Trust-based recommendation systems in Internet of Things: a systematic literature review

Security and Trust Management in the Internet of Vehicles (IoV): Challenges and Machine Learning Solutions

The Internet of Vehicles (IoV) is a technology that is connected to the public internet and is a subnetwork of the Internet of Things (IoT) in which vehicles with sensors are connected to a mobile and wireless network. Numerous vehicles, users, things, and networks allow nodes to communicate information with their surroundings via various communication channels. IoV aims to enhance the comfort of driving, improve energy management, secure data transmission, and prevent road accidents. Despite IoV's advantages, it comes with its own set of challenges, particularly in the highly important aspects of security and trust. Trust management is one of the potential security mechanisms aimed at increasing reliability in IoV environments. Protecting IoV environments from diverse attacks poses significant challenges, prompting researchers to explore various technologies for security solutions and trust evaluation methods. Traditional approaches have been employed, but innovative solutions are imperative. Amid these challenges, machine learning (ML) has emerged as a potent solution, leveraging its remarkable advancements to effectively address IoV's security and trust concerns. ML can potentially be utilized as a powerful technology to address security and trust issues in IoV environments. In this survey, we delve into an overview of IoV and trust management, discussing security requirements, challenges, and attacks. Additionally, we introduce a classification scheme for ML techniques and survey ML-based security and trust management schemes. This research provides an overview for understanding IoV and the potential of ML in improving its security framework. Additionally, it provides insights into the future of trust and security enhancement.

SCBC: Smart city monitoring with blockchain using Internet of Things for and neuro fuzzy procedures

The security of the Internet of Things (IoT) is crucial in various application platforms, such as the smart city monitoring system, which encompasses comprehensive monitoring of various conditions. Therefore, this study conducts an analysis on the utilization of blockchain technology for the purpose of monitoring Internet of Things (IoT) systems. The analysis is carried out by employing parametric objective functions. In the context of the Internet of Things (IoT), it is imperative to establish well-defined intervals for job execution, ensuring that the completion status of each action is promptly monitored and assessed. The major significance of proposed method is to integrate a blockchain technique with neuro-fuzzy algorithm thereby improving the security of data processing units in all smart city applications. As the entire process is carried out with IoT the security of data in both processing and storage units are not secured therefore confidence level of monitoring units are maximized at each state. Due to the integration process the proposed system model is implemented with minimum energy conservation where 93% of tasks are completed with improved security for about 90%.

Provenance-Based Trust-Aware Requirements Engineering Framework for Self-Adaptive Systems

With the development of artificial intelligence technology, systems that can actively adapt to their surroundings and cooperate with other systems have become increasingly important. One of the most important factors to consider during the process of cooperation among systems is trust. Trust is a social concept that assumes that cooperation with an object will produce positive results in the direction we intend. Our objectives are to propose a method for defining trust during the requirements engineering phase in the process of developing self-adaptive systems and to define the trust evidence models required to evaluate the defined trust at runtime. To achieve this objective, we propose in this study a provenance-based trust-aware requirement engineering framework for self-adaptive systems. The framework helps system engineers derive the user's requirements as a trust-aware goal model through analysis of the trust concept in the requirements engineering process. We also propose a provenance-based trust evidence model to evaluate trust and provide a method for defining this model for the target domain. Through the proposed framework, a system engineer can treat trust as a factor emerging from the requirements engineering phase for the self-adaptive system and understand the factors affecting trust using the standardized format.

Computational Model of Recommender System Intervention

A recommender system is an information selection system that offers preferences to users and enhances their decision-making. This system is commonly implemented in human-computer-interaction (HCI) intervention because of its information filtering and personalization. However, its success rate in decision-making intervention is considered low and the rationale for this is associated with users’ psychological reactance which is causing unsuccessful recommender system interventions. This paper employs a computational model to depict factors that lead to recommender system rejection by users and how these factors can be enhanced to achieve successful recommender system interventions. The study made use of design science research methodology by executing a computational analysis based on an agent-based simulation approach for the model development and implementation. A total of sixteen model concepts were identified and formalized which were implemented in a Matlab environment using three major case conditions as suggested in previous studies. The result of the study provides an explicit comprehension on interplaying of recommender system that generate psychological reactance which is of great importance to recommender system developers and designers to depict how successful recommender system interventions can be achieved without users experiencing reactance and rejection on the system.

Approaches and Challenges in Internet of Robotic Things

The Internet of robotic things (IoRT) is the combination of different technologies including cloud computing, robots, Internet of things (IoT), artificial intelligence (AI), and machine learning (ML). IoRT plays a major role in manufacturing, healthcare, security, and transport. IoRT can speed up human development by a very significant percentage. IoRT allows robots to transmit and receive data to and from other devices and users. In this paper, IoRT is reviewed in terms of the related techniques, architectures, and abilities. Consequently, the related research challenges are presented. IoRT architectures are vital in the design of robotic systems and robotic things. The existing 3–7-tier IoRT architectures are studied. Subsequently, a detailed IoRT architecture is proposed. Robotic technologies provide the means to increase the performance and capabilities of the user, product, or process. However, robotic technologies are vulnerable to attacks on data security. Trust-based and encryption-based mechanisms can be used for secure communication among robotic things. A security method is recommended to provide a secure and trustworthy data-sharing mechanism in IoRT. Significant security challenges are also discussed. Several known attacks on ad hoc networks are illustrated. Threat models ensure integrity confidentiality and availability of the data. In a network, trust models are used to boost a system’s security. Trust models and IoRT networks play a key role in obtaining a steady and nonvulnerable configuration in the network. In IoRT, remote server access results in remote software updates of robotic things. To study navigation strategies, navigation using fuzzy logic, probabilistic roadmap algorithms, laser scan matching algorithms, heuristic functions, bumper events, and vision-based navigation techniques are considered. Using the given research challenges, future researchers can get contemporary ideas of IoRT implementation in the real world.

PINE: Post-Quantum Based Incentive Technique for Non-Cooperating Nodes in Internet of Everything

The Internet of Everything (IoE) is a smart system that interconnects smart entities by incorporating low-cost or low-energy gadgets that are useful for communication with people, processes, data, and devices/things. In such an instantaneously connected environment, network-enabled heterogeneous devices may exhibit non-cooperative behaviour which may lead to the degradation of the network. To address this performance degradation, the proposed Post-quantum based Incentive technique for Non-cooperating nodes in internet of Everything (PINE) protocol provides an end-to-end reliable solution by incorporating location-aware post-quantum encryption in these networks while addressing the non-cooperative behaviour of the nodes by employing an effective strategy in a bi-directional multi-hop relay environment. This proposed protocol further aims to evaluate the consequences of non-cooperative nodes by considering various metrics, namely, number of nodes, message size, execution time, memory consumption, average residual energy, percentage of selfish nodes, and blackhole nodes detection, aiming to achieve significant accuracy in an IoE environment.

Trust and Mobility-Based Protocol for Secure Routing in Internet of Things

In the Internet of Things (IoT), the de facto Routing Protocol for Low Power and Lossy Networks (RPL) is susceptible to several disruptive attacks based on its functionalities and features. Among various RPL security solutions, a trust-based security is easy to adapt for resource-constrained IoT environments. In the existing trust-based security for RPL routing attacks, nodes' mobility is not considered or limited to only the sender nodes. Similarly, these trust-based protocols are not evaluated for mobile IoT environments, particularly regarding RPL attacks. Hence, a trust and mobility-based secure routing protocol is proposed, termed as SMTrust, by critically analysing the trust metrics involving the mobility-based metrics in IoT. SMTrust intends to provide security against RPL Rank and Blackhole attacks. The proposed protocol is evaluated in three different scenarios, including static and mobile nodes in an IoT network. SMTrust is compared with the default RPL objective function, Minimum Rank with Hysteresis Objective Function (MRHOF), SecTrust, DCTM, and MRTS. The evaluation results indicate that the proposed protocol outperforms with respect to packet loss rate, throughput, and topology stability. Moreover, SMTrust is validated using routing protocol requirements analysis to ensure that it fulfils the consistency, optimality, and loop-freeness.

A Systematic Study on a Customer’s Next-Items Recommendation Techniques

A customer’s next-items recommender system (NIRS) can be used to predict the purchase list of a customer in the next visit. The recommendations made by these systems support businesses by increasing their revenue and providing a more personalized shopping experience to customers. The main objective of this paper is to provide a systematic literature review of the domain to analyze the recent techniques and assist future research. The paper examined 90 selected studies to answer the research questions concerning the key aspects of NIRSs. To this end, the main contribution of the paper is that it provides detailed insight into the use of conventional and deep learning techniques, the popular datasets, and specialized metrics for developing and evaluating these systems. The study reveals that conventional machine learning techniques have been quite popular for developing NIRSs in the past. However, more recent works have mainly focused on deep learning techniques due to their enhanced ability to learn sequential and temporal information. Some of the challenges in developing NIRSs that need further investigation are related to cold start, data sparsity, and cross-domain recommendations.

Research on the Method of Digital Media Content Creation Based on the Internet of Things

This paper provides an in-depth study and analysis of the approach to digital media content creation using IoT technology. This study first investigates both WSN and NB-IoT technologies separately and then combines them to investigate the networking structure based on NB-IoT and WSN as well as the related technologies based on fusion. Then, the coverage method of the node redeployment of the traditional network of wireless sensors is elaborated. For the traditional method, a series of problems such as poor node connectivity and low coverage caused by not conducting a local search of subgroup nodes are proposed, and the node redeployment method of wireless sensor network based on the frog hopping algorithm is proposed, introducing the frog hopping algorithm, combining local search of subgroup and global information exchange, and proposing that for wireless sensor network nodes. We propose initializing the nodes of the wireless sensor network, combining the global information exchange with the subgroup, determining the range of the detectable area of the wireless sensor, and solving the calculus method for the irregular area to get the optimal network nodes so that the nodes of the wireless sensor network can be redeployed. In terms of system, this design abandons the CIS structure, which is more used in the current IoT and uses B/S structure and Java-web technology to design a web-based system. SSH (Struts + Spring + Hibernate) framework, AJAX asynchronous request technology, and JXLL/JFreechart technology are fully applied to improve the practicality and comfort of the system, reduce development and maintenance costs, and facilitate popularization. After the system design was completed, the modules were tested with the existing experimental conditions. The experimental results show that the system is designed to be reliable and can operate normally with high stability and practical significance.

Digital transformation of organizations: what do we know and where to go next?

Purpose

The purpose of this paper is to identify the development of the digital transformation literature and to the systematic literature review methodology.

Design/methodology/approach

The authors run a systematic literature review, followed by a rigorous thematic analysis of both academic and grey literature dataset, in order to develop a conceptual map of organizations' digital transformation. The authors aggregate the concepts and topics identified across the literature to find that they overwhelmingly tackle digital business models. At the same time, the authors identify a major blind spot resulting from ignoring the organization itself as a unit of analysis.

Findings

The findings show that developing a digital theory of the organization or the theory of digitally transformed organization is a major challenge to management researchers. The analysis exposed numerous research gaps that can be helpful for future research directions.

Originality/value

Digital transformation research enjoys an increasingly rapid rise to recognition across many academic disciplines and strongly impacts the management domain. adopt the view that published documents reflect the collective understanding of a phenomenon. This paper contributes to filtering the digital transformation literature, clarify complex relation between digital transformations of organizations and identify the key blind points.

Social Internet of Things: vision, challenges, and trends

IoT describes a new world of billions of objects that intelligently communicate and interact with each other. One of the important areas in this field is a new paradigm-Social Internet of Things (SIoT), a new concept of combining social networks with IoT. SIoT is an imitation of social networks between humans and objects. Objects like humans are considered intelligent and social. They create their social network to achieve their common goals, such as improving functionality, performance, and efficiency and satisfying their required services. Our article’s primary purpose is to present a comprehensive review article from the SIoT system to analyze and evaluate the recent works done in this area. Therefore, our study concentrated on the main components of the SIoT (Architecture, Relation Management, Trust Management, web services, and information), features, parameters, and challenges. To gather enough information for better analysis, we have reviewed the articles published between 2011 and December 2019. The strengths and weaknesses of each article are examined, and effective evaluation parameters, approaches, and the most used simulation tools in this field are discussed. For this purpose, we provide a scientific taxonomy for the final SIoT structure based on the academic contributions we have studied. Ultimately we observed that the evaluation parameters are different in each element of the SIoT ecosystem, for example for Relation Management, scalability 29% and navigability 22% are the most concentrated metrics, in Trust Management, accuracy 25%, and resiliency 25% is more important, in the web service process, time 23% and scalability 16% are the most mentioned and finally in information processing, throughput and time 25% are the most investigated factor. Also, Java-based tools like Eclipse has the most percentage in simulation tools in reviewed literature with 28%, and SWIM has 13% of usage for simulation.

A model-driven approach to ensure trust in the IoT

The Internet of Things (IoT) is a paradigm that permits smart entities to be interconnected anywhere and anyhow. IoT opens new opportunities but also rises new issues. In this dynamic environment, trust is useful to mitigate these issues. In fact, it is important that the smart entities could know and trust the other smart entities in order to collaborate with them. So far, there is a lack of research when considering trust through the whole System Development Life Cycle (SDLC) of a smart IoT entity. In this paper, we suggest a new approach that considers trust not only at the end of the SDLC but also at the start of it. More precisely, we explore the modeling phase proposing a model-driven approach extending UML and SysML considering trust and its related domains, such as security and privacy. We propose stereotypes for each diagram in order to give developers a way to represent trust elements in an effective way. Moreover, we propose two new diagrams that are very important for the IoT: a traceability diagram and a context diagram. This model-driven approach will help developers to model the smart IoT entities according to the requirements elicited in the previous phases of the SDLC. These models will be a fundamental input for the following and final phases of the SDLC.

A Two-Class Data Transmission Method Using a Lightweight Blockchain Structure for Secure Smart Dust IoT Environments

In smart dust IoT environments, a large number of devices with low computing power/resources are deployed to collect surrounding information. There are many issues to consider for an efficient and secure smart dust IoT environment. Sometimes the urgent sensed data needs to be transmitted immediately. In addition, there are potential problems related to security issues since the smart dust IoT systems may be deployed in hard-to-access areas. In this paper, we propose an effective transmission method for two-class sensed data for secure smart IoT systems. We divide the sensed data into two classes which consist of the urgent sensed data class (requiring urgent data transmission) and the normal sensed data class (with a slight transmission delay due to yielding to the urgent data transmission). In addition, for security reasons, the proposed transmission method uses two kinds of blockchains with the following two ledgers: (1) the urgent sensed data ledger, which is a ledger of data that needs urgent transmission; and (2) the normal sensed data ledger, which is a ledger of data that allows some delay. To be specific, the lightweight blockchain based on our earlier work is used for the normal sensed data transmission, whereas the modified conventional blockchain is used for the normal sensed data transmission. The experiments show that the performance of the proposed transmission method is better than the conventional transmission method in almost all sections. There is a 53% performance increase on average with regard to the transmission time. When the ratio of urgent sensed data is 0% (i.e., no urgent sensed data at all), the proposed transmission method is greater improved by as much as about 96%. This means that the lightweight blockchain scheme used in the proposed transmission method for the normal sensed data is very efficient.

Robust Intra-Body Communication Using SHA1-CRC Inversion-Based Protection and Error Correction for Securing Electronic Authentication

The explosive increase in the number of IoT devices requires various types of communication methods. This paper presents secure personal authentication using electrostatic coupling Intra-body communication (IBC) based on frequency shift keying (FSK) and error correction. The proposed architecture uses GPIO for a transmitter and analog-to-digital conversion (ADC) for a receiver. We mplemented FSK modulation, demodulation, data protection, and error correction techniques in the MCU software without applying hardware devices. We used the characteristic that the carrier signal is 50% duty square wave for 1-bit error correction and applied a method of randomly inverting SHA1 hash data to protect user authentication data during transmission. The transmitter modulates binary data using a square wave as a carrier signal and transmits data through the human body. The receiver demodulates the signal using ADC and decrypts the demodulated binary data. To determine the carrier frequency from ADC results, we applied a zero-crossing algorithm which is used to detect edge characteristics in image processing. When calculating the threshold value within the zero-crossing algorithm, we implemented an adaptive threshold setting technique utilizing Otsu’s binarization technique. We found that the size of the electrode pad does not affect the signal strength, but the distance between the electrode pad and the skin has a significant effect on the signal strength. Our results show that binary data modulated with a square wave can be successfully transmitted through the human body, and, when 1-bit error correction is applied, the byte error rate on the receiver side is improved around 3.5% compared to not applying it.

A Survey on Trust Management for WBAN: Investigations and Future Directions

The rapid uptake of the Wireless Body Area Networks (WBAN) and their services poses unprecedented security requirements. WBAN are evolving to support these requirements. Fulfilling these tasks is challenging as their mobile context is increasingly complex, heterogeneous, and evolving. One potential solution to meet the WBAN security requirements is trust management that helps to reach a more secure and adaptable WBAN environment. Accordingly, this article aims to serve as a brief survey of trust management approaches within intra-WBAN and inter-WBAN. For that, we first summarize trust management concepts, discuss WBAN challenges and classify the attacks on WBAN trust management models. Subsequently, we detail and compare the existing trust based approaches in a WBAN context. We pinpoint their limitations and provide a new classification of these different approaches. We also propose a set of best practices that may help the reader to build a robust and an efficient trust management framework. We complete this survey by highlighting the open future directions and perspectives for research.

TSME: a trust-based security scheme for message exchange in vehicular Ad hoc networks

A Vehicular Ad hoc NETwork (VANET) is a self-organized network formed by connected vehicles, which allows the exchange of useful traffic information in a timely manner. In such a context, evaluating the reliability of transmissions is vital. Trust can be used to promote such healthy collaboration. In fact, trust enables collaborating vehicles to counter uncertainty and suspicion by establishing trustworthy relationships. The main contribution of this paper is the proposition of a trust-based security scheme for message exchange in a VANET called TSME. Because of VANET characteristics, including dynamicity and high speed, we first proposed a VANET Grouping Algorithm (VGA); a suitable clustering algorithm organizing the network into groups with elected Group-Heads. Second, built on the VGA, we defined our trust management scheme dealing with vehicles’ reputations. Finally, we proposed a formal specification of the scheme using an inference system, and conducted a formal validation to assess its completeness and soundness rather than conducting simulations where some potentially rare conflicting or malfunctioning situations might not be detected. Soundness was proven by showing that there were no conflicts in our scheme, and completeness was established by assessing that all potential situations could be handled. The results obtained showed that our scheme for evaluating the veracity of exchanged messages is formally sound and complete.