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Blockchain-based IoT system
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Internet of Things (IoT) systems have gained huge popularity in the past decade. This technology is developing as a back boon from the day-to-day utility in smart homes to intelligent power grids. It has become ubiquitous in the past decade while gaining popularity in academia and industry. As the devices used are usually sensors without a well-dev...
Citations
... Given that the existing solutions are insufficient, addressing the comprehensive spectrum of privacy, security, and scalability issues in IoT systems presents a substantial research challenge. The advent of Bitcoin alongside other cryptocurrencies popularised blockchain technology, which emerged as a revolutionary invention with wide-ranging applications across several industries [9,10]. The IoT is a promising field where interconnected gadgets share data and independently perform tasks. ...
... The selection of a consensus mechanism can substantially influence the efficiency and scalability of the blockchain network, especially in IoT systems where resources are constrained [16]. The blockchain is a highly suitable technology that can offer a safe and decentralised environment for IoT networks [9]. The security features blockchain offers are unparalleled and highly motivating [17,18]. ...
An amalgamation of blockchain technology and the Internet of Things (IoT) has presented notable concerns regarding scalability, security, and privacy, particularly in IoT contexts with limited resources. Conventional blockchains, including traditional consensus mechanisms like Proof of Work (PoW) and Proof of Stake (PoS), meet challenges in handling many transactions, meeting energy efficiency standards, and addressing privacy issues in blockchain-based IoT networks. This work presents a new fog-based blockchain paradigm that integrates the benefits of Proof of Authority (PoA) and Delegated Proof of Stake (DPoS) consensus mechanisms and a proxy re-encryption approach to guarantee improved efficiency and system security. The proposed architecture integrates three essential operational algorithms: Fog Node Operation, Blockchain Node Operation, and Privacy Preservation Mechanism. These algorithms manage data processing, ensure secure transactions, and maintain privacy. Fobsim is used to conduct a series of simulations to evaluate the performance of PoA, DPoS, PoW, and PoS. The results indicate that PoA and DPoS provide better transaction speed, energy efficiency, and scalability than conventional consensus. As illustrated in the results, PoA stands out for its deficient energy consumption, making it an ideal fit for IoT applications. This research addresses the pressing concerns of scalability, privacy, and energy efficiency in blockchain-enabled Internet of Things (B-IoT) systems. The results lay the foundation for the future advancement of integrated B-IoT systems that can enable extensive, real-time IoT applications.
... Blockchain presents a promising framework inside the vast network of interconnected IoT devices to develop a complete and decentralised system for verifying the authenticity of IoT data . The peerto-peer network of this technology distributes and controls data over numerous nodes worldwide, providing essential resilience and authentication procedures for safeguarding IoT devices [4,8]. The concept of blockchain emerged as a viable option to possess such prominent attributes. ...
... Various industries, are progressively utilising the IoT and cloud computing services to monitor critical applications such as industrial control This article is part of the Topical Collection: 4 -Track on IoT Guest Editor: Peter Langendoerfer B Iraq Ahmad Reshi rshiraq333@gmail.com 1 Department of CSE, Islamic University of Science and Technology, Awantipora, Kashmir, J&K, India systems and smart grids. The main objective is to enhance efficiency and reduce operational costs [1,2,4].The essential data of the IoT is stored within a third-party cloud service provider as part of the conventional architecture for IoTcloud integration [3].Nevertheless, integrating these devices present challenges, particularly in managing the limited resources available for interconnected devices and addressing concerns regarding the possible vulnerability of sensitive IoT data [4]. It is important to recognise that cloud servers, essential to the traditional IoT-cloud structure, possess extensive knowledge of the data they store, which leads to privacy concerns. ...
... Various industries, are progressively utilising the IoT and cloud computing services to monitor critical applications such as industrial control This article is part of the Topical Collection: 4 -Track on IoT Guest Editor: Peter Langendoerfer B Iraq Ahmad Reshi rshiraq333@gmail.com 1 Department of CSE, Islamic University of Science and Technology, Awantipora, Kashmir, J&K, India systems and smart grids. The main objective is to enhance efficiency and reduce operational costs [1,2,4].The essential data of the IoT is stored within a third-party cloud service provider as part of the conventional architecture for IoTcloud integration [3].Nevertheless, integrating these devices present challenges, particularly in managing the limited resources available for interconnected devices and addressing concerns regarding the possible vulnerability of sensitive IoT data [4]. It is important to recognise that cloud servers, essential to the traditional IoT-cloud structure, possess extensive knowledge of the data they store, which leads to privacy concerns. ...
The inherent challenges associated with the Internet of Things (IoT), such as vulnerability to cyber threats and privacy issues, need the development of novel solutions to ensure secure and efficient handling of data. Fog computing resolves these concerns by facilitating data processing in proximity to edge devices, minimising latency, and improving real-time decision-making. Blockchain boosts security in fog-based systems by providing a tamper-proof and transparent ledger. However, exclusively prioritising privacy in fog-based blockchains may impede the practical execution. This article presents the FogBlock Connect paradigm, which combines Fog computing and Blockchain through the implementation of a tailored Proxy Re-encryption (PRE) algorithm inspired by BBS98. This strategy guarantees enhanced data confidentiality while simultaneously upholding operational effectiveness in fog-based blockchains for Internet of Things applications. The efficiency and effectiveness of the suggested PRE algorithm over typical encryption methods are confirmed by comprehensive simulations utilising the Fobsim simulator. The FogBlock Connect paradigm entails the transmission of updates from nearby IoT devices to Fog servers for the purpose of creating and securely storing global updates, hence improving efficiency and performance. The paradigm ensures robust privacy measures, mitigates risks of single-point failures, and facilitates precise access control, establishing a basis for secure and resilient IoT applications. The CCA resistant formal security proof provides further validation for the strength and effectiveness of the suggested approach.
... Moreover, Internet of Things (IoT) devices present an enticing opportunity for malicious actors because of their capability to collect and transmit sensitive personal data, such as individual names, addresses, and credit card details. Hackers can facilitate the unauthorized infiltration of additional devices and data within a network by utilizing Internet of Things (IoT) devices as potential entry points [16]. In general, the issue of cybersecurity in the Internet of Things (IoT) presents a complex and formidable challenge that necessitates a comprehensive and holistic approach. ...
... Collaborative efforts among hardware and software manufacturers, network and infrastructure service providers, and end users are necessary to identify effective resolutions for these challenges. The deployment of security measures, establishment of standards, and promotion of best practices will be crucial in ensuring the security and privacy of IoT devices and the data they collect [16]. ...
... The architecture aims to ensure the secure and scalable transmission of IoT data from decentralized IoT applications at the fog layer. Artificial intelligence (AI) is employed in diverse domains of advanced technologies, including blockchain thinking , decentralized AI , the intelligence of things, and intelligent robots, among others, in the daily lives of individuals [16]. The convergence between artificial intelligence (AI) Internet of Things (IoT) enables the collection of a vast amount of data and facilitates its analysis. ...
This book chapter presents an overview of the cybersecurity concerns of the Internet of Things (IoT). It investigates how artificial intelligence (AI) and blockchain technologies address these challenges. This chapter describes the growing number of accessories in IoT and the increasing sophistication of cyberattacks targeting these devices. Each of these factors presents its own set of unique security challenges. Furthermore, we are investigating the potential benefits of incorporating AI and blockchain into IoT cybersecurity. These advantages include improved threat detection and response, increased data privacy and integrity, and increased attack resistance. Moreover, we present a review of particular novel approaches in the field. This chapter presents brief case studies of AI and blockchain-based Internet of Things cybersecurity solutions. These case studies show the practical applications and benefits of these technologies in safeguarding Internet of Things environments. The chapter provides insights into the changing landscape of cybersecurity for the Internet of Things (IoT) and AI and blockchain’s role in mitigating cyber threats in this sector.
... The resource restraints of IoT, like limited processing power, may hinder direct integration with resource-intensive blockchain networks. In addition, scalability and latency issues must be carefully addressed to handle the large-scale data generated by IoT devices Reshi and Sholla, 2022). ...
The more intelligent devices connect to the Internet, the more security and privacy breaches. This research explores integrating the blockchain and the Internet of Things (IoT) technologies, referred to as the blockchain-based IoT (B-IoT), focusing on the opportunities, challenges, and solutions associated with this convergence. The emergence of B-IoT has the latent to transform several domains and industries by enhancing security, trust, and decentralized data management. It begins with an introduction that highlights the significance of B-IoT and outlines the research objectives. Next, a comprehensive literature review examines existing studies and frameworks on blockchain, IoT, and their convergence. This review identifies gaps in the current literature, setting the foundation for subsequent research. Finally, the research analyzes the opportunities offered by B-IoT, showcasing real-world examples and use cases in areas such as healthcare, supply chain management, and energy systems. However, integrating blockchain and IoT brings various challenges, including scalability, interoperability, security, and privacy concerns. These challenges are examined, focusing on their implications for adopting and implementing B-IoT solutions. The chapter proposes potential solutions, frameworks, and architectures to mitigate the limitations. It also explores case studies and experiments to validate and evaluate the proposed solutions’ effectiveness. The discussion section interprets the findings, comparing them with existing literature and theories. The conclusion summarizes the main contributions of the research and suggests future research to advance the field of B-IoT further. This research offers a comprehensive analysis of B-IoT, providing valuable insights and guidance for researchers, practitioners, and decision-makers in understanding and harnessing the potential of this emerging technology paradigm.
... While these solutions offer respite, they often cater to specific scenarios, necessitating the development of novel techniques that account for IoT nodes' energy, processing, and computational constraints. Moreover, current techniques require further refinements due to underlying flaws [20]. Considering the imminent ubiquity of IoT in the future, extensive research and efforts are indispensable in mitigating the risks associated with Black Hole attacks. ...
The Internet of Things (IoT) and Wireless Sensor Networks (WSNs) have rapidly spread in recent decades, leading to remarkable innovation and integrated possibilities. The switch from IPv4 to IPv6, made possible by advancements in networking technology and the use of nanodevices, has further improved connectivity. This move allows for connecting a wider range of devices to servers. Nevertheless, the increasing interconnectivity has brought about difficulties in efficiently overseeing and analysing the enormous amount of data produced throughout all levels of the IoT. The requirement of comprehensive security management is particularly concerning for IoT devices due to their large quantity and small size. Within the layered architecture of IoT, the network layer assumes pivotal importance in ensuring security, bearing responsibility for storing routing information and executing corresponding decisions. The Black Hole attack is a frequently encountered and significant concern among the security attacks addressed. This paper thoroughly examines the consequences of the Black Hole attack on IoT networks, carefully analyzing its impact. Furthermore, it presents a novel mitigation algorithm designed to counter such threats efficiently. The research employs NS2 and Simulink to run extensive simulations, enabling the evaluation of network throughput and Packet Delivery Ratio (PDR). Applying the proposed mitigation strategy to a network affected by the Black Hole attack results in a significant improvement in throughput, which closely resembles that of an unaffected network. The observed Packet Delivery Ratio (PDR) is measured at 98.21%. This highlights the algorithm’s effectiveness in mitigating the detrimental effects of the Black Hole attack on IoT networks.
... However, addressing the integration challenges requires in-depth research focusing on efficient and scalable consensus algorithms, lightweight cryptography, privacy-preserving techniques, and energy-efficient mining algorithms. 22 Apart from providing a trustless environment for IoT devices, researchers are implementing blockchain for the security, data management, and monetization of IoT devices. Designing a secure and energy-efficient protocol that considers both IoT and blockchain technology is still an open issue, and there is a need to converge the technologies to make IoT devices scalable for particular blockchain types. ...
The accelerated development of information and communication technologies has generated a demand for data storage that is effective, transparent, immutable, and secure. Distributed ledger technology and encryption techniques such as hashing and blockchain technology revolutionised the landscape by meeting these requirements. However, blockchain must overcome obstacles such as low latency, throughput, and scalability for its full potential. Investigating blockchain's structure, types, challenges, promises, and variants is necessary to understand blockchain and its capabilities comprehensively. This paper overviews various aspects, such as emergent blockchain protocols, models, concepts, and trends. We classify blockchain variants into five essential categories, DAG, TDAG, Sharding, Consensus, and Combining methods, based on the structure each follows, and conduct a comparative analysis. In addition, we explore current research tendencies. As technology progresses, it is essential to comprehend the fundamental requirements for blockchain development.
... Reshi et al. [5] reviewed in their survey some of the challenges of securing IoT systems particularly, as well as how promising emerging technologies can be used as or to support security measures. ...
... Pervasive Health Monitoring (PHM) architectures present significant security concerns that need attention and resolution. Different potential solutions have been proposed in the literature [7], [9]- [13], including addressing security and privacy concerns using emerging technologies [5], [6], [8], [21]. ...
Pervasive Health Monitoring (PHM) uses sensors and wearable devices and data analytics for real-time health monitoring. It enables early detection and personalized care interventions. This technology has the potential to revolutionize healthcare by improving proactive and preventive care.
Besides, Deep learning (DL) based PHM is even more promising as it improves the discovery of complex patterns and correlations. This leads to precise health monitoring and personalized care, enhances diagnostics, and ultimately improves patient outcomes in the field of healthcare.
However, privacy and security considerations must be addressed for successful implementation. This paper investigates the security and privacy concerns in Pervasive Health Monitoring architectures. It discusses through an illustrative DL-based PHM architecture the potential threats and attacks during the inference and training phases, and identifies key security and privacy issues. It also gives insights on countermeasures and technological solutions that can address security and privacy concerns in PHM architectures.
Background:
Today, computer networks are everywhere, and we utilize the Internet to access our home network. IoT networks connect home appliances and provide remote instructions. Access to any tool over an uncertain network attracts assaults. User authentication might be password- or biometric-based. Data security across a secure network like the Internet is difficult when authenticating a device. Hashing is used for validation and confidentiality in several encryption and decryption schemes. Classic cryptographic security methods require a lot of memory, processing power, and power. They cannot work with low-resource IoT devices.
Method:
Automatic Device-to-Device communiqué opens up new applications, yet network machines and devices have limited resources. A remote-access home device authentication mechanism is proposed in this research. A new, lightweight encryption approach based on Deoxyribonucleic- Acid (DNA) sequences is developed to make IoT device connections easy and secure. Home network and appliance controller devices use authentication tools. DNA sequences are random therefore we utilized them to create a secure secret key.
Results:
Efficiency and strength are advantages of the proposed method. Our method prevents replay, server spoofing, and man-in-the-middle attacks. The suggested method protects network users and devices.
Conclusion:
Meanwhile, we model the system and find that the network's delay, throughput, and energy consumption don't degrade considerably.
