Biblio

This work expands on our prior work on an architecture and supporting protocols to efficiently integrate constrained devices into an Information-Centric Network-based Internet of Things in a way that is both secure and scalable. In this work, we propose a scheme for addressing additional threats and integrating trust-based behavioral observations and attribute-based access control by leveraging the capabilities of less constrained coordinating nodes at the network edge close to IoT devices. These coordinating devices have better insight into the behavior of their constituent devices and access to a trusted overall security management cloud service. We leverage two modules, the security manager (SM) and trust manager (TM). The former provides data confidentiality, integrity, authentication, and authorization, while the latter analyzes the nodes' behavior using a trust model factoring in a set of service and network communication attributes. The trust model allows trust to be integrated into the SM's access control policies, allowing access to resources to be restricted to trusted nodes.

Unmanned aerial vehicles (UAVs) and various network entities deployed on the ground can communicate with each other over the Internet of Drones (IoD), a network architecture designed expressly to allow communications between heterogenous entities. Drone technology has a wide range of uses, including on-demand package delivery, traffic and wild life surveillance, inspection of infrastructure and search, rescue and agriculture. However, IoD systems are vulnerable to numerous attacks, The main goal is to develop an all-encompassing security model that can be used to analyze security concerns in various UAV-based systems. With exceptional flexibility and increasing efficiency, trust management is a promising alternative to traditional detection methods. In a heterogeneous environment, it is also compatible with other security mechanisms. In this article, we present a fuzzy logic as an Insider Detection technique which calculate sensor data trust and assessing node behavior. To build confidence throughout the entire IoD, our proposal divides trust into two parts: Data trust and Node trust. This is in contrast to earlier models. Experimental results show that our solution is effective in terms of False positive ratio and Average of end-to-end delay.

The fast-evolving Intelligent Transportation Systems (ITS) are crucial in the 21st century, promising answers to congestion and accidents that bother people worldwide. ITS applications such as Connected and Autonomous Vehicle (CAVs) update and broadcasts road incident event messages, and this requires significant data to be transmitted between vehicles for a decision to be made in real-time. However, broadcasting trusted incident messages such as accident alerts between vehicles pose a challenge for CAVs. Most of the existing-trust solutions are based on the vehicle's direct interaction base reputation and the psychological approaches to evaluate the trustworthiness of the received messages. This paper provides a scheme for improving trust in the received incident alert messages for real-time decision-making to detect malicious alerts between CAVs using direct and indirect interactions. This paper applies artificial intelligence and statistical data classification for decision-making on the received messages. The model is trained based on the US Department of Technology Safety Pilot Deployment Model (SPMD). An Autonomous Decision-making Trust Scheme (ADmTS) that incorporates a machine learning algorithm and a local trust manager for decision-making has been developed. The experiment showed that the trained model could make correct predictions such as 98% and 0.55% standard deviation accuracy in predicting false alerts on the 25% malicious data

Cooperative Intelligent Transportation System (CITS) has been introduced recently to increase road safety, traffic efficiency, and to enable various infotainment and comfort applications and services. To this end, a bunch technologies have been deployed to maintain and promote ITS. In essence, ITS is composed of vehicles, roadside infrastructure, and the environment that includes pedestrians, and other entities. Recently, several solutions were suggested to handle with the challenges faced by the vehicular networks (VN) using future internet architectures. One of the promising solutions proposed recently is Vehicular Fog computing (VFC), an attractive solution that supports sensitive service requests considering factors such as latency, mobility, localization, and scalability. VFC also provides a virtual platform for real-time big data analytic using servers or vehicles as a fog infrastructure. This paper surveys the general fog computing (FC) concept, the VFC architectures, and the key characteristics of several intelligent computing applications. We mainly focus on trust and security challenges in VFC deployment and real-time BD analytic in vehicular environment. We identify the faced challenges and future research directions in VFC and we highlight the research gap that can be exploited by researchers and vehicular manufactures while designing a new secure VFC architecture.

The vast proliferation of the connected devices makes the operation of the traditional networks so complex and drops the network performance, particularly, failure cases. In fact, a novel solution is proposed to enable the management of the network resources and services named software defined network (SDN). SDN splits the data plane and the control plane by centralizing all the control plane on one common platform. Further, SDN makes the control plane programmable by offering high flexibility for the network management and monitoring mostly in failure cases. However, the main challenge in SDN is security that is presented as the first barrier for its development. Security in SDN is presented at various levels and forms, particularly, the communication between the data plane and control plane that presents a weak point in SDN framework. In this article, we suggest a new security framework focused on the combination between the trust and awareness concepts (TAS-SDN) for a dynamic southbound communication SDN. Further, TAS-SDN uses trust levels to establish a secure communication between the control plane and data plane. As a result, we discuss the implementation and the performance of TAS-SDN which presents a promote security solution in terms of time execution, complexity and scalability for SDN.

This study purpose was to examine the determinant factors that affect the Micro, Small, and Medium Enterprise (MSME) merchants who had the intention to use Quick Response Code Indonesian Standard (QRIS) as a payment system. QRIS was expected to be applied by merchants to diminish the virus spread and keep the circulation of money safe; but there were not many merchants using the QRIS as a payment method. The factors MSME merchant might not use the QRIS were related to perceived usefulness, perceived security, perceived ease of use, and trust. The population was MSMEs in South Tangerang City who did not use QRIS yet and the population was unknown. Using the Lemeshow formula, obtained a sample of 115 people, and the sampling technique used purposive sampling. Then data were analyzed using multi-regression analysis and processed by SPSS. The results indicated that perceived usefulness and perceived security had a significant affect on trust, whereas trust and ease of use significant affect the intention to use QRIS. Moreover, trust was able to mediate the perceived usefulness to intention to use. Since ease of use had no significant affect on trust, then the mediation given by trust to perceived ease of use had no significant affect on intention to use.

The success of human-robot interaction is strongly affected by the people’s ability to infer others’ intentions and behaviours, and the level of people’s trust that others will abide by their same principles and social conventions to achieve a common goal. The ability of understanding and reasoning about other agents’ mental states is known as Theory of Mind (ToM). ToM and trust, therefore, are key factors in the positive outcome of human-robot interaction. We believe that a robot endowed with a ToM is able to gain people’s trust, even when this may occasionally make errors.In this work, we present a user study in the field in which participants (N=123) interacted with a robot that may or may not have a ToM, and may or may not exhibit erroneous behaviour. Our findings indicate that a robot with ToM is perceived as more reliable, and they trusted it more than a robot without a ToM even when the robot made errors. Finally, ToM results to be a key driver for tuning people’s trust in the robot even when the initial condition of the interaction changed (i.e., loss and regain of trust in a longer relationship).

As autonomous service robots will become increasingly ubiquitous in our daily lives, human-robot conflicts will become more likely when humans and robots share the same spaces and resources. This thesis investigates the conflict resolution of robots and humans in everyday conflicts in the domestic and public context. Hereby, the acceptability, trustworthiness, and effectiveness of verbal and non-verbal strategies for the robot to solve the conflict in its favor are evaluated. Based on the assumption of the Media Equation and CASA paradigm that people interact with computers as social actors, robot conflict resolution strategies from social psychology and human-machine interaction were derived. The effectiveness, acceptability, and trustworthiness of those strategies were evaluated in online, virtual reality, and laboratory experiments. Future work includes determining the psychological processes of human-robot conflict resolution in further experimental studies.

For designing the interaction with robots in healthcare scenarios, understanding how trust develops in such situations characterized by vulnerability and uncertainty is important. The goal of this study was to investigate how technology-related user dispositions, anxiety, and robot characteristics influence trust. A second goal was to substantiate the association between hospital patients' trust and their intention to use a transport robot. In an online study, patients, who were currently treated in hospitals, were introduced to the concept of a transport robot with both written and video-based material. Participants evaluated the robot several times. Technology-related user dispositions were found to be essentially associated with trust and the intention to use. Furthermore, hospital patients' anxiety was negatively associated with the intention to use. This relationship was mediated by trust. Moreover, no effects of the manipulated robot characteristics were found. In conclusion, for a successful implementation of robots in hospital settings patients' individual prior learning history - e.g., in terms of existing robot attitudes - and anxiety levels should be considered during the introduction and implementation phase.

Trust is a cognitive ability that can be dependent on behavioral consistency. In this paper, a partially observable Markov Decision Process (POMDP)-based computational robot-human trust model is proposed for hand-over tasks in human-robot collaborative contexts. The robot's trust in its human partner is evaluated based on the human behavior estimates and object detection during the hand-over task. The human-robot hand-over process is parameterized as a partially observable Markov Decision Process. The proposed approach is verified in real-world human-robot collaborative tasks. Results show that our approach can be successfully applied to human-robot hand-over tasks to achieve high efficiency, reduce redundant robot movements, and realize predictability and mutual understanding of the task.

In this study, the nature of human trust in communication robots was experimentally investigated comparing with trusts in other people and artificial intelligence (AI) systems. The results of the experiment showed that trust in robots is basically similar to that in AI systems in a calculation task where a single solution can be obtained and is partly similar to that in other people in an emotion recognition task where multiple interpretations can be acceptable. This study will contribute to designing a smooth interaction between people and communication robots.

The blockchain network is often considered a reliable and secure network. However, some security attacks, such as eclipse attacks, have a significant impact on blockchain networks. In order to perform an eclipse attack, the attacker must be able to control enough IP addresses. This type of attack can be mitigated by blocking incoming connections. Connected machines may only establish outbound connections to machines they trust, such as those on a whitelist that other network peers maintain. However, this technique is not scalable since the solution does not allow nodes with new incoming communications to join the network. In this paper, we propose a scalable and secure trust-based solution against eclipse attacks with a peer-selection strategy that minimizes the probability of eclipse attacks from nodes in the network by developing a trust point. Finally, we experimentally analyze the proposed solution by creating a network simulation environment. The analysis results show that the proposed solution reduces the probability of an eclipse attack and has a success rate of over 97%.

Security in the communication systems rely mainly on a trusted Public Key Infrastructure (PKI) and Certificate Authorities (CAs). Besides the lack of automation, the complexity and the cost of assigning a signed certificate to a device, several allegations against CAs have been discovered, which has created trust issues in adopting this standard model for secure systems. The automation of the servers certificate assignment was achieved by the Automated Certificate Management Environment (ACME) method, but without confirming the trust of assigned certificate. This paper presents a complete tested and implemented solution to solve the trust of the Certificates provided to the servers by using the blockchain platform for certificate validation. The Blockchain network provides an immutable data store, holding the public keys of all domain names, while resolving the trust concerns by applying an automated Blockchain-based Domain Control Validation (B-DCV) for the server and client server verification. The evaluation was performed on the Ethereum Rinkeby testnet adopting the Proof of Authority (PoA) consensus algorithm which is an improved version of Proof of Stake (Po \$S\$) applied on Ethereum 2.0 providing superior performance compared to Ethereum 1.0.

Open Source Software plays an important role in many software ecosystems. Whether in operating systems, network stacks, or as low-level system drivers, software we encounter daily is permeated with code contributions from open source projects. Decentralized development and open collaboration in open source projects introduce unique challenges: code submissions from unknown entities, limited personpower for commit or dependency reviews, and bringing new contributors up-to-date in projects’ best practices & processes.In 27 in-depth, semi-structured interviews with owners, maintainers, and contributors from a diverse set of open source projects, we investigate their security and trust practices. For this, we explore projects’ behind-the-scene processes, provided guidance & policies, as well as incident handling & encountered challenges. We find that our participants’ projects are highly diverse both in deployed security measures and trust processes, as well as their underlying motivations. Based on our findings, we discuss implications for the open source software ecosystem and how the research community can better support open source projects in trust and security considerations. Overall, we argue for supporting open source projects in ways that consider their individual strengths and limitations, especially in the case of smaller projects with low contributor numbers and limited access to resources.

The Sixth Generation (6G) is currently under development and it is a planned successor of the Fifth Generation (5G). It is a new wireless communication technology expected to have a greater coverage area, significant fast and a higher data rate. The aim of this paper is to examine the literature on challenges and possible solutions of 6G's security, privacy and trust. It uses the systematic literature review technique by searching five research databases for search engines which are precise keywords like “6G,” “6G Wireless communication,” and “sixth generation”. The latter produced a total of 1856 papers, then the security, privacy and trust issues of the 6G wireless communication were extracted. Two security issues, the artificial intelligence and visible light communication, were apparent. In conclusion, there is a need for new paradigms that will provide a clear 6G security solutions.

This short paper argues that current conceptions in trust formation scholarship miss the context of zero trust, a practice growing in importance in cyber security. The contribution of this paper presents a novel approach to help conceptualize and operationalize zero trust and a call for a research agenda. Further work will expand this model and explore the implications of zero trust in future digital systems.

The user's access history can be used as an important reference factor in determining whether to allow the current access request or not. And it is often ignored by the existing access control models. To make up for this defect, a Dynamic Trust - game theoretic Access Control model is proposed based on the previous work. This paper proposes a method to quantify the user's trust in the cloud environment, which uses identity trust, behavior trust, and reputation trust as metrics. By modeling the access process as a game and introducing the user's trust value into the pay-off matrix, the mixed strategy Nash equilibrium of cloud user and service provider is calculated respectively. Further, a calculation method for the threshold predefined by the service provider is proposed. Authorization of the access request depends on the comparison of the calculated probability of the user's adopting a malicious access policy with the threshold. Finally, we summarize this paper and make a prospect for future work.

The promise of access to contextual expertise, advanced security tools and an increase in staff augmentation coupled with reduced computing costs has indisputably made cloud computing a computing platform of choice, so enticing that many organizations had to migrate some if not all their services to the cloud. Identity-management-as-a-service (IdMaaS), however, is still struggling to mature due to lack of trust. Lack of trust arises from losing control over the identity information (user credentials), identity management system as well as the underlying infrastructure, raising a fear of loss of confidentiality, integrity and availability of both the identities and the identity management system. This paper recognizes the need for a trust framework comprising of both the operational and technical Frameworks as a holistic approach towards enhancing trust in IdMaaS. To this end however, only the operational Framework will form the core of this paper. The success of IdMaaS will add to the suite of other matured identity management technologies, spoiling the would-be identity service consumers with a wide choice of identity management paradigms to pick from, at the same time opening entrepreneurial opportunities to cloud players.

Conversational agents (CAs) have been widely adopted for various purposes, ranging from personal assistants to health information providers. While the research on CAs is growing rapidly, less attention is paid to CAs in virtual reality (VR) environments with respect to how the design of these agents influences their trustworthiness as perceived by users, which is key to the adoption and use of VR products featuring CAs. Accordingly, this position paper conceptualizes an immersive model of user trust in CAs in VR. The model is centered around users’ sense of co-presence with CAs in VR, which is influenced by the agents’ embodiment, expressiveness, and responsiveness.

Due to the shortage of resources and services, agents are often in competition with each other. Excessive competition will lead to a social dilemma. Under the viewpoint of breaking social dilemma, we present a novel trust-based logic framework called Trust Computation Logic (TCL) for measure method to find the best partners to collaborate and automatically verifying trust in Multi-Agent Systems (MASs). TCL starts from defining trust state in Multi-Agent Systems, which is based on contradistinction between behavior in trust behavior library and in observation. In particular, a set of reasoning postulates along with formal proofs were put forward to support our measure process. Moreover, we introduce symbolic model checking algorithms to formally and automatically verify the system. Finally, the trust measure method and reported experimental results were evaluated by using DeepMind’s Sequential Social Dilemma (SSD) multi-agent game-theoretic environments.

Privacy and data security are critical aspects in databases, mainly when the latter are publically accessed such in social networks. Furthermore, for advanced databases, such as NoSQL ones, security models and security meta-data must be integrated to the business specification and data. In the literature, the proposed models for NoSQL databases can be considered as static, in the sense where the privileges for a given user are predefined and remain unchanged during job sessions. In this paper, we propose a novel model for NoSQL database access control that we aim that it will be dynamic. To be able to design such model, we have considered the Trust concept to compute the reputation degree for a given user that plays a given role.

The main technology of traditional information security is firewall, intrusion detection and anti-virus software, which is used in the first anti-outer defence, the first anti-service terminal defence terminal passive defence ideas, the complexity and complexity of these security technologies not only increase the complexity of the autonomous system, reduce the efficiency of the system, but also cannot solve the security problem of the information system, and cannot satisfy the security demand of the information system. After a significant stretch of innovative work, individuals utilize the secret word innovation, network security innovation, set forward the idea “confided in figuring” in view of the equipment security module support, Trusted processing from changing the customary protection thoughts, center around the safety efforts taken from the terminal to forestall framework assaults, from the foundation of the stage, the acknowledgment of the security of data frameworks. Believed figuring is chiefly worried about the security of the framework terminal, utilizing a progression of safety efforts to ensure the protection of clients to work on the security of independent frameworks. Its principle plan thought is implanted in a typical machine to oppose altering the equipment gadget - confided in stage module as the base of the trust, the utilization of equipment and programming innovation to join the trust of the base of trust through the trust bind level to the entire independent framework, joined with the security of information stockpiling insurance, client validation and stage respectability of the three significant safety efforts guarantee that the terminal framework security and unwavering quality, to guarantee that the terminal framework is consistently in a condition of conduct anticipated.

The randomness, ambiguity and some other uncertainties of trust relationships in Wireless Sensor Networks (WSNs) make existing trust management methods often unsatisfactory in terms of accuracy. This paper proposes a trust evaluation method based on cloud model for malicious node detection. The conversion between qualitative and quantitative sensor node trust degree is achieved. Firstly, nodes cooperate with each other to establish a standard cloud template for malicious nodes and a standard cloud template for normal nodes, so that malicious nodes have a qualitative description to be either malicious or normal. Secondly, the trust cloud template obtained during the interactions is matched against the previous standard templates to achieve the detection of malicious nodes. Simulation results demonstrate that the proposed method greatly improves the accuracy of malicious nodes detection.

In order to strengthen information security, practical solutions to reduce information security stress are needed because the motivation of the members of the organization who use it is needed to work properly. Therefore, this study attempts to suggest the key factors that can enhance security while reducing the information security stress of organization members. To this end, based on the theory of protection motivation, trust and security stress in information security policies are set as mediating factors to explain changes in security reinforcement behavior, and risk, efficacy, and reaction costs of cyberattacks are considered as prerequisites. Our study suggests a solution to the security reinforcement problem by analyzing the factors that influence the behavior of organization members that can raise the protection motivation of the organization members.

As a supplement to the cloud computing model, the edge computing model can use edge servers and edge devices to coordinate information processing on the edge of the network to help Internet of Thing (IoT) data storage, transmission, and computing tasks. In view of the complex and changeable situation of edge computing IoT scenarios, this paper proposes a multi-dimensional trust evaluation factor selection scheme. Improve the traditional trusted modeling method based on direct/indirect trust, introduce multi-dimensional trusted decision attributes and rely on the collaboration of edge servers and edge device nodes to infer and quantify the trusted relationship between nodes, and combine the information entropy theory to smoothly weight the calculation results of multi-dimensional decision attributes. Improving the current situation where the traditional trusted assessment scheme's dynamic adaptability to the environment and the lack of reliability of trusted assessment are relatively lacking. Simulation experiments show that the edge computing IoT multi-dimensional trust evaluation model proposed in this paper has better performance than the trusted model in related literature.