Iota Tangle: A cryptocurrency to communicate Internet-of-Things data

Silvano, Wellington Fernandes; Marcelino, Roderval

doi:10.1016/j.future.2020.05.047

Cited by 166 publications

(71 citation statements)

References 15 publications

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“…The related findings from the Giacomini–White Test confirms the successful performances by the AEN infrastructure. Additionally, the methods in [102] , and [110] took places in the best performance (with the AEN) for the PASCAL dataset while the method [103] had place in the best performance (with the AEN) for the PhysioNet dataset.…”

Section: Evaluation and Discussionmentioning

confidence: 98%

“…The central system stores twin data over the cloud environment so that it regularly checks and any data discrepancy corresponding to possible attacks or data errors is detected accordingly. Additionally, the central system stores data in terms of Tangle data model, which was introduced by the IOTA, as focusing on Directed Acyclic Graph (DAG) [101] , [102] . Here, actions by users are checked in the context of the data history shared with all authenticated peers (mobile devices).…”

Section: Methodsmentioning

confidence: 99%

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Diagnosis of heart diseases by a secure Internet of Health Things system based on Autoencoder Deep Neural Network

Deperlioğlu

Köse

Gupta

et al. 2020

Computer Communications

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Objective of this study is to introduce a secure IoHT system, which acts as a clinical decision support system with the diagnosis of cardiovascular diseases. In this sense, it was emphasized that the accuracy rate of diagnosis (classification) can be improved via deep learning algorithms, by needing no hybrid-complex models, and a secure data processing can be achieved with a multi-authentication and Tangle based approach. In detail, heart sounds were classified with Autoencoder Neural Networks (AEN) and the IoHT system was built for supporting doctors in real-time. For developing the diagnosis infrastructure by the AEN, PASCAL B-Training and Physiobank-PhysioNet A-Training heart sound datasets were used accordingly. For the PASCAL dataset, the AEN provided a diagnosis-classification performance with the accuracy of 100%, sensitivity of 100%, and the specificity of 100% whereas the rates were respectively 99.8%, 99.65%, and 99.13% for the PhysioNet dataset. It was seen that the findings by the developed AEN based solution were better than the alternative solutions from the literature. Additionally, usability of the whole IoHT system was found positive by the doctors, and according to the 479 real-case applications, the system was able to achieve accuracy rates of 96.03% for normal heart sounds, 91.91% for extrasystole, and 90.11% for murmur. In terms of security approach, the system was also robust against several attacking methods including synthetic data impute as well as trying to penetrating to the system via central system or mobile devices.

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Section: Evaluation and Discussionmentioning

confidence: 98%

Section: Methodsmentioning

confidence: 99%

Diagnosis of heart diseases by a secure Internet of Health Things system based on Autoencoder Deep Neural Network

Deperlioğlu

Köse

Gupta

et al. 2020

Computer Communications

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“…IOTA is an open-source DLT protocol using a nonlinear directed acyclic graph to store data in the IOTA Tangle [31]. The IOTA Tangle is designed for applications in the Internet of things [32], offers high transaction throughput, and charges no transaction fees. In the IOTA network, a transaction contains an address.…”

Section: Distributed Ledger Technologymentioning

confidence: 99%

When Data Fly: An Open Data Trading System in Vehicular Ad Hoc Networks

et al. 2021

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Communication between vehicles and their environment (i.e., vehicle-to-everything or V2X communication) in vehicular ad hoc networks (VANETs) has become of particular importance for smart cities. However, economic challenges, such as the cost incurred by data sharing (e.g., due to power consumption), hinder the integration of data sharing in open systems into smart city applications, such as dynamic environmental zones. Moving from open data sharing to open data trading can address the economic challenges and incentivize vehicle drivers to share their data. In this context, integrating distributed ledger technology (DLT) into open systems for data trading is promising for reducing the transaction cost of payments in data trading, avoiding dependencies on third parties, and guaranteeing openness. However, because the integration of DLT conflicts with the short available communication time between fast moving objects in VANETs, it remains unclear how open data trading in VANETs using DLT should be designed to be viable. In this work, we present a system design for data trading in VANETs using DLT. We measure the required communication time for data trading between a vehicle and a roadside unit in a real scenario and estimate the associated cost. Our results show that the proposed system design is technically feasible and economically viable.

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“…As discussed in [5], the main drawback of current MAM channel implementation stands behind the need to store messages in the IOTA permanent node to prevent deletion during snapshot processes [31]. This node requires large storage, bandwidth, and high speed, so it cannot be hosted on devices with small computational resources.…”

Section: B Distributed Ledger Vehicular Pki: Iota-vpkimentioning

confidence: 99%

“…However, to better explain the timing compatibility between public and private IOTA instances, it is worth discussing the concept of approved transactions. The full process of attaching a transaction to the Tangle is detailed in [31]. At the end of such process, the new transaction is called a tip, i.e.…”

Section: A Experimental Settingsmentioning

confidence: 99%

Securing Seaport Logistic Vehicles Using a Distributed Ledger-Based Credential Management System

Tesei

Lattuca

Tardo

et al. 2021

IEEE Open J. Veh. Technol.

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Major maritime carriers are globally demanding improvements in the efficiency of port operations. Cargo carried by ships must be loaded and unloaded quickly with minimal stopover time in the port. This requirement mandates seaports to deploy cutting-edge technology to the port area so that logistic processes are increasingly efficient and reliable. In this scenario, the attack surface of such critical infrastructure is growing very rapidly and advanced security techniques must be deployed to enforce a high attack resilience. A Distributed Ledger-based Credential Management System exploiting a Distributed Ledger Technology (DLT) to enable transparent and real-time tracking of logistic vehicles and cargos within a terminal is presented in this paper. Based on a customization of Vehicular Ad-Hoc Network (VANET) security standards, the proposed scheme provides authentication, authorization, and revocation capabilities to promptly exclude misbehaving logistic vehicles from the system, while maintaining an immutable record of all the logistic vehicles' activity. The laboratory validation demonstrates that the delay of the devised scheme is not dependent on the quay area capacity, thus being applicable in seaports of any size. Furthermore, the effectiveness of the solution is demonstrated with the field trial results obtained with the EU Horizon 2020 COREALIS project testbed deployed in the Port of Livorno.

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Iota Tangle: A cryptocurrency to communicate Internet-of-Things data

Cited by 166 publications

References 15 publications

Diagnosis of heart diseases by a secure Internet of Health Things system based on Autoencoder Deep Neural Network

Diagnosis of heart diseases by a secure Internet of Health Things system based on Autoencoder Deep Neural Network

When Data Fly: An Open Data Trading System in Vehicular Ad Hoc Networks

Securing Seaport Logistic Vehicles Using a Distributed Ledger-Based Credential Management System

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