Trusted Computing Research Articles

Public Trust in Computing: Analyzing Trust and Digital Technologies with the Constitutionalism Framework


 
 
 This paper engages the issue of trust in contemporary societies, where data and computing are a defining condition of public life, with the framework of constitutionalism from the field of Science, Technology and Society. The framework of constitutionalism, extending and generalizing from Sheila Jasanoff’s original formulation of “bioconstitutionalism,” says that transformations to understandings of what it means to be human in the age of ubiquitous computing require rethinking of law at the constitutional level – at the level of the most basic relations between states and citizens. These refashionings of the human, however, take place on terrain already steeped in the norms of constitution with a small “c,” that is, the written rules as well as unwritten norms generated by institutional practices that make up the daily hum of a society. The framework draws attention to three aspects of trust in the contemporary sociotechnical condition: 1) trust is not only a narrowly human or social quality separate from the technological systems, but the very condition of the technology’s existence and the specific form that the technology takes; 2) the present day state of trust is the result of a long, gradual, and incomplete process of publics becoming constituted with computing; and 3) trust today is a result and context of “constitutional moments,” moments of rupture in constitutional orders that are the result of interplay between legal, technical, and anthropological factors. These aspects point to sites of intervention that people can activate to shape the current state of trust and they suggest research agendas that scholars of law, society, and technology can pursue to make sense of this crucial area of sociotechnical relations today.
 
 

Emergency Data Transmission Mechanism in VANETs using Improved Restricted Greedy Forwarding (IRGF) Scheme

One of the most critical tasks in Vehicular Ad-hoc Networks (VANETs) is broadcasting Emergency Messages (EMs) at considerable data delivery rates (DDRs). The enhanced spider-web-like Transmission Mechanism for Emergency Data (TMED) is based on request spiders and authenticated spiders to create the shortest route path between the source vehicle and target vehicles. However, the adjacent allocation is based on the DDR only and it is not clear whether each adjacent vehicle is honest or not. Hence, in this article, the Improved Restricted Greedy Forwarding (IRGF) scheme is proposed for adjacent allocation with the help of trust computation in TMED. The trust and reputation score value of each adjacent vehicle is estimated based on successfully broadcast emergency data. The vehicles’ position, velocity, direction, density, and the reputation score, are fed to a fuzzy logic (FL) scheme, which selects the most trusted adjacent node as the forwarding node for broadcasting the EM to the destination vehicles. Finally, the simulation results illustrate the TMED-IRGF model’s efficiency compared to state-of-the-art models in terms of different network metrics.

A dynamic trust management model for vehicular ad hoc networks

Trust management in vehicular ad hoc networks (VANETs) is a challenging dynamic optimization problem due to their decentralized, infrastructureless, and dynamically changing topology. Evolutionary computation (EC) algorithms are good candidates for solving dynamic optimization problems (DOPs), since they are inspired from the biological evolution that is occurred as a result of changes in the environment. In this study, we explore the use of genetic programming (GP) algorithm and evolutionary dynamic optimization (EDO) techniques to build a dynamic trust management model for VANETs. The proposed dynamic trust management model properly evaluates the trustworthiness of vehicles and their messages in the simulation of experimental scenarios including bogus information attacks. The simulation results show that the evolved trust calculation formula prevents the propagation of bogus messages over VANETs successfully and the dynamic trust management model detects changes in the problem and reacts to them in a timely manner. The best evolved formula achieves 89.38% Matthews Correlation Coefficient (MCC), 91.81% detection rate (DR), and 1.01% false positive rate (FPR), when ≈ 5% of the network traffic is malicious. The formula obtains 87.33% MCC, 92.01% DR, and 4.8% FPR when ≈ 40% of the network traffic is malicious, demonstrating its robustness to increasing malicious messages. The proposed model is also run on a real-world traffic model and obtains high MCC and low FPR values. To the best of our knowledge, this is the first application of EC and EDO techniques that generate a trust formula automatically for dynamic trust management in VANETs.

Research on Medical Security System Based on Zero Trust.

With the rapid development of Internet of Things technology, cloud computing, and big data, the combination of medical systems and information technology has become increasingly close. However, the emergence of intelligent medical systems has brought a series of network security threats and hidden dangers, including data leakage and remote attacks, which can directly threaten patients' lives. To ensure the security of medical information systems and expand the application of zero trust in the medical field, we combined the medical system with the zero-trust security system to propose a zero-trust medical security system. In addition, in its dynamic access control module, based on the RBAC model and the calculation of user behavior risk value and trust, an access control model based on subject behavior evaluation under zero-trust conditions (ABEAC) was designed to improve the security of medical equipment and data. Finally, the feasibility of the system is verified through a simulation experiment.

ARAM: A Technology Acceptance Model to Ascertain the Behavioural Intention to Use Augmented Reality

The expansion of augmented reality across society, its availability in mobile platforms and the novelty character it embodies by appearing in a growing number of areas, have raised new questions related to people's predisposition to use this technology in their daily life. Acceptance models, which have been updated following technological breakthroughs and society changes, are known to be great tools for predicting the intention to use a new technological system. This paper proposes a new acceptance model aiming to ascertain the intention to use augmented reality technology in heritage sites-the Augmented Reality Acceptance Model (ARAM). ARAM relies on the use of the Unified Theory of Acceptance and Use of Technology model (UTAUT) model's constructs, namely performance expectancy, effort expectancy, social influence, and facilitating conditions, to which the new and adapted constructs of trust expectancy, technological innovation, computer anxiety and hedonic motivation are added. This model was validated with data gathered from 528 participants. Results confirm ARAM as a reliable tool to determine the acceptance of augmented reality technology for usage in cultural heritage sites. The direct impact of performance expectancy, facilitating conditions and hedonic motivation is validated as having a positive influence on behavioural intention. Trust expectancy and technological innovation are demonstrated to have a positive influence on performance expectancy whereas hedonic motivation is negatively influenced by effort expectancy and by computer anxiety. The research, thus, supports ARAM as a suitable model to ascertain the behavioural intention to use augmented reality in new areas of activity.

Competitor Analysis Using Business Intelligence for Product Innovation

Competitor analysis and product innovation are important requirements for both strategic and operational management. The competitive characteristics of reviewers' comments are used to innovate and improve the product. The primary objective is to develop a comprehensive framework that intelligently learns from competitors’ data and suggests innovative methods to aid the product to become a market leader with the help of artificial intelligence. The goal of this project is to create a model for analyzing and understanding the competitor’s performance, its strengths, weakness, methods through various ways such as competitive attributes from consumers' perspectives, observation of the competitors' adverts etc. This model is expected to help in business decisions, a decision support system is created and help in the innovation of their product. The proposed system consists of the following modules: Trust computation module to compute the amount of trust in a product and its advertisements, Information storage module to store and process the video and image advertisements required efficiently, Video analytics module to derive key information from the filtered videos based on trust score, a Decision support system to make intelligent decisions for determining the multi-objective parameters for product innovation.

Real‐time trust aware scheduling in fog‐cloud systems

SummaryFog computing offers cloud‐like facilities at the network edge, delivering reduced response times to latency sensitive applications. It comprises of fog devices/micro data centers/cloudlets located between users and the cloud data center. Fog devices are generally susceptible to privacy, security, and trust issues. We propose RT‐TADS (Real Time‐Trust Aware Dynamic Scheduling), a scheduling algorithm that accounts for privacy, trust and real‐time performance. To compute the trustworthiness of fog devices, we propose a trust computation model. This model factors in direct and recommended trust techniques for each fog device, and updates their aggregated trust values at regular intervals. User tasks are tagged as: private, semi‐private, and public. Fog devices are classified as: extremely highly trusted, highly trusted, normal trusted, low trusted, and untrusted. RT‐TADS maps the input jobs according to their privacy constraints on trustworthy fog devices, which increases the overall Success Ratio, hence improving real‐time performance. Using the Bitbrain dataset, the real‐time performance of RT‐TADS has been demonstrated, versus comparable algorithms. The results indicate that the proposed RT‐TADS offers an average improvement of 13%, 45%, and 71% in task success ratio compared to RLTCM, no‐trust, and cdc‐only respectively.

The Data Security and multi-cloud Privacy concerns

The security, privacy, and challenges of establishing trust in cloud computing are examined in this paper. It discusses the issues that must be resolved to guarantee the security, privacy, and reliability of data processed, stored, and shared in cloud architecture. Cloud computing is a rapidly growing field, with more and more individuals and organizations adopting it as their preferred data storage and processing method. However, with this growth comes the need for increased attention to privacy, security, and trust in cloud computing. In this paper, we review the current state of privacy, security, and trust in cloud computing and examine the various strategies and technologies being used to address these concerns. We discuss the importance of end-to-end encryption, strong access controls, and data anonymization techniques in protecting user data in the cloud. Additionally, we analyze the role of trusted third parties, such as auditors and certifications, in ensuring the integrity of cloud services. Finally, we consider the impact of emerging technologies, such as blockchain and homomorphic encryption, on the future of privacy, security, and trust in cloud computing. Overall, our analysis highlights the need for ongoing research and development in this area to ensure that cloud computing remains a secure and trustworthy platform for users.

A Semi-Centralized Trust Management Model Based on Blockchain for Data Exchange in IoT System

IoT data exchange plays a vital role in supporting various applications and services with massive IoT devices. However, the existence of malicious devices threatens the integrity and reliability of the exchanged data. Trust management has been used to mitigate the impact of malicious devices in centralized and decentralized architectures. However, most of these traditional trust management systems bear computation, storage, and communication challenges. In this study, we propose a semi-centralized trust management system architecture based on blockchain in both single and multiple domains. The IoT devices are centralized organized by cloud servers who coordinately sustain a rating data ledger within each domain based the proposed rotation based consensus protocol in a decentralized manner to support cross-domain data exchange. A computational trust model is proposed by aggregating the direct and indirect trust information, where we elaborately design decay function, recommendation credibility and adaptable weights so as to calculate the trust value of dynamic malicious devices. Finally, we evaluate the proposed system model in various situations through simulation based experiments and compare it with two classical models in the literature. The experimental results demonstrate the effectiveness of the proposed trust model in identifying malicious devices and mitigating the influence of malicious devices.

LightTrust: Lightweight Trust Management for Edge Devices in Industrial Internet of Things

The phenomenal increase in the usage of Internet promotes the quality of trust in the scope of the Internet of Things (IoT). Trust is beneficial in the provision of an effective, reliable, scalable, and trustworthy environment to users of the IoT network, where they can share their private information with each other on a secure communication platform. For successful communications among the Internet users, trust is an important factor to provide them with private infrastructures and secure environments, where exchanging data among devices becomes more easy and trustworthy. Therefore, trust management is a backbone for the successful and secure transmission of data among various nodes in a large-scale IoT network. To overcome the security issues, latency, and risk of malicious activities, a lightweight approach is proposed for those nodes in Industrial IoT that cannot maintain security. LightTrust utilizes a centralized trust agent to generate and manage trust certificates that allow nodes to communicate for a specific time without performing trust computations. Trust agents also maintain a trust database to store the current trust degree for the aggregation/propagation purposes. Trust between two nodes is developed by direct observations in terms of compatibility, cooperativeness, and delivery ratio, whereas recommendations are used to develop trust in the context of indirect observations, i.e., experience or previous knowledge. The comparative simulations of the proposed and existing approaches are also performed whereby the results illustrate that the proposed approach efficiently maintains resilience and robust environments.

Trustable Body Area Network for Emergency Response

In the medical field, Wireless Body Area Networks (WBAN) play the main role in keeping users healthy by offering convenient services for doctors and patients. However, the attacker is prevented from tampering with the sensor data by communicating through an unsecured channel, which prevents the forwarded packets from their hazardous origins. Several methods of safe authentication are suggested for bolstering the trustworthiness of the channels of communication in protecting user data. A Trustable Body Area Network (TBAN) for Emergency Response approach to protect the medical sensor nodes from untrusted nodes and increase efficiency. Simple trust and compound trust computations are used to isolate untrustable nodes. In addition, this system applies a hash-based signature with a onetime password to confirm the second-level sensor node authentication in the WBAN. The simulation result demonstrates that the proposed system detects the untrustable sensor node efficiently and reduces the network delay.

Speciesism and Preference of Human–Artificial Intelligence Interaction: A Study on Medical Artificial Intelligence

Artificial intelligence (AI) has revolutionized the medical industry in the decade. It is critical to integrate human–computer interaction into daily clinic service and further increase the public acceptance of medical AI. Based on self-categorization theory, our research draws on speciesism as a vital cognitive factor to examine how patients’ speciesism affects their acceptance of medical AI in different roles. The study adopted a positivist research paradigm by examining 249 samples of data collected during COVID-19 in China. The results indicate that patients with higher speciesism tend to have lower acceptance of medical AI in an independent role but higher acceptance in an assistive role. Furthermore, we verified the mediating effect of human–computer trust and the positive moderating role of human uniqueness perception. This article expands the practicality of speciesism from human–animal relationships into human–AI relationships and contributes to human–computer interaction from the perspective of medical AI acceptance.

Trust Management Methodology and Agents Simulations Framework for Conflict Research

AbstractTrust plays a pivotal role in numerous humans’ interactions, and it affects relationships ranging from individuals to interstate levels. Any conflict and its resolution can therefore benefit from insights into trust dynamics. The deployment of computational trust management methods and agent technologies provide promising options. They have already been successfully applied in many domains, while in conflict research (and possible resolution policies) they are rather unexplored. This research paper therefore presents an approach that is based on a formalized, anthropocentric trust management method. It deploys it accordingly in agents’ simulations to obtain new insights into the dynamics of trust in cooperation–conflict interplay, and to enable derivation of strategies for managing societies to drive them toward desired states.

A dynamic Bayesian-based comprehensive trust evaluation model for dispersed computing environment

Dispersed computing is a new resource-centric computing paradigm. Due to its high degree of openness and decentralization, it is vulnerable to attacks, and security issues have become an important challenge hindering its development. The trust evaluation technology is of great significance to the reliable operation and security assurance of dispersed computing networks. In this paper, a dynamic Bayesian-based comprehensive trust evaluation model is proposed for dispersed computing environment. Specifically, in the calculation of direct trust, a logarithmic decay function and a sliding window are introduced to improve the timeliness. In the calculation of indirect trust, a random screening method based on sine function is designed, which excludes malicious nodes providing false reports and multiple malicious nodes colluding attacks. Finally, the comprehensive trust value is dynamically updated based on historical interactions, current interactions and momentary changes. Simulation experiments are introduced to verify the performance of the model. Compared with existing model, the proposed trust evaluation model performs better in terms of the detection rate of malicious nodes, the interaction success rate, and the computational cost.

Controversy-Adjudication-Based Trust Management Mechanism in the Internet of Underwater Things

Owing to the characteristics of underwater communication, such as limited bandwidth, low transmission speed, and long delivery delay, it is significantly challenging to address trust management in the Internet of Underwater Things (IoUT). In the process of trust calculation, trust judgments between nodes may be conflicting based on the obtained diverse trust evidences. However, in existing studies, the analysis of trust-conflict adjudication is nonexhaustive and lacking in detail. Therefore, a controversy-adjudication method is proposed in this study to handle conflict recommendations, and a novel trust management mechanism is further investigated based on the controversy-adjudication method, including three phases: 1) trust calculation; 2) trust recommendation; and 3) trust evaluation. First, trust evidences, e.g., packet delivery ratio, end-to-end packet transmission latency, and residual energy, are collected to calculate trust for trustees. In addition, for the trustor without sufficient trust evidences, recommendations are required and an incentive mechanism is proposed based on the prisoner’s dilemma to encourage neighbors to participate in trust recommendation. Finally, trust values of trustees are obtained by executing trust evaluation based on the controversy-adjudication mechanism. Simulation results demonstrate that the proposed trust management mechanism outperforms existing related works in terms of accuracy and robustness against unreliable IoUT.

A systematic study on the challenges, characteristics and security issues in vehicular networks

PurposeThe purpose of this study is to extensively explore the vehicular network paradigm, challenges faced by them and provide a reasonable solution for securing these vulnerable networks. Vehicle-to-everything (V2X) communication has brought the long-anticipated goal of safe, convenient and sustainable transportation closer to reality. The connected vehicle (CV) paradigm is critical to the intelligent transportation systems vision. It imagines a society free of a troublesome transportation system burdened by gridlock, fatal accidents and a polluted environment. The authors cannot overstate the importance of CVs in solving long-standing mobility issues and making travel safer and more convenient. It is high time to explore vehicular networks in detail to suggest solutions to the challenges encountered by these highly dynamic networks.Design/methodology/approachThis paper compiles research on various V2X topics, from a comprehensive overview of V2X networks to their unique characteristics and challenges. In doing so, the authors identify multiple issues encountered by V2X communication networks due to their open communication nature and high mobility, especially from a security perspective. Thus, this paper proposes a trust-based model to secure vehicular networks. The proposed approach uses the communicating nodes’ behavior to establish trustworthy relationships. The proposed model only allows trusted nodes to communicate among themselves while isolating malicious nodes to achieve secure communication.FindingsDespite the benefits offered by V2X networks, they have associated challenges. As the number of CVs on the roads increase, so does the attack surface. Connected cars provide numerous safety-critical applications that, if compromised, can result in fatal consequences. While cryptographic mechanisms effectively prevent external attacks, various studies propose trust-based models to complement cryptographic solutions for dealing with internal attacks. While numerous trust-based models have been proposed, there is room for improvement in malicious node detection and complexity. Optimizing the number of nodes considered in trust calculation can reduce the complexity of state-of-the-art solutions. The theoretical analysis of the proposed model exhibits an improvement in trust calculation, better malicious node detection and fewer computations.Originality/valueThe proposed model is the first to add another dimension to trust calculation by incorporating opinions about recommender nodes. The added dimension improves the trust calculation resulting in better performance in thwarting attacks and enhancing security while also reducing the trust calculation complexity.

Trust aware ad hoc routing protocol with key management based mechanism and optimal energy‐efficient cluster head selection in mobile ad hoc networks

SummaryThe implementation of Mobile Ad hoc Networks in numerous domains is necessitated by the fast evolving wireless service requirements as well as deployment demands over the last few decades. The application areas are environmental monitoring, disaster rescue operations, military communications, and other safety‐critical sectors. The underlying routing protocol has a considerable impact on the effectiveness of an ad hoc network deployment in a specific situation. MANETs are vulnerable to major security risks that are difficult to combat with current security measures. As a result, several safe routing protocols have been created to improve MANET security. This work proposes a safe and energy‐efficient routing mechanism using group key management. Initially, Particle Swarm Optimization (PSO) was adopted for efficient selection of cluster heads and malicious node detection, which aims to establish the trust among connected nodes that can enhance security as every participating node will produce as well as propagate authentic, accurate, and trusted content within the network. Two specialized nodes, dubbed Calculator Key (CK) and Distribution Key (DK), are then responsible for producing, verifying, and distributing secret keys among nodes employing Asymmetric key cryptography. The proposed method is named Optimal Cluster_ Trust Asymmetric Key Management Protocol (OptCH_TAKMP), which is considered an excellent energy‐efficient cluster head election process with a securable routing mechanism. It is compared with three state‐of‐art methods. Simulation results show that proposed OptCH_TAKMP achieves 31.4% of routing overhead, 23% of end‐to‐end delay, 78.6% of energy efficiency, 94.8% of throughput, 28.2% of average latency, 91.4% of malicious detection rate, and 92.4% of packet delivery ratio, 85.2% of network lifetime, 19.2% of communication cost and 28.6% of trust computation error.

Mitigating Software Integrity Attacks With Trusted Computing in a Time Distribution Network

Time Distribution Networks (TDNs) evolve as new technologies occur to ensure more accurate, reliable, and secure timing information. These networks typically exploit several distributed time servers, organized in a master-slave architecture, that communicate via dedicated timing protocols. From the security perspective, timing data must be protected since its modification or filtering can lead to grave consequences in different time-based contexts, such as health, energy, finance, or transportation. Thus, adequate countermeasures must be employed in all the stages and systems handling timing data from its calculation until it reaches the final users. We consider a TDN offering highly accurate (nanosecond level) time synchronization through specific time unit devices that exploit terrestrial atomic or rubidium clocks and Global Navigation Satellite Systems (GNSS) receivers. Such devices are appealing targets for attackers, who might exploit various attack vectors to compromise their functionality. We individuate three possible software integrity attacks against time devices, and we propose a solution to counter them by exploiting the cryptographic Trusted Platform Module (TPM), defined and supported by the Trusted Computing Group. We used remote attestation software for cloud environments, namely the Keylime framework, to verify (periodically) the software daemons running on the time devices (or their configuration) from a trusted node. Experiments performed on a dedicated testbed set up in the ROOT project with customized time unit devices from Seven Solutions (currently Orolia Spain) allow us to demonstrate that exploiting TPMs and remote attestation in the TDNs is not only helpful but is fundamental for discovering some attacks that would remain otherwise undetected. Our work helps thus TDN operators build more robust, accurate, and secure time synchronization services.

Energy Based Random Repeat Trust Computation in Delay Tolerant Network

As the use of mobile devices continues to rise, trust administration will significantly improve security in routing the guaranteed quality of service (QoS) supply in Mobile Ad Hoc Networks (MANET) due to the mobility of the nodes. There is no continuance of network communication between nodes in a delay-tolerant network (DTN). DTN is designed to complete recurring connections between nodes. This approach proposes a dynamic source routing protocol (DSR) based on a feed-forward neural network (FFNN) and energy-based random repetition trust calculation in DTN. If another node is looking for a node that swerved off of its path in this situation, routing will fail since it won’t recognize it. However, in the suggested strategy, nodes do not stray from their pathways for routing. It is only likely that the message will reach the destination node if the nodes encounter their destination or an appropriate transitional node on their default mobility route, based on their pattern of mobility. The EBRRTC-DTN algorithm (Energy based random repeat trust computation) is based on the time that has passed since nodes last encountered the destination node. Compared to other existing techniques, simulation results show that this process makes the best decision and expertly determines the best and most appropriate route to send messages to the destination node, which improves routing performance, increases the number of delivered messages, and decreases delivery delay. Therefore, the suggested method is better at providing better QoS (Quality of Service) and increasing network lifetime, tolerating network system latency.

TABI: Trust-Based ABAC Mechanism for Edge-IoT Using Blockchain Technology

Recent research has focused on applying blockchain technology to solve security-related problems in Internet of Things (IoT) networks. However, implementing blockchain technology directly on IoT networks is prone to high overheads and energy-expensive operations. Therefore, in this paper, we use edge computing technology to avoid these problems. We also propose a novel Trust-based Access Control Mechanism for Edge-IoT Networks using Blockchain technology (named TABI) to implement end-to-end security in resource-constrained IoT networks. The TABI mechanism utilizes both access control and trust evaluation mechanisms to mitigate the impact of malicious IoT users and devices. Additionally, it incorporates permissioned Hyperledger blockchain technology to provide an added layer of security through authentication. The trust evaluation mechanism is implemented as a trust calculation contract (TCC) on the edge devices using Hyperledger Composer. The access control mechanism employs an Attribute-based Access Control (ABAC) mechanism, which is implemented on the Hyperledger blockchain using two smart contracts: the attribute contract (AC) and the access control contract (ACC). We implement a proof-of-concept (PoC) implementation using Hyperledger Caliper (a benchmark testing tool) and Docker images. Our evaluation includes five analyses: Trust Evaluation Mechanism, Access Control Mechanism, Security, Blockchain, and IoT Applications. Through this evaluation, we highlight the effectiveness of TABI in terms of throughput, latency, detection of malicious IoT devices, and resource consumption of the IoT devices. Our analyses demonstrate that TABI is particularly useful in IoT applications that require low latency and resource efficiency.