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Towards bitcoin transaction anonymity with recurrent attack prevention

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Abstract

The unprecedented financial and economic ledger performing bitcoin is continuously suffering from anonymity troubles. In bitcoin framework, users as nodes submit coins publicly in which transactions lead to privacy breaches resulting from recurrent attacks by malicious and/or dishonest nodes. Thereby, introducing anonymity into bitcoin transaction becomes an utmost necessity such that adversaries will find it relatively impossible to trace the transaction trajectories of the original bitcoin users. Thus, anonymity is seen to improve the difficulties in revealing the true identities of users, original transactions, transaction addresses and coins. Nonetheless, the perfectly honest condition of mixing services in the bitcoin framework is subjected to compromising attacks. Moreover, Lockmix model and other related mixing service schemes in recent decades are introduced to specifically secure bitcoin and to generally enhance the privacy and accountability framework of blockchain ecosystem. However, providing flexible anonymous and secure mixing services remain a challenge. Therefore, this paper adopts attribute-based signcryption scheme and further proposes Anonymix technique to obfuscates the true identity of clients and their coins prior to transacting with mixing services. The security protocol underlying the Anonymix technique overlays the existing Lockmix model technique to enhance flexibility and achieve complete anonymized bitcoin transaction. The proposed Anonymix technique is composed of properties such as unforgeability, confidentiality, fine-grained access control, authentication, privacy and public verifiability. Anonymix technique is compatible with bitcoin framework and supports trust requirement management for mixing services. Our theoretical analysis proves the Anonymix technique as secured against possible recurrent attacks in the bitcoin framework.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China [Grant No.61602097, No.61502087, and No.61472064]

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No funding was received to assist with the preparation of this manuscript.

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Authors and Affiliations

  1. C. K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana

    Daniel Adu-Gyamfi, Gabriel Kofi Armah & Dominic Kwasi Adom

  2. University of Electronic Science and Technology of China, Chengdu, 610054, China

    Daniel Adu-Gyamfi, Albert Kofi Kwansah Ansah, Seth Alornyo & Fengli Zhang

  3. University of Mines and Technology, Tarkwa, Ghana

    Albert Kofi Kwansah Ansah

  4. Koforidua Technical University, Koforidua, Ghana

    Seth Alornyo

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  1. Daniel Adu-Gyamfi
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  5. Dominic Kwasi Adom
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  6. Fengli Zhang
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Authors contributed equally to the study conception and design, material preparation, data collection and analysis, etc. The first draft of the manuscript was written by Daniel Adu-Gyamfi and all other authors commented on previous versions of the manuscript. All authors read and approved the final and revised manuscript for submission.

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Correspondence to Daniel Adu-Gyamfi.

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Adu-Gyamfi, D., Kwansah Ansah, A.K., Armah, G.K. et al. Towards bitcoin transaction anonymity with recurrent attack prevention. Int J Syst Assur Eng Manag 13, 1–17 (2022). https://doi.org/10.1007/s13198-021-01506-z

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