A Novel Distributed Authentication of Blockchain Technology Integration in IoT Services

Abstract

Digital Object Identifier 10.1109/ACCESS.2017.DOI I. INTRODUCTION The Internet of Things (IoT) is a revolutionary technology that has enhanced the way in how smart devices and sensors are coherently interconnected to exchange data in an uninterrupted mechanism [1], [2]. This technology has been applied in smart living and transport sectors (e.g, smart cities and healthcare) to create a seamless and efficient flow of data for intelligent decision-making and automation [3], [4]. However, the proliferation of IoT devices has raised concerns in terms of trust and security. Here, traditional IoT architectures are designed with a centralized scheme such that devices that are connected to the IoT architecture can be vulnerable to threats and, in consequence, the data integrity, privacy and trustworthiness are compromised. This is particularly worrying when sensitive data are collected and exchanged in centralized IoT devices. Key security requirements have been established in IoT environments to ensure the confidentiality, integrity, and privacy of sensitive data. These requirements include authentication, authorization and access control, data integrity, interoperability, privacy, and identity management [5]. Here, the most severe threats in IoT are attributed to the lack of compliance of the aforementioned requirements [6], [7]. In addition, the absence of standardized protocols hinders the efficient communication, interoperability and data exchange between devices. This can lead to a fragmented and inefficient IoT environment [8].Scalability plays an important role in the success of IoT systems by scaling up the network capacity, infrastructure, and computational resources. However, as the IoT environment grows in size, it can produce significant delays, scalability issues, and increased costs [9]. Furthermore, several issues can be observed due to the centralized nature of traditional IoT architectures such as: i) single point failures, ii) network congestions, iii) increased latency, and iv) malicious attacks from hackers or unauthorized actors [10], [11].Blockchain-technology has gained interest in the IoT framework due to its immutability and transparency capabilities in a decentralized architecture. One of the fundamental aspects of IoT is to enable the sharing of resources from

Secure Data Sharing in IoT Networks using Blockchain and Machine Learning

“…The results section showcases the performance of the proposed model for secure data sharing in IoT networks using blockchain and machine learning in comparison with three existing methods: [5], [9], and [15]. The following tables provide a comprehensive overview of the comparative analysis, highlighting the impacts of the performance enhancements achieved by the proposed model process.…”

“…94.3 [9] 91.2 [15] 95.8 Table 3 presents a comparison of packet delivery ratios. The proposed model achieves an impressive packet delivery ratio of 98.7%, surpassing [5], [9], and [15], which attain lower ratios of 94.3%, 91.2%, and 95.8%, respectively. This enhancement significantly improves data reliability and ensures that a higher percentage of transmitted data reaches its destination successfully.…”

“…The proposed model exhibits a substantial throughput improvement, achieving a throughput of 385 Mbps. In contrast, [5], [9], and [15] achieve lower throughputs of 275 Mbps, 210 Mbps, and 310 Mbps, respectively. This enhancement in throughput directly translates into faster data transfer rates, enabling more efficient IoT applications and reduced latency in data transmission.…”

“…Energy Efficiency (%) Proposed 12.5 [5] 8.9 [9] 7.2 [15] 9.8 Table 1 presents a comparative analysis of energy efficiency between the proposed model and existing methods. The results demonstrate that the proposed model outperforms [5], [9], and [15] by achieving a 12.5% improvement in energy efficiency.…”

“…Energy Efficiency (%) Proposed 12.5 [5] 8.9 [9] 7.2 [15] 9.8 Table 1 presents a comparative analysis of energy efficiency between the proposed model and existing methods. The results demonstrate that the proposed model outperforms [5], [9], and [15] by achieving a 12.5% improvement in energy efficiency. This enhancement has significant implications for IoT networks as it reduces energy consumption, prolongs device lifespan, and contributes to sustainable IoT operations.…”