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Conference Papers Year : 2020

E-IOTA: an efficient and fast metamorphism for IOTA

Abstract

IOTA opened recently a new line of research in distributed ledgers area by targeting algorithms that ensure a high throughput for the transactions generated in IoT systems. Transactions are continuously appended to an acyclic structure called Tangle. Each new transaction selects and approves, as parents, two existing transactions who have not been approved yet (called Tips). Recent research indicates that, IOTA suffers from a Fairness Problem, where a part of submitted transactions might not be approved by new coming transactions. They are called Left-Behind transactions. Recently, G-IOTA has been proposed: by using the Left-Behind Protection mechanism, G-IOTA can fix the fairness problem. G-IOTA, however, needs additional computation resources for left-behind protection mechanism, which is not suitable for an energy-aware IoT system. Furthermore, both IOTA and G-IOTA suffer from a potential security defect. This side effect reduces the Unpredictability when transactions are appended to the tangle. Leaking the unpredictability, an adversary can easily induce the tendency of transactions appending to the tangle. This approach is called Prediction Attack. In this paper, we propose E-IOTA to solve the fairness problem and at the same time, guarantee the unpredictability of the tangle. Interestingly, our real scenario simulation shows that E-IOTA offers better performance efficiency compared to G-IOTA and even original IOTA. Simultaneously, E-IOTA retains the core data structure of IOTA, which makes E-IOTA be compatible with current IOTA implementation. Our solution can therefore be a perfect alternative solution for current IOTA.
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Dates and versions

hal-04035469 , version 1 (17-03-2023)

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Gewu Bu, Wassim Hana, Maria Potop-Butucaru. E-IOTA: an efficient and fast metamorphism for IOTA. 2020 2nd Conference on Blockchain Research & Applications for Innovative Networks and Services (BRAINS), Sep 2020, Paris, France. pp.9-16, ⟨10.1109/BRAINS49436.2020.9223294⟩. ⟨hal-04035469⟩
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