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.

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.

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.

Attack Resistant Trust Management Model Based on Beta Function for Distributed Routing in Internet of Things

With the rapid development of Internet of Things (IoT),the issue of trust in distributed routing systems has attracted more research attention.The existing trust management frameworks,however,suffer from some possible attacks in hostile environments,such as false accusation,collusion,on-off,and conflicting behavior.Therefore,more comprehensive models should be proposed to predict the trust level of nodes on potential routes more precisely,and to defeat several kinds of possible attacks.This paper makes an attempt to design an attack-resistant trust management model based on beta function for distributed routing strategy in IoT.Our model can evaluate and propagate reputation in distributed routing systems.We first describe possible attacks on existing systems.Our model is then proposed to establish reliable trust relations between self-organized nodes and defeat possible attacks in distributed routing systems.We also propose a theoretical basis and skeleton of our model.Finally,some performance evaluations and security analyses are provided to show the effectiveness and robustness of our model compared with the existing systems.

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.

Design and Implementation of Trusted-Router Based on Trust Management System

This paper presents a scheme to perform QoS management and assure network security by using the trusted-router based on the Trust Management System.In this trusted-router,every IP packet is forwarded and queued by its trust value,which is the quantification of the network's expectation for this packet's and its owner's behavior in the network.We outline the algorithms to calculate the trust value of the trusted-router and the IP packet.We also introduce the trust-based QoS management algorithm and the deployment of the trusted-routers which carry out this algorithm.The simulation results show that the least trusted IP packets will be dropped to save resources for those highly trusted IP packets.This will ecourage all the elements in the network to keep a good trust record.

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.

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 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.

Personalized Trust Management for Open and Flat P2P Communities

A personalized trust management scheme is proposed to help peers build up trust between each other in open and flat P2P communities. This scheme totally abandons the attempt to achieve a global view. It evaluates trust from a subjective point of view and gives personalized decision support to each peer. Simulation experiments prove its three advantages: free of central control, stronger immunity to misleading recommendations, and limited traffic overload.

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.

Trust Management in Grid-Trust Assessment and Trust Degree Calculation of a Resource—A Novel Approach

Grid Computing is concerned with the sharing and coordinated use of diverse resources in distributed Virtual Organizations. This introduces various challenging security issues. Among these trusting, the resources to be shared and coordinated with the dynamic and multi-institutional virtual organization environment becomes a challenging security issue. In this paper, an approach for trust assessment and trust degree calculation using subjective logic is suggested to allocate the Data Grid or Computational Grid user a reliable, trusted resource for maintaining the integrity of the data with fast response and accurate results. The suggested approach is explained using an example scenario and also from the simulation results. It is observed that there is an increase in the resource utilization of a trusted resource in contrast to the resource which is not trusted.

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.

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.

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.

TRUSED:A Trust-Based Security Evaluation Scheme for A Distributed Control System

Distributed control systems(DCS)have revolutionized the communication process and attracted more interest due to their pervasive computing nature(cyber/physical),their monitoring capabilities and the benefits they offer.However,due to distributed communication,flexible network topologies and lack of central control,the traditional security strategies are inadequate formeeting the unique characteristics ofDCS.Moreover,malicious and untrustworthy nodes pose a significant threat during the formation of a DCS network.Trust-based secure systems not only monitor and track the behavior of the nodes but also enhance the security by identifying and isolating the malicious node,which reduces the risk and increases network lifetime.In this research,we offer TRUSED,a trust-based security evaluation scheme that both,directly and indirectly,estimates each node’s level of trustworthiness,incorporating the cumulative trust concept.In addition,simulation results show that the proposed technique can effectively identify malicious nodes,determine their node’s trustworthiness rating,and improve the packet delivery ratio.

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.

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.