The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Analysis of Blockchain Selfish Mining Attacks
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Integrity signals
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In the citing paper
“For instance, a participant in a blockchain-based system may expect that a miner will always act in accordance with the consensus algorithm of that system but empirical research has shown that miners can deviate from the standard protocol and engage in 'selfish mining' 27 [94].”
From Blockchain as a confidence machine: The problem of trust & challenges of governance (2020) · cites this paper as [94]
Citations
Cites
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Majority is not enough: bitcoin mining is vulnerable
Eyal, I., & Sirer, E. G. (2018) · Communications of the ACM · doi:10.1145/3212998 · Cited by 742
Stubborn Mining: Generalizing Selfish Mining and Combining with an Eclipse Attack
Nayak, K., Kumar, S., Miller, A., & Shi, E. (2016) · 2016 IEEE European Symposium on Security and Privacy (EuroS&P) · doi:10.1109/eurosp.2016.32 · Cited by 481
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Li, W., Andreina, S., Bohli, J.-M., & Karame, G. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-67816-0_17 · Cited by 264
Research works printed but not linked: 1
- Kozlowski, P., Kedziora, M., Marianski, A., Jozwiak, I.: Implementation of Research on the Feasibility of a Sybil Attacks in Blockchain Networks, ICSAI 2019 – in review (2019)
Cited by
Blockchain as a confidence machine: The problem of trust & challenges of governance
De Filippi, P., Mannan, M., & Reijers, W. (2020) · Technology in Society · doi:10.1016/j.techsoc.2020.101284 · Cited by 406
A survey of DeFi security: Challenges and opportunities
Li, W., Bu, J., Li, X., Peng, H.-L., Niu, Y., & Zhang, Y. (2022) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2022.10.028 · Cited by 91
A Review on Blockchain Technology, Current Challenges, and AI-Driven Solutions
Abdelhamid, M. M., Sliman, L., Djemaa, R. B., & Perboli, G. (2024) · ACM Computing Surveys · doi:10.1145/3700641 · Cited by 46
Chen, C., Chen, X., Yu, J., Wu, W., & Wu, D. (2020) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2020.3038943 · Cited by 44
Communications Security in Industry X: A Survey
Ahmad, I., Rodriguez, F., Kumar, T., Suomalainen, J., Jagatheesaperumal, S. K., Walter, S., Asghar, M. Z., Li, G., Papakonstantinou, N., Ylianttila, M., et al. (2024) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2024.3356076 · Cited by 43
A review on deep anomaly detection in blockchain
Mounnan, O., Manad, O., Boubchir, L., Mouatasim, A. E., & Daâchi, B. (2024) · Blockchain Research and Applications · doi:10.1016/j.bcra.2024.100227 · Cited by 34
Islam, M. S., Rahman, M. A., Ameedeen, M. A., Ajra, H., Ismail, Z. B., & Zain, J. M. (2023) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2023.028687 · Cited by 28
Beyond Flight: Enhancing the Internet of Drones with Blockchain Technologies
Tychola, K. A., Voulgaridis, K., & Λάγκας, Θ. (2024) · Drones · doi:10.3390/drones8060219 · Cited by 28
Woznica, A., & Kędziora, M. (2022) · Computer Science and Information Systems · doi:10.2298/csis210507002w · Cited by 22
Self-citationA New Theoretical Framework of Pyramid Markov Processes for Blockchain Selfish Mining
Li, Q., Chang, Y.-X., Wu, X., & Zhang, G. (2021) · Journal of Systems Science and Systems Engineering · doi:10.1007/s11518-021-5515-3 · Cited by 19
Security of Blockchain Distributed Ledger Consensus Mechanism in Context of the Sybil Attack
Kędziora, M., Kozłowski, P., & Jóźwiak, P. P. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-55789-8_36 · Cited by 16
Self-citationKędziora, M., Pieprzka, D., Jóźwiak, I. J., Liu, Y., & Song, H. (2022) · Journal of Information and Telecommunication · doi:10.1080/24751839.2022.2122301 · Cited by 16
Self-citationRakkini, M. J. J., & Geetha, K. (2021) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-021-03527-9 · Cited by 13
Thakur, A., Ranga, V., & Agarwal, R. (2025) · Transactions on Emerging Telecommunications Technologies · doi:10.1002/ett.70087 · Cited by 12
Towards Detection of Selfish Mining Using Machine Learning
Peterson, M., Andel, T. R., & Benton, R. (2022) · International Conference on Cyber Warfare and Security · doi:10.34190/iccws.17.1.15 · Cited by 11
Panwar, A., & Bhatnagar, V. (2021) · Algorithms for intelligent systems · doi:10.1007/978-981-33-4893-6_46 · Cited by 11
Space-Efficient Storage Structure of Blockchain Transactions Supporting Secure Verification
Feng, X., Ma, J., Wang, H., Wen, S., Xiang, Y., & Miao, Y. (2022) · IEEE Transactions on Cloud Computing · doi:10.1109/tcc.2022.3220664 · Cited by 9
Kędziora, M., Pieprzka, D., Jóźwiak, I. J., Liu, Y., & Song, H. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-63007-2_50 · Cited by 7
Self-citationRakkini, M. J. J., & Geetha, K. (2022) · IEEE Mysore Sub Section International Conference (MysuruCon) · doi:10.1109/mysurucon55714.2022.9972484 · Cited by 4
Q‐Learning model for selfish miners with optional stopping theorem for honest miners
Rakkini, M. J. J., & Geetha, K. (2023) · International Transactions in Operational Research · doi:10.1111/itor.13359 · Cited by 3
Sridevi, S., Kumar, B. V., & Karpagam, G. R. (2026) · Scientific Reports · doi:10.1038/s41598-025-34833-3 · Cited by 1
Towards Realizing Lightweight Consensus Protocol for IoT
Sharma, A., & Kataria, S. (2023) · Asian Conference on Innovation in Technology (ASIANCON) · doi:10.1109/asiancon58793.2023.10270590 · Cited by 1
Prevention of Selfish Mining Attacks in Blockchain-Enabled Smart City Networks
Kalinin, M., & Konoplev, A. S. (2025) · International Russian Smart Industry Conference (SmartIndustryCon) · doi:10.1109/smartindustrycon65166.2025.10986235 · Cited by 1
Protecting Smart City Blockchain Systems from Selfish Mining Attacks
Kalinin, M., & Konoplev, A. S. (2025) · Automatic Control and Computer Sciences · doi:10.3103/s0146411625701044
Metadata
- Authors
- Kędziora, M., Kozłowski, P., Szczepanik, M., & Jóźwiak, P.
- Affiliations
- Wrocław University of Science and Technology (PL)
- Venue
- Advances in Intelligent Systems and Computing
- Publisher
- Springer International Publishing
- Published
- 2019-09-05
- Pages
- 231-240
- ISSN
- 2194-5357 (ISSN-L)
- 2194-5365
- OpenAlex
- W2972132048
- Cited by
- 24
- References
- 12
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 4 · 2023: 3 · 2022: 6 · 2021: 3 · 2020: 4
- FWCI
- 2.55
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Advances in intelligent systems and computing (publishedVersion)
- 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
- selfish mining, blockchain attacks, proof-of-work, cryptocurrency mining
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.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
