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A Survey on Security and Privacy Issues of Bitcoin
Open accessAbstract
Bitcoin is a popular cryptocurrency that records all transactions in a distributed append-only public ledger called blockchain. The security of Bitcoin heavily relies on the incentive-compatible proof-of-work (PoW) based distributed consensus protocol, which is run by the network nodes called miners. In exchange for the incentive, the miners are expected to maintain the blockchain honestly. Since its launch in 2009, Bitcoin economy has grown at an enormous rate, and it is now worth about 150 billions of dollars. This exponential growth in the market value of bitcoins motivate adversaries to exploit weaknesses for profit, and researchers to discover new vulnerabilities in the system, propose countermeasures, and predict upcoming trends. In this paper, we present a systematic survey that covers the security and privacy aspects of Bitcoin. We start by giving an overview of the Bitcoin system and its major components along with their functionality and interactions within the system. We review the existing vulnerabilities in Bitcoin and its major underlying technologies such as blockchain and PoW-based consensus protocol. These vulnerabilities lead to the execution of various security threats to the standard functionality of Bitcoin. We then investigate the feasibility and robustness of the state-of-the-art security solutions. Additionally, we discuss the current anonymity considerations in Bitcoin and the privacy-related threats to Bitcoin users along with the analysis of the existing privacy-preserving solutions. Finally, we summarize the critical open challenges, and we suggest directions for future research towards provisioning stringent security and privacy solutions for Bitcoin.
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“Besides, there are some other review papers on security and privacy in distributed ledgers such as [29], but they are mainly focused on bitcoin [30] or cryptocurrencies.”
From Privacy-Preserving Solutions for Blockchain: Review and Challenges (2019) · cites this paper as [29]
In the citing paper
“If a mining pool owns more than 50% of the network's computing power, then it is likely that those miners would be able to prevent the validation of proposed transactions, and consequently stop the transactions between users [73].”
From A Review of Blockchain Architecture and Consensus Protocols: Use Cases, Challenges, and Solutions (2019) · cites this paper as [73]
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“Due to this reason, such a kind of IIoT nodes commonly route their data through gateways by using non-P2P protocols like MQTT [30] or by making use of a fog [31] or edge computing infrastructure [32].”
From A Review on the Application of Blockchain to the Next Generation of Cybersecure Industry 4.0 Smart Factories (2019) · cites this paper as [32]
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Metadata
- Authors
- Conti, M., Sandeep Kumar, E., Lal, C., & Ruj, S.
- Affiliations
- University of Padua (IT)
- Manipal University Jaipur (IN)
- Indian Statistical Institute (IN)
- Venue
- IEEE Communications Surveys & Tutorials
- Published
- 2018
- Volume
- 20
- Issue
- 4
- Pages
- 3416-3452
- ISSN
- 1553-877X (ISSN-L)
- 2373-745X
- OpenAlex
- W2624307925
- Cited by
- 1,116
- References
- 173
- Citations by year
- 2026: 84 · 2025: 125 · 2024: 94 · 2023: 135 · 2022: 145 · 2021: 164 · 2020: 160 · 2019: 137 · 2018: 67
- FWCI
- 213.02
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- IEEE Communications Surveys & Tutorials (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Padua Research Archive (University of Padova) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Computer Networks and Communications › Cryptography and Data Security
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
- Keywords
- Bitcoin, cryptocurrency security, blockchain, proof-of-work, distributed consensus, mining, vulnerability (computer security), anonymity, privacy risks, security countermeasures
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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