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Conference Papers Year : 2019

G-IOTA: Fair and confidence aware tangle


This paper proposes strategies to improve the IOTA tangle in terms of resilience to splitting attacks. Our contribution is two fold. First, we define the notion of confidence fairness for tips selection algorithms to guarantee the first approval for all honest tips. Then, we analyze IOTA-tangle from the point of view of confidence fairness and identify its drawbacks. Second, we propose a new selection mechanism, G-IOTA, that targets to protect tips left behind. G-IOTA therefore has a good confidence fairness. G-IOTA lets honest transactions increase their confidence efficiently. Furthermore, G-IOTA includes an incentive mechanism for users who respect the algorithm and punishes conflicting transactions. Additionally, G-IOTA provides a mutual supervision mechanism that reduces the benefits of speculative and lazy behaviours. To evaluate the performances of G-IOTA, we implemented G-IOTA and compared it with the original IOTA. In our simulations, G-IOTA presents more confirmed transactions and fewer left-behind transactions than the original IOTA.

Dates and versions

hal-02443142 , version 1 (16-01-2020)



Gewu Bu, Önder Gürcan, Maria Potop-Butucaru. G-IOTA: Fair and confidence aware tangle. INFOCOM Workshops, Apr 2019, Paris, France. pp.644-649, ⟨10.1109/INFCOMW.2019.8845163⟩. ⟨hal-02443142⟩
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