Addressing Security and Privacy Issues of IoT Using Blockchain Technology

Mohanta, Bhabendu Kumar; Jena, Debashisha; Ramasubbareddy, Somula; Daneshmand, Mahmoud; Gandomi, Amir H.

doi:10.1109/jiot.2020.3008906

Cited by 155 publications

(69 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…IoT is mostly modeled through a three-layer architecture, with a physical layer, a network layer, and an application layer. Each of these layers is vulnerable to certain types of attacks that challenge the security of IoT systems [9,10]. Unauthorized access to the network resources, as well as trust management and authentication issues are regarded as some of the most important threats for the network and application layer.…”

Section: Iot Platforms and Blockchain Solutionsmentioning

confidence: 99%

Combining Blockchains, Smart Contracts, and Complex Sensors Management Platform for Hyper-Connected SmartCities: An IoT Data Marketplace Use Case

et al. 2021

View full text Add to dashboard Cite

In this paper, we demonstrate the multiple points of innovation when combining blockchain technology with Internet of Things (IoT) and security frameworks. The deployment and use of IoT device networks in smart city environments has produced an enormous amount of data. The fact that those data are possessed by multiple sources that use independent systems for data collection, storage, and use impedes the exploitation of their value. Blockchains, as distributed ledgers, can be used for addressing the development of a universal system for data collection and distribution. Smart contracts can be used to automate all the processes of such a network, while at the same time, blockchain and the InterPlanetary File System (IPFS) protect sensitive data through anonymity and distributed storage. An innovative and open IoT blockchain market of applications, data, and services is proposed that: (i) provides the framework upon which objects and people can exchange value in form of virtual currencies, for assets (data and services) received; (ii) defines the motivation incentives according to social and business context for humans and smart objects to interact. The specific marketplace is piloted through a cross-border trial between Santander and Fujisawa, in the context of the M-Sec project, validating thus the interoperability, efficiency, and data protection principles.

show abstract

Section: Iot Platforms and Blockchain Solutionsmentioning

confidence: 99%

Combining Blockchains, Smart Contracts, and Complex Sensors Management Platform for Hyper-Connected SmartCities: An IoT Data Marketplace Use Case

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Mohanta et al [116] 2020 Analyzing blockchain for IoT security and privacy; Analyzing IoT security threats; Result-oriented case study analysis for the integration factors.…”

Section: References Year Contributionmentioning

confidence: 99%

Security Threats and Research Challenges of IoT - A Review

Haque

Tasmin

2020

JEA

View full text Add to dashboard Cite

Internet of things (IoT) is the epitome of sustainable development. It has facilitated the development of smart systems, industrialization, and the state-of-the-art quality of life. IoT architecture is one of the essential baselines of understanding the widespread adoption. Security issues are very crucial for any technical infrastructure. Since IoT comprises heterogeneous devices, its security issues are diverse too. Various security attacks can be responsible for compromising confidentiality, integrity, and availability. In this paper, at first, the IoT architecture is described briefly. After that, the components of IoT are explained with perspective to various IoT based applications and services. Finally, various security issues, including recommended solutions, are elaborately described and the potential research challenges and future research directions.

show abstract

“…Among them, the last module Compute R(i) with formula (3); (8) if s i ∈ S, then (9) Update Q-value with formula ( 12); ( 10) else (11) Update Q-value with formula ( 13); (12) endfor ALGORITHM 1: ABR optimization algorithm. 6 Mobile Information Systems can provide the reference for the adolescent physical training directly according to the monitored data.…”

Section: System Implementationmentioning

confidence: 99%

“…To the best of our knowledge, the traditional ABR optimization algorithms cannot obtain the realtime network status to adapt to the dynamic network environment. On the contrary, the AI-based ABR optimization algorithms can adaptively adjust the network parameters and obtain the relatively optimal video transmission [6]. In terms of AI, the Reinforcement Learning (RL) [7] is the most popular representative.…”

Section: Introductionmentioning

confidence: 99%

Performance Optimization Mechanism of Adolescent Physical Training Based on Reinforcement Learning and Markov Model

Wei

Yuan

2020

Mobile Information Systems

View full text Add to dashboard Cite

Upon the teenagers’ failure to obtain the plenty of physical exercises at the growth and development stage, the related central nervous system is prone to degeneration and the physical fitness starts to decline gradually. In fact, through monitoring the exercise process real-timely and quantifying the exercise data, the adolescent physical training can be effectively conducted. For such process, it involves two issues, i.e., the real-time data monitoring and data quantification evaluation. Therefore, this paper proposes a novel method based on Reinforcement Learning (RL) and Markov model to monitor and evaluate the physical training effect. Meanwhile, the RL is used to optimize the adaptive bit rate of surveillance video and help the real-time data monitoring; the Markov model is employed to evaluate the health condition on the physical training. Finally, we develop a real-time monitoring system on exercise data and compare with the state-of-the-art mechanisms based on this system platform. The experimental results indicate that the proposed performance optimization mechanism can be more efficient to conduct the physical training. Particularly the average evaluation deviation rate based on Markov model is controlled within 0.16%.

show abstract

Addressing Security and Privacy Issues of IoT Using Blockchain Technology

Cited by 155 publications

References 23 publications

Combining Blockchains, Smart Contracts, and Complex Sensors Management Platform for Hyper-Connected SmartCities: An IoT Data Marketplace Use Case

Combining Blockchains, Smart Contracts, and Complex Sensors Management Platform for Hyper-Connected SmartCities: An IoT Data Marketplace Use Case

Security Threats and Research Challenges of IoT - A Review

Performance Optimization Mechanism of Adolescent Physical Training Based on Reinforcement Learning and Markov Model

Contact Info

Product

Resources

About