complete trust characteristic obtains by integrating all logical and physical trust from every node.To assure intermediate node trust-worthiness,we designed an ETBSRP,and it calculates and certifies each mobile node's reputation and sends packets based on that trust.Connection,honesty,power,and capacity are the four trust characteristics used to calculate node repu-tation.We categorize Nodes as trustworthy or untrustworthy according to their reputation values.Fool nodes are detached from the routing pathway and cannot communicate.Then,we use the cryptographic functions to ensure more secure data transmission.Finally,we eliminate the untrustworthy nodes from the routing process,and the datagram from the origin are securely sent to the target,increas-ing throughput by 93.4%and minimizing delay.

Hybrid Trust Based Reputation Mechanism for Discovering Malevolent Node in MANET

A self-contained connection of wireless links that functions without any infrastructure is known as Mobile Ad Hoc Network(MANET).A MANET’s nodes could engage actively and dynamically with one another.However,MAN-ETs,from the other side,are exposed to severe potential threats that are difficult to counter with present security methods.As a result,several safe communication protocols designed to enhance the secure interaction among MANET nodes.In this research,we offer a reputed optimal routing value among network nodes,secure computations,and misbehavior detection predicated on node’s trust levels with a Hybrid Trust based Reputation Mechanism(HTRM).In addition,the study designs a robust Public Key Infrastructure(PKI)system using the suggested trust evaluation method in terms of“key”generation,which is a crucial component of a PKI cryptosystem.We also concentrate on the solid node authenticating process that relies on pre-authentication.To ensure edge-to-edge security,we assess safe,trustworthy routes to secure computations and authenticate mobile nodes,incorporating uncertainty into the trust management solution.When compared to other protocols,our recommended approach performs better.Finally,we use simulations data and performance evaluation metrics to verify our suggested approach’s validity Our approach outperformed the competing systems in terms of overall end-to-end delay,packet delivery ratio,performance,power consumption,and key-computing time by 3.47%,3.152%,2.169%,and 3.527%,3.762%,significantly.

Logistic Regression Trust–A Trust Model for Internet-of-Things Using Regression Analysis

Internet of Things(IoT)is a popular social network in which devices are virtually connected for communicating and sharing information.This is applied greatly in business enterprises and government sectors for delivering the services to their customers,clients and citizens.But,the interaction is success-ful only based on the trust that each device has on another.Thus trust is very much essential for a social network.As Internet of Things have access over sen-sitive information,it urges to many threats that lead data management to risk.This issue is addressed by trust management that help to take decision about trust-worthiness of requestor and provider before communication and sharing.Several trust-based systems are existing for different domain using Dynamic weight meth-od,Fuzzy classification,Bayes inference and very few Regression analysis for IoT.The proposed algorithm is based on Logistic Regression,which provide strong statistical background to trust prediction.To make our stand strong on regression support to trust,we have compared the performance with equivalent sound Bayes analysis using Beta distribution.The performance is studied in simu-lated IoT setup with Quality of Service(QoS)and Social parameters for the nodes.The proposed model performs better in terms of various metrics.An IoT connects heterogeneous devices such as tags and sensor devices for sharing of information and avail different application services.The most salient features of IoT system is to design it with scalability,extendibility,compatibility and resiliency against attack.The existing worksfinds a way to integrate direct and indirect trust to con-verge quickly and estimate the bias due to attacks in addition to the above features.

Registered Nurses’ Perceptions of Factors Contributing to Trust-Based Public Management

Aim: The aim of this study was to illuminate registered nurses’ (RNs) perceptions of Trust-Based Public Management (TBPM) in Swedish health care. Design: This study follows a phenomenografic approach guided by Ference Marton’s philosophy. Methods: Semi-structured interviews were used to identify variations in RNs’ perceptions of TBPM. Between February and April 2019, 24 RNs from five Swedish public healthcare departments participated in the study. Results: The results show that none of the participants had previously heard about the work of the Swedish Delegation for TBPM. The study revealed perceptions those politicians and managers were absent from the workplace, that power had been displaced to HR, and that perceptions of trust in the leadership and of working to guidelines varied. Perceptions varied between RNs employed by the municipalities and by the hospitals concerning administration, the time allotted for work, cooperation, and education.