Trust Management Protocol Research Articles

Trustworthy data provisioning for IoT-Based circadian health evaluation systems

IoT healthcare systems use the data provided by IoT devices to make automated health decisions and to provide recommendations to users for better health. If the data sent by the device is not trustworthy, it will lead to incorrect health decisions and recommendations. In this paper, we propose a trust computational model for provisioning trusted data to the health index evaluation system (HIES). This HIES uses the trusted data selected by the trust model to calculate the health index (e.g., circadian health index) of a particular user. The objective of the proposed work is to provide a trustworthy system for better circadian health decision making by determining the trustworthiness of the data provided by health IoT devices. Unlike existing trust management protocols, our trust model considers identity-based schema such as device identity and user identity, device health, user feedback, data consensus, and acceptance rate for trustworthy data selection. Our trust computational model is resistant to malicious devices with false identities and identifies the devices that report false data. We present the performance analysis of our trusted data selection model and compare it to the baseline scheme.

Trust Based Service Management for Social Internet of Things: The Implementation

Abstract: A social internet of things (Iot) system can be seen as a union of normal peer-to-peer networks and social networks, where "things" freely establish the social relations according to the owners' social networks, and search trusted "things" that can provide services stand in need of when they come into contact with each other aggressively. We have suggested and study the design notion of many easily flexible trust management system for social Internet of Things systems in which social relationships progress are not stable but they are variable among the owners of Internet of Things devices. We have been give away the planned trade-off between trust confluence vs. trust contrast in our old easily adaptive trust management protocol design. With our regular easily adaptable trust operation principals, the social Internet of effects( SIOT) operations can fluently elect the stylish trust r settings in response to changing Internet of effects social parameters similar that not only trust assessment is accurate but also the application performance is enhanced. We have propose a table-lookup method to apply the analysis results dynamically and demonstrate the practicability of our proposed adaptive trust management scheme with two actual social IoT service construction applications.

BTrust: A New Blockchain-Based Trust Management Protocol for Resource Sharing

BTrust: A New Blockchain-Based Trust Management Protocol for Resource Sharing

Blockchain-Based Trust Management Framework for Cloud Computing-Based Internet of Medical Things (IoMT): A Systematic Review.

The internet of medical things (IoMT) is a smart medical device structure that includes apps, health services, and systems. These medical equipment and applications are linked to healthcare systems via the internet. Because IoT devices lack computational power, the collected data can be processed and analyzed in the cloud by more computationally intensive tools. Cloud computing in IoMT is also used to store IoT data as part of a collaborative effort. Cloud computing has provided new avenues for providing services to users with better user experience, scalability, and proper resource utilization compared to traditional platforms. However, these cloud platforms are susceptible to several security breaches evident from recent and past incidents. Trust management is a crucial feature required for providing secure and reliable service to users. The traditional trust management protocols in the cloud computing situation are centralized and result in single-point failure. Blockchain has emerged as the possible use case for the domain that requires trust and reliability in several aspects. Different researchers have presented various blockchain-based trust management approaches. This study reviews the trust challenges in cloud computing and analyzes how blockchain technology addresses these challenges using blockchain-based trust management frameworks. There are ten (10) solutions under two broad categories of decentralization and security. These challenges are centralization, huge overhead, trust evidence, less adaptive, and inaccuracy. This systematic review has been performed in six stages: identifying the research question, research methods, screening the related articles, abstract and keyword examination, data retrieval, and mapping processing. Atlas.ti software is used to analyze the relevant articles based on keywords. A total of 70 codes and 262 quotations are compiled, and furthermore, these quotations are categorized using manual coding. Finally, 20 solutions under two main categories of decentralization and security were retrieved. Out of these ten (10) solutions, three (03) fell in the security category, and the rest seven (07) came under the decentralization category.

Blockchain based holistic trust management protocol for ubiquitous and pervasive IoT network

ABSTRACT The new emerging blockchain (BC) technology integrated with the IoT ecosystem revolutionised the IoT world. Classic BC with bitcoin method was realised as very expensive operations difficult to adopt for smart IoT applications; therefore, we integrated IoT network with overlay BC with distributed ledger capability to provide a secure trust management system, which can address access control issues of devices on resources. Further, the R-LEACH protocol followed by the same group urges additional cluster head requirement to establish trust between nodes is not considered in our proposed approach. The main advantage of this method is utilising ledgers for holding the trust and IoT information ensuring tamper-proof data. The miners of blockchain layer perform the trust value calculations based on trust evidence and achieved fast trust convergence, accuracy, and resilience against adversary attacks. Our proposed approach enhances privacy, reliability, availability, and more importantly, sharing and storage of trust information and also followed the consensus mechanism Proof-of-Authority (PoA) to approve the synthesis trust value of related transactions by the pre-authenticated miners/validators, from which we can take more accurate trust-based decisions. Performance results of our blockchain-based trust management approach outperformed literature review trust mechanisms for protecting trust data manipulation against the malicious nodes.

Block diagonal dominance-based dynamic programming for detecting community

Clustering or partition is a fundamental work for graph or network. Detecting communities is a typical clustering, which divides a network into several parts according to the modularity. Community detection is a critical challenge for designing scalable, adaptive and survivable trust management protocol for a community of interest-based social IoT system. Most of the existed methods on community detection suffer from a common issue that the number of communities should be prior decided. This urges us to estimate the number of communities from the data by some way. This paper concurrently considers eliminating the number of communities and detecting communities based on block diagonal dominace adjacency matrix. To construct a block diagonal dominance adjacency matrix for the input network, it first reorders the node number by the breadth-first search algorithm. For the block diagonal dominance adjacency matrix, this paper shows that the numbers of nodes in a community should be continuous adjacent. And thus, it only needs insert some breakpoints in node number sequence to decide the number of communities and the nodes in every community. In addition, a dynamic programming algorithm is designed to achieve an optimal community detection result. Experimental results on a number of real-world networks show the effectiveness of the dynamic programming approach on the community detection problem.

A Decentralized Blockchain-Based Trust Management Protocol for the Internet of Things

The Internet of Things (IoT) is a network that integrates a variety of heterogeneous nodes, such as connected devices (sensors, robots, smart phones…), connected cars, smart homes, etc. These smart objects communicate and collaborate between each other in distributed and dynamic environments that face several security challenges. Trust management is one of the most important challenges in such environments. Existing trust management solutions do not meet the new requirements of IoT such as heterogeneity, mobility and scalability. In this paper, we propose a hierarchical and scalable based blockchain trust management protocol with mobility support in massively distributed IoT systems. In our protocol, mobile smart objects disseminate trust information about service providers to the blockchain. Thus, all the objects will have a global view about each service provider in the architecture which speeds up the trust decision making. In addition, our protocol is resilient against known malicious attacks such as \textit{bad-mouthing}, \textit{ballot-stuffing} and \textit{cooperative attacks}. We confirm the efficiency of our proposal through theoretical analysis and extensive simulations. Finally, we show that it outperforms existing solutions especially in terms of scalability, mobility support, communication and computation.

Dynamic Trust Management for Community Based Mobile Grid Application

Mobile Grid is the inter-networking of heterogeneous physical as well as virtualdevices. Each device transfer and share the information with each other. Trust management plays a significant role in network based applications for information collection, data mining, qualified services with context-awareness, upgraded client protection and data security. It assists individuals with beating impression of vulnerability, threat and participates in client acknowledgment to utilization on grid services and applications. In this paper a unique trust management protocol is proposed for network based mobile grid application to manage misbehaving nodes whose status or performance may change dynamically. Trust plays an important role for handling the security in the community based system. Trust management provides facilitate to identify malfunctions and also make legitimate collaboration and enhance the user privacy and information security.

Trust-Based Service Management for Mobile Cloud IoT Systems

We propose and analyze a 3-tier cloud-cloudlet-device hierarchical trust-based service management protocol called IoT-HiTrust for large-scale mobile cloud Internet of Things (IoT) systems. Our mobile cloud hierarchical service management protocol allows an IoT customer to report its service experiences and query its subjective service trust score toward an IoT service provider following a scalable report-and-query design. We conduct a formal scalability analysis along with an ns-3 simulation performance analysis demonstrating that IoT-HiTrust not only achieves scalability without compromising accuracy, convergence, and resiliency properties against malicious attacks but also outperforms contemporary distributed and centralized IoT trust management protocols. We test the feasibility by applying IoT-HiTrust to two case studies: 1) a smart city travel service composition and binding application and 2) an air pollution detection and response application. The results demonstrate that IoT-HiTrust outperforms contemporary distributed and centralized trust-based IoT service management protocols in selecting trustworthy nodes to maximize application performance, while achieving scalability.

Securing Emergency Communications for the Next-Generation Networks

Delay Tolerant Network (DTN) provides connectivity where there is uncertainty in end-to-end connectivity. In DTN, nodes exchange buffered messages upon an encounter. In disaster operations where the telecommunication and power infrastructures are completely broken down or destroyed, DTN can be used to support emergency communication till these infrastructures are restored. Security in DTN remains a major challenge because of its network characteristics such as frequent disruptions, dynamic topology, limited and constrained resources. One of the major threats in DTN is Denial of Service (DoS) attacks. This attack mainly comes from intermediary nodes that drop or flood packets in the network which often results in the degradation of the network performance. In this paper, we propose a collaborative content-aware trust forwarding for emergency communication networks. Extensive simulations and validations show that the proposed schemes outperform existing routing and trust management protocols in the presence of malicious nodes and are resilient to trust related attacks.

A reputation-based truthfulness paradigm for multi-hop transmission in cognitive radio networks

Cognitive radio networks (CRNs) consist of different intellectual users with capability of sensing and sharing underutilised spectrum, and they are called as cognitive users (CUs). The spectrum is allocated to licensed users or primary users (PUs), but they do not utilise it completely. To overcome an ever-increasing spectrum demand and utilise the underutilised licensed spectrum, the cognitive radio plays a major role. In this distributed network, communications among CUs become more challenging due to channel heterogeneity, uncontrolled environment, a need of cooperative and accurate sensing, and different security attacks. Thus, this affects and degrades system and CRN performance, which creates an opportunity for a trust management model to manage the CRNs properly. In this paper, we propose an efficient trust management protocol for centralised and distributed CRNs to build a trust-based system over the complete cognitive cycle to protect against security attacks brought by the unreliable individuals. The security analysis and simulation results represent that the proposed protocol can identify malicious behaviour and thus, it enhances reliability of the network in centralised and distributed circumstances.

Trust-Based Decision Making for Health IoT Systems

With the onset of the Internet of Things (IoT) era, the number of IoT devices and sensors is increasing tremendously. This paper is concerned with a health IoT system consisting of various IoT devices carried by members of an environmental health community. We propose a novel trust-based decision making protocol that uses trust-based information sharing among the health IoT devices, so that a collective knowledge base can be built to rate the environment at a particular location and time. This knowledge would enable an IoT device acting on behalf of its user to decide whether or not it should visit this place/environment for health reasons. Unlike existing trust management protocols, our trust-based health IoT protocol considers risk classification, reliability trust, and loss of health probability as three design dimensions for decision making, resulting in a protocol suitable for decision making in health IoT systems. Our protocol is resilient to noisy sensing data provided by IoT devices either unintentionally or intentionally. We present performance data of our trust-based health IoT protocol and conduct a comparative performance analysis of our protocol with two baseline protocols to demonstrate the feasibility.

Trust-Based Task Assignment With Multiobjective Optimization in Service-Oriented Ad Hoc Networks

We propose and analyze a trust management protocol in service-oriented mobile ad hoc networks (MANETs) populated with service providers and service requesters, and demonstrate the resiliency and convergence properties against bad-mouthing, ballot-stuffing, opportunistic service, and self-promotion attacks. To demonstrate the applicability, we consider a mission-driven service-oriented MANET that must handle dynamically arriving tasks to achieve multiple conflicting objectives. We devise a trust-based heuristic algorithm based on auctioning with local knowledge of node status to solve this node-to-task assignment problem with multiobjective optimization (MOO) requirements. Our trust-based heuristic algorithm has a polynomial runtime complexity, rather than an exponential runtime complexity as in existing work, thus allowing dynamic node-to-task assignment to be performed at runtime. It outperforms a nontrust-based counterpart using blacklisting techniques while performing close to the ideal solution quality with perfect knowledge of node status over a wide range of environmental conditions. We conduct extensive sensitivity analysis of the results with respect to key design parameters and alternative trust protocol designs. We also develop a table-lookup method to apply the best trust protocol parameter settings upon detection of dynamically changing environmental conditions to maximize MOO performance.

Trust-Based Service Management for Social Internet of Things Systems

A social internet of things (IoT) system can be viewed as a mix of traditional peer-to-peer networks and social networks, where “things” autonomously establish social relationships according to the owners’ social networks, and seek trusted “things” that can provide services needed when they come into contact with each other opportunistically. We propose and analyze the design notion of adaptive trust management for social IoT systems in which social relationships evolve dynamically among the owners of IoT devices. We reveal the design tradeoff between trust convergence versus trust fluctuation in our adaptive trust management protocol design. With our adaptive trust management protocol, a social IoT application can adaptively choose the best trust parameter settings in response to changing IoT social conditions such that not only trust assessment is accurate but also the application performance is maximized. We propose a table-lookup method to apply the analysis results dynamically and demonstrate the feasibility of our proposed adaptive trust management scheme with two real-world social IoT service composition applications.

Enhancing the Security for Manet by Identifying Untrusted Nodes using Uncertainity Rules

Background/Objectives: Trust based models offer security against vulnerabilities due to the dynamic and open wireless medium. The raise up of uncertain reasoning methods originates from the artificial intelligence leads to trust management protocols for the creation of secure environment in MANET. Methods/Statistical Analysis: In this paper, two schemes namely, direct and indirect observation based trust evaluation are proposed. Initially, the network is formed to investigate the security. The utilization of full probability model in Bayesian interface evaluates the trust from the observer node in direct observation scheme. Alternatively, the neighbor hop information is used in the derivation of trust value in indirect observation scheme. Another type of uncertain reasoning called Dempster-Shafter theory calculates the trust value after the observation schemes. Finally, the Dijkstra’s algorithm establishes the routing process on the basis of shortest path. Findings: The proposed observation schemes provide more accurate results compared to existing ones. The comparative analysis of proposed hybrid model with the existing model assures the effectiveness on the parameters of Packet Delivery Ratio (PDR), throughput with less overhead for variation in number of nodes and node speed. Improvements/Applications: The results of MANET routing scenario positively support the effectiveness and performance of our scheme and we can extend the proposed scheme to MANETs with cognitive radios. Keywords: Bayesian Interface, Dempster-Shafter Theory (DST), Direct Observation, Indirect Observation, Mobile Ad-hoc Network (MANET), Security, Trust Evaluation, Uncertain Reasoning

Hierarchical trust management of community of interest groups in mobile ad hoc networks

In mission-critical applications deployed in mobile ad hoc networks, very frequently a commander will need to assemble and dynamically manage Community of Interest (COI) mobile groups to achieve the mission assigned despite failure, disconnection or compromise of COI members. In this paper, we present a dynamic hierarchical trust management protocol that can learn from past experiences and adapt to changing environment conditions (e.g., increasing misbehaving node population, evolving hostility and node density, etc.) to enhance agility and maximize application performance. With trust-based misbehaving node detection as an application, we demonstrate how our proposed COI trust management protocol is resilient to node failure, disconnection and capture events, and can help maximize application performance in terms of minimizing false negatives and positives in the presence of mobile nodes exhibiting vastly distinct QoS and social behaviors.

Quantitative Modeling of Trust and Trust Management Protocols in Next Generation Social Networks Based Wireless Mobile Ad Hoc Networks

Trust and Trust Management represent the very foundations of Computer and Network Security Protocols enabling all cyber activities. Recent spate of national and global high-impact Cyber Security compromises, threats, vulnerabilities, and exposures leads to fundamental questioning of Trust as the key enabler of all cyber phenomena in the unfolding era of exponentially increasing Distrust. It is therefore necessary to understand the current state of Trust and Trust Management modeling and implementation in the most high security environments such as in Defense & Space. Such understanding can serve as a foundation for modeling, design, and implementation of next generation mobile wireless networks for other high security environments such as in Banking & Finance. This study attempts to understand how Trust and Trust Management are being modeled for the “next generation wireless communication systems” (NIST) such as autonomous self-discovering, self-organizing, and self-adaptive mobile ad hoc networks. Within the context of Network-Centric Operations (NCO), we examine: (i) the capabilities of next generation wireless mobile ad hoc networks; (ii) how trust and trust management are modeled in such mobile ad hoc networks; and, (iii) how trust and trust management are implemented in trust-based task assignment in tactical networks. US Army Research Lab (ARL) Computational and Information Sciences Directorate’s Network Science research program on wireless mobile ad hoc networks is the focus of our case study.

An Efficient Trust Management Technique for Delay Tolerant Network

Delay Tolerant Networks (DTNs) have high end-to-end latency, which is often faces disconnection, and unreliable wireless connections. It does not mean a delay service instead DTNs provides a service where network imposes disruption or delay. It operates in challenged networks with extremely limited resources such as memory size, CPU processing power etc. This paper presents an efficient trust managing mechanism for providing secure environment. The proposed dynamic trust management protocol uses a dynamic threshold updating which overcomes the problems with time changing dynamic characteristics by dynamically updating the criteria in response to changing network conditions. This reduces overheads and increases the efficient use of routing network even in conditions change. Also the dynamic threshold update reduces the false detection probability of the malicious nodes. To show the effectiveness of the proposed system, a detailed simulation in the presence of selfish and malicious nodes is performed with ONE simulator. Finally a comparative analysis of our proposed routing with previous routing protocols is also performed. The results demonstrate that presented algorithm deals effectively with selfish behavior with providing significant gain on effective delivery ratio in trade off with message overhead and delay.

Dynamic Trust Management for Delay Tolerant Networks and Its Application to Secure Routing

Delay tolerant networks (DTNs) are characterized by high end-to-end latency, frequent disconnection, and opportunistic communication over unreliable wireless links. In this paper, we design and validate a dynamic trust management protocol for secure routing optimization in DTN environments in the presence of well-behaved, selfish and malicious nodes. We develop a novel model-based methodology for the analysis of our trust protocol and validate it via extensive simulation. Moreover, we address dynamic trust management, i.e., determining and applying the best operational settings at runtime in response to dynamically changing network conditions to minimize trust bias and to maximize the routing application performance. We perform a comparative analysis of our proposed routing protocol against Bayesian trust-based and non-trust based (PROPHET and epidemic) routing protocols. The results demonstrate that our protocol is able to deal with selfish behaviors and is resilient against trust-related attacks. Furthermore, our trust-based routing protocol can effectively trade off message overhead and message delay for a significant gain in delivery ratio. Our trust-based routing protocol operating under identified best settings outperforms Bayesian trust-based routing and PROPHET, and approaches the ideal performance of epidemic routing in delivery ratio and message delay without incurring high message or protocol maintenance overhead.

Trust management in mobile ad hoc networks for bias minimization and application performance maximization

Trust management for mobile ad hoc networks (MANETs) has emerged as an active research area as evidenced by the proliferation of trust/reputation protocols to support mobile group based applications in recent years. In this paper we address the performance issue of trust management protocol design for MANETs in two important areas: trust bias minimization and application performance maximization. By means of a novel model-based approach to model the ground truth status of mobile nodes in MANETs as the basis for design validation, we identify and validate the best trust protocol settings under which trust bias is minimized and application performance is maximized. We demonstrate the effectiveness of our approach with an integrated social and quality-of-service (QoS) trust protocol (called SQTrust) with which we identify the best trust aggregation setting under which trust bias is minimized despite the presence of malicious nodes performing slandering attacks. Furthermore, using a mission-oriented mobile group utilizing SQTrust, we identity the best trust formation protocol setting under which the application performance in terms of the system reliability of the mission-oriented mobile group is maximized.