Trustworthy Internet Of Things Research Articles

Streamlining IoT-driven Data Using Blockchain

The integration of Internet of Things (IoT) technology has revolutionized data collection and analytics, creating vast networks of interconnected devices generating large volumes of data. However, this rapid expansion of IoT ecosystems introduces significant challenges related to data security, integrity, scalability, and privacy. Blockchain technology, with its decentralized and immutable nature, emerges as a compelling solution to address these challenges. This paper explores the synergy between IoT and blockchain, examining how blockchain can streamline IoT-driven data by providing secure data exchanges, enhancing transparency, and facilitating scalability. The study investigates the key mechanisms through which blockchain can mitigate common IoT data issues. It considers blockchain's role in ensuring data integrity by utilizing cryptographic methods, enabling traceability through distributed ledgers, and protecting against unauthorized data manipulation. Furthermore, it explores the potential of blockchain-based smart contracts to automate processes and improve interoperability among IoT devices. The paper delves into specific use cases, such as smart cities, demonstrating how blockchain can effectively streamline IoT data across various industries. The findings highlight that while blockchain offers substantial benefits, it also introduces unique challenges, including high energy consumption, latency concerns, and complex integration processes. This concludes with a discussion of Security concerns, Comparison with existing solutions. By addressing these challenges, blockchain can become a pivotal technology in streamlining IoT-driven data, paving the way for more secure, efficient, and trustworthy IoT ecosystems.

Application of Trustworthy IoT Technology in Fast Communities: Smart Access Control

As a response to the current development status and existing problems in the ubiquitous and trustworthy aspect of the Internet of Things (IoT) in the construction of smart community systems in Bangladesh, this paper presents the trustworthy technology strategy of the ubiquitous and trustworthy IoT intelligent system. Additionally, it provides a list of the demonstration application practice of trustworthy IoT technology at the level of smart communities through three different application scenario project construction cases. These cases include smart access control, smart buildings' construction, and smart parks' construction.

Enhancing Trust and Security in IoT Architecture for Low-Cost Microcontroller Devices using Elliptic Curve Cryptography

Abstract—In the rapidly expanding universe of the Internet of Things (IoT), low-cost microcontroller devices, such as the NodeMCU, have become ubiquitous. While these devices have transformed how we interact with the physical world, they also introduce significant security vulnerabilities. Chief among these is susceptibility to man-in-the-middle (MITM) attacks, which pose a serious risk to the confidentiality and integrity of data transmitted across these networks. This study addresses this critical issue by proposing the adoption of Elliptic Curve Cryptography (ECC), a cryptographic method known for its efficiency and strong security, despite the computational limitations of low-cost IoT devices. We conducted an experiment demonstrating the ease with which an MITM attack can intercept data from a NodeMCU device. Following this, we implemented ECC to secure data transmission, showcasing its viability as a lightweight yet robust security solution. Our research not only highlights the pressing need for enhanced security measures in the IoT ecosystem but also provides a practical framework for securing low-cost microcontroller devices against sophisticated cyber threats. Through our findings, we contribute to the development of more secure, trustworthy IoT architectures, ensuring that these devices can continue to safely serve as integral components of our digital lives. Keywords—NodeMCU, ESP8266, Data theft, Elliptic Curve Cryptography, Man-in-the-middle attack

Enhancing Security and Trust in Internet of Things through Meshtastic Protocol Utilising Low-Range Technology

The rapid proliferation of Internet of Things (IoT) devices has raised significant concerns regarding the trustworthiness of IoT devices, which is becoming a crucial aspect of our daily lives. In this paper, we deal with this important aspect by taking into account Meshtastic, a dynamic mesh networking protocol that offers robustness and adaptability, important characteristics for the dynamic and heterogeneous IoT environment. LoRaWAN (Low-Range Wide Area Network), a low-power, long-range wireless communication standard, introduces energy efficiency and extends the reach of IoT networks, enabling secure communication over extended distances. To improve the trustworthiness of IoT devices, we present an integrated approach that leverages the strengths of Meshstastic’s dynamic mesh networking capabilities and LoRa’s low-power, long-range communication, along with the integration of a reputation model specifically designed for IoT. We evaluated the performance of the proposed solution through several simulations and real-world experiments. The results show that the devices’ measured values of trust reflect the real behaviour of the devices. These findings underscore the viability and applicability of the Meshtastic protocol utilising LoRa technology as a pivotal step towards establishing resilient and trustworthy IoT infrastructures in the face of evolving security challenges.

Governance of a Blockchain-Enabled IoT Ecosystem: A Variable Geometry Approach.

The proliferation of Internet of Things (IoT) applications is rapidly expanding, generating increased interest in the incorporation of blockchain technology within the IoT ecosystem. IoT applications enhance the efficiency of our daily lives, and when blockchain is integrated into the IoT ecosystem (commonly referred to as a blockchain-IoT system), it introduces crucial elements, like security, transparency, trust, and privacy, into IoT applications. Notably, potential domains where blockchain can empower IoT applications include smart logistics, smart health, and smart cities. However, a significant obstacle hindering the widespread adoption of blockchain-IoT systems in mainstream applications is the absence of a dedicated governance framework. In the absence of proper regulations and due to the inherently cryptic nature of blockchain technology, it can be exploited for nefarious purposes, such as ransomware, money laundering, fraud, and more. Furthermore, both blockchain and the IoT are relatively new technologies, and the absence of well-defined governance structures can erode confidence in their use. Consequently, to fully harness the potential of integrating blockchain-IoT systems and ensure responsible utilization, governance plays a pivotal role. The implementation of appropriate regulations and standardization is imperative to leverage the innovative features of blockchain-IoT systems and prevent misuse for malicious activities. This research focuses on elucidating the significance of blockchain within governance mechanisms, explores governance tailored to blockchain, and proposes a robust governance framework for the blockchain-enabled IoT ecosystem. Additionally, the practical application of our governance framework is showcased through a case study in the realm of smart logistics. We anticipate that our proposed governance framework will not only facilitate but also promote the integration of blockchain and the IoT in various application domains, fostering a more secure and trustworthy IoT landscape.

A model for evaluating the impediments to secure and trustworthy IoT environment: a software industry study

PurposeIn the existing era, the Internet of Things (IoT) can be considered entirely as a system of embedding intelligence. The transverse character of IoT systems and various components associated with the arrangement of IoT systems have confronted impediments in the form of security and trust. There is a requirement to efficiently secure the IoT environment. The present study recommends a framework for impediments to secure and trustworthy IoT environments.Design/methodology/approachThe present study identifies thirteen potential impediments to secure and trustworthy IoT environment. Further, a framework is developed employing Total Interpretive Structural Model (TISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) approach. The integrated approach is employed as TISM organizes inter-relations among the identified impediments, while MICMAC analysis organizes interpretations related to the driving and dependence power of the impediments.FindingsThe results from the study represents that security of IoT from arbitrary attacks is the impediment that has attained the highest driving power. The impediments such as “security of IoT from arbitrary attacks”, “profiling” and “trust and prominence structure” are identified at the top level in the analysis.Research limitations/implicationsThe previous studies highlight the facilitating contribution of IoT on various devices but neglect the impediments that can contribute towards a safe and trustworthy IoT environment. Also, the present study has its limitations as it depends upon the experts’ recommendations and suggestions.Originality/valueThe existing framework could be beneficial in constructing policies and suggestions to efficiently cater the impediments to a secure and trustworthy IoT environment.

A Review on the IOT System

The advancement of computer science and communication technologies is being enabled by something called the Internet of Things (IoT). The IoT is being used in many fields, so maintaining its Security is becoming an increasingly important concern. The IoT industry as a whole is going to be significantly impacted as a result of this. This study examines the IoT security problem at the IoT system's perception, network, and application levels suggests a secure way to build IoT and explains how to make it safe based on the problems that already exist in the IoT framework. The study begins with the concept of IoT, its characteristics, and how it functions as a system. Finally, the theoretical foundations necessary to construct a trustworthy IoT security system will be presented. The IoT will enable inanimate things to participate in human activities. IoT security is notoriously difficult to handle because items are often integrated into the control procedures of more complicated systems. In practice, the IoT is a complicated paradigm in which people interact with a technological ecosystem based on intelligent devices via various complicated procedures. Interactions between a person, an intelligent object, a technical environment, and a process show IoT security's cognitive and systemic components.

A context-aware information-based clone node attack detection scheme in Internet of Things

The rapidly expanding nature of the Internet of Things (IoT) networks is beginning to attract interest across a range of applications, including smart homes, smart transportation, smart health, and industrial contexts such as smart robotics. This cutting-edge technology enables individuals to track and control their integrated environment in real-time and remotely via a thousands of IoT devices comprised of sensors and actuators that actively participate in sensing, processing, storing and sharing information. Nonetheless, IoT devices are frequently deployed in hostile environments, wherein adversaries attempt to capture them in order to seize control of the entire network. One such example of potentially malicious behaviour is the cloning of IoT devices, in which an attacker can physically capture the devices, obtain some sensitive information, duplicate the devices, and intelligently deploy them in desired locations to conduct various insider attacks. A device cloning attack on IoT networks is a significant security concern since it allows for selective forwarding, sink-hole, black-hole, and warm-hole attacks. To address this issue, this paper provides an efficient scheme for detecting clone node attack on mobile IoT networks that uses semantic information of IoT devices known as context information to locate them securely. We design the location proof mechanism by combining location proofs and batch verification of the extended elliptic curve digital signature technique (ECDSA*) to accelerate the verification process at selected trusted nodes. Furthermore, we present a model for selecting trustworthy IoT devices based on their profile capabilities, enabling them to be chosen from the other IoT devices for the location proof-verification procedure. Compared with existing studies, the performance analysis and experimental results suggest that our proposed scheme provides a high degree of detection accuracy with minimal detection time and significantly reduces the computation, communication, energy and storage overheads.

Zero-Bias Deep Learning for Accurate Identification of Internet-of-Things (IoT) Devices

The Internet of Things (IoT) provides applications and services that would otherwise not be possible. However, the open nature of IoT make it vulnerable to cybersecurity threats. Especially, identity spoofing attacks, where an adversary passively listens to existing radio communications and then mimic the identity of legitimate devices to conduct malicious activities. Existing solutions employ cryptographic signatures to verify the trustworthiness of received information. In prevalent IoT, secret keys for cryptography can potentially be disclosed and disable the verification mechanism. Non-cryptographic device verification is needed to ensure trustworthy IoT. In this paper, we propose an enhanced deep learning framework for IoT device identification using physical layer signals. Specifically, we enable our framework to report unseen IoT devices and introduce the zero-bias layer to deep neural networks to increase robustness and interpretability. We have evaluated the effectiveness of the proposed framework using real data from ADS-B (Automatic Dependent Surveillance-Broadcast), an application of IoT in aviation. The proposed framework has the potential to be applied to accurate identification of IoT devices in a variety of IoT applications and services. Codes and data are available in IEEE Dataport.

A blockchain-based trust management method for Internet of Things

In Internet of things (IoT), one of the main concepts is wireless sensor networks where there are a large of resource-constrained sensor nodes. With the wide application of Internet of things (IoT), these resource-constrained sensor nodes have to suffer from more security threats. One of possible solutions is to establish a trustworthy IoT environment where the interactions are based on the trustworthiness of sensor nodes. More and more scholars focus on studying trust management and trust evaluation in IoT, but there is few research in ensuring that the feedbacks used in the trust evaluating process is trustworthy. Furthermore, a resource-constrained IoT node does not have enough memory to satisfy the usage of trust computation and maintenance. To solve the problem, this paper proposes a blockchain-based trust management mechanism (BBTM), where the trustworthiness of sensor nodes will be evaluated by the mobile edge nodes. BBTM can create smart contracts for trust computation and verify the computation process. We analyze BBTM performance in terms of trust accuracy, convergence, and resiliency against attacks. In addition, we also compare BBTM with other methods. Experimental results demonstrate the effectiveness of the proposed method.

From Trustworthy Data to Trustworthy IoT

Internet of Things (IoT) is composed of physical devices, communication networks, and services provided by edge systems and over-the-top applications. IoT connects billions of devices that collect data from the physical environment, which are pre-processed at the edge and then forwarded to processing services at the core of the infrastructure, on top of which cloud-based applications are built and provided to mobile end users. IoT comes with important advantages in terms of applications and added value for its users, making their world smarter and simpler. These advantages, however, are mitigated by the difficulty of guaranteeing IoT trustworthiness, which is still in its infancy. IoT trustworthiness is a must especially in critical domains (e.g., health, transportation) where humans become new components of an IoT system and their life is put at risk by system malfunctioning or breaches. In this article, we put forward the idea that trust in IoT can be boosted if and only if its automation and adaptation processes are based on trustworthy data. We therefore depart from a scenario that considers the quality of a single decision as the main goal of an IoT system and consider the trustworthiness of collected data as a fundamental requirement at the basis of a trustworthy IoT environment. We therefore define a methodology for data collection that filters untrusted data out according to trust rules evaluating the status of the devices collecting data and the collected data themselves. Our approach is based on blockchain and smart contracts and collects data whose trustworthiness and integrity are proven over time. The methodology balances trustworthiness and privacy and is experimentally evaluated in real-world and simulated scenarios using Hyperledger fabric blockchain.

Computational Intelligence for Internet of Things in the Big Data Era (Part II) [Guest Editorial

This special issue puts a focus on CI-based solutions for the spatial-temporal challenges toward trustworthy Internet of Things in the Big Data Era.

STIR: A Smart and Trustworthy IoT System Interconnecting Legacy IR Devices

Legacy-infrared (IR) devices are pervasively used. They are often controlled by IR remotes and cannot be controlled over the Internet. A trustworthy and cost-effective smart IR system that is able to change an IR controllable device into a smart Internet of Things (IoT) device and interconnect them for smart city/home applications is offered in this article. First, a printed circuit board (PCB) consisting of an IR receiver and multiple IR transmitters side by side which are capable of transmitting about 20 m indoors is designed and implemented. This IR transceiver board is the first of its kind. Second, the IR transceiver can be linked up with a Raspberry Pi, for which we develop two software tools, recording and replaying any IR signals so as to put the corresponding IR device in control. Third, a smartphone can be connected to the Pi by means of a message queuing telemetry transport (MQTT) cloud server so that the commands can be sent by the smartphone to the legacy IR device over the Internet. We have also identified the deficiency of TLS mutual authentication implemented by the popular MQTT open-source package Mosquitto for a trustworthy IoT system and patched the system. We analyze the factors that affect the IR signal transmission distance, discuss the security concerns of our IR transceiver, and illustrate the scenarios for attacks. For instance, TV can be turned off remotely by a drone equipped with the transceiver.

A Roadmap Toward the Resilient Internet of Things for Cyber-Physical Systems

The Internet of Things (IoT) is a ubiquitous system connecting many different devices - the things - which can be accessed from the distance. The cyber-physical systems (CPS) monitor and control the things from the distance. As a result, the concepts of dependability and security get deeply intertwined. The increasing level of dynamicity, heterogeneity, and complexity adds to the system's vulnerability, and challenges its ability to react to faults. This paper summarizes state-of-the-art of existing work on anomaly detection, fault-tolerance and self-healing, and adds a number of other methods applicable to achieve resilience in an IoT. We particularly focus on non-intrusive methods ensuring data integrity in the network. Furthermore, this paper presents the main challenges in building a resilient IoT for CPS which is crucial in the era of smart CPS with enhanced connectivity (an excellent example of such a system is connected autonomous vehicles). It further summarizes our solutions, work-in-progress and future work to this topic to enable "Trustworthy IoT for CPS". Finally, this framework is illustrated on a selected use case: A smart sensor infrastructure in the transport domain.

Clustering-Driven Intelligent Trust Management Methodology for the Internet of Things (CITM-IoT)

The growth and adoption of the Internet of Things (IoT) is increasing day by day. The large number of IoT devices increases the risk of security threats such as (but not limited to) viruses or cyber-attacks. One possible approach to achieve IoT security is to enable a trustworthy IoT environment in IoT wherein the interactions are based on the trust value of the communicating nodes. Trust management and trust assessment has been extensively studied in distributed networks in general and the IoT in particular, but there are still outstanding pressing issues such as bad-mouthing of trust values which prevent them from being used in practical IoT applications. Furthermore, there is no research in ensuring that the developed IoT trust solutions are scalable across billions of IoT nodes. To address the above-mentioned issues, we propose a methodology for scalable trust management solution in the IoT. The methodology addresses practical and pressing issues related to IoT trust management such as trust-based IoT clustering, intelligent methods for countering bad-mouthing attacks on trust systems, issues of memory-efficient trust computation and trust-based migration of IoT nodes from one cluster to another. Experimental results demonstrate the effectiveness of the proposed approaches.

A survey on trust management for Internet of Things

Internet of Things (IoT) is going to create a world where physical objects are seamlessly integrated into information networks in order to provide advanced and intelligent services for human-beings. Trust management plays an important role in IoT for reliable data fusion and mining, qualified services with context-awareness, and enhanced user privacy and information security. It helps people overcome perceptions of uncertainty and risk and engages in user acceptance and consumption on IoT services and applications. However, current literature still lacks a comprehensive study on trust management in IoT. In this paper, we investigate the properties of trust, propose objectives of IoT trust management, and provide a survey on the current literature advances towards trustworthy IoT. Furthermore, we discuss unsolved issues, specify research challenges and indicate future research trends by proposing a research model for holistic trust management in IoT.