Journal of Green Energy Research and Innovation
Quarterly

A Survey of Different Methods for Miner Detection and Challenges of Them in Power Industries

Document Type : Review article

Author

Mohammad Hossein shakoor

Department of Computer Engineering, Faculty of Engineering, Arak University, Arak, 38156-8-8349, Iran.

https://doi.org/10.61186/jgeri.1.3.96
Abstract
Cryptocurrency mining requires high consumption power. In recent years, because of the increase in the price of cryptocurrencies and due to the cheap price of electricity in Iran, mining Bitcoin and other cryptocurrencies has been very profitable. Some miners are legally engaged in cryptocurrency mining, but many miners do it illegally and without permission. Since cryptocurrency mining is an operation that consumes a lot of electricity, it is one of the reasons for the lack of electricity, especially in the summer season, and it has caused power outages and financial losses to various industries. In this paper, different methods of detection of illegal mining are reviewed. In this research, by collecting the small number of researches done in the world, a comprehensive study of this issue has been tried. The methods of identifying miners and related consumers are divided into several different categories. Some of them are based-on data mining and mostly to identify consumers who use the output of the converter for the miner device. The second category is related to people who illegally get their electricity from behind the meter or unmetered branches, which are much more difficult to identify than the first type. These methods will be mentioned more in this article. Finally, some suggestions are provided for better identification of these consumers. Furthermore, at the end of the paper, some renewable and new sources of electrical power are discussed for using as an electricity power for miners instead of traditional fossil fuel and gas planes.

Graphical Abstract

A Survey of Different Methods for Miner Detection and Challenges of Them in Power Industries

Highlights

 

  • Some aspects of Mining, blockchain, Hash, Cryptocurrency, Encryption and Decryption
  • A comprehensive study on different methods of miner detection
  • Some suggestions to enhance the power electricity consumption

Keywords

Power Consumption
Cryptocurrency Mining
Miner detection

 

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The ethical issues, including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, redundancy, have been completely observed by the authors.

 

Credit Authorship Contribution Statement

Mohammad Hossein Shakoor: Conceptualization, Formal analysis, Project administration, Supervision, Validation, Investigation, Methodology, Roles/Writing - original draft.

 

Bibliography

Mohammad Hossein Shakoor received the B.Sc. degree in Computer Engineering from Shiraz University, Shiraz, Iran, in 1998 and M.S. degree in computer architecture from Isfahan university, Isfahan, Iran, in 2003. He received Ph.D. in Artificial Intelligent of Computer engineering from Shiraz University, Shiraz, Iran in 2016. His research interests include Texture Classification, Pattern Recognition and Computer Vision.

 

Citation

M. H. Shakoor, " A Survey of Different Methods for Miner Detection and Challenges of ‎Them in Power Industries," Journal of Green Energy Research and Innovation, vol. 1, no. 3, pp. 96-109, 2024.

  1. Nakamoto, “Bitcoin: A Peer-to-Peer Electronic Cash System,” 2008.
  2. O'Dwyer, and D. Malone, "Bitcoin Mining and its Energy Footprint," 25th IET Irish Signals & Systems Conference 2014 and 2014 China-Ireland International Conference on Information and Communications Technologies, pp. 280-285, 2014.
  3. T. Courtois, M. Grajek, and R. Naik, "The Unreasonable Fundamental in Certitudes Behind Bitcoin Mining," Arxiv Preprint Arxiv, 1310,7935, 2013.
  4. J. O’Dwyer, and D. Malone, ‘‘Bitcoin Mining and Its Energy Footprint,’’ 25th IET Irish Signals & Systems Conference 2014 and 2014 China-Ireland International Conference on Information and Communications Technologies (ISSC 2014/CIICT 2014), p. 280 – 285, 2014.
  5. Amiri, and H. Askari, "Illegal Miner Detection Based on Pattern Mining: a Practical Approach," Journal of Computing and Security, vol. 9, no. 2, pp. 1-10, 2022.
  6. Dindar, and O. G¨ul, "The Detection of Illicit Cryptocurrency Mining Farms with Innovative Approaches for the Prevention of Electricity Theft," Energy & Environment, vol. 33, no. 8, pp. 1663-1678, 2022.
  7. Jiang, R. Lu, et al., "Energy-Theft Detection Issues for Advanced Metering Infrastructure in Smart Grid," Tsinghua Science and Technology, vol. 19, no. 2, pp. 105-120, 2014.
  8. Rahimi, A. Shahrestani, et al., "Filter Based Time-Series Anomaly Detection in AMI using AI Approaches," 2021 5th International Conference on Internet of Things and Applications (Iot), pp. 1-6, 2021.
  9. Chahla, H. Snoussi, L. Merghem, and M. Esseghir, "A Deep Learning Approach for Anomaly Detection and Prediction in Power Consumption Data," Energy Efficiency, vol. 13, no. 8, pp. 1633-1651, 2020.
  10. Ouyang, X. Sun, J. Chen, D. Yue, and T. Zhang, "Multi-View Stacking Ensemble for Power Consumption Anomaly Detection in the Context of Industrial Internet of Things," IEEE Access, vol. 6, pp. 9623-9631, 2018.
  11. Li, K. Zhang, J. Liu, H. Gong, and Z. Zhang, "Blockchain-Based Anomaly Detection of Electricity Consumption in Smart Grids," Pattern Recognition Letters, vol. 138, pp. 476-482, 2020.
  12. Claise, B. Trammell, and P. Aitken, Specification of the IP Flow Information Export (IPFIX) Protocol, RFC 7011. IETF. 2013.
  13. Almalaq, S. Albadran, and M. A. Mohamed, "An Adoptive Miner-Misuse Based Online Anomaly Detection Approach in the Power System: An Optimum Reinforcement Learning Method," Mathematics, vol.11, no.4, pp. 884-884, 2023.
  14. Livadas, R. Walsh, D. Lapsley, and W. T. Strayer, "Usilng Machine Learning Technliques to Identify Botnet Traffic," 2006 31st IEEE Conference on Local Computer Networks, Tampa, pp. 967-974, 2006.
  15. Vesely, and M. Zadnik, "How to Detect Crypto Currency Miners? by Traffic Forensics," Digital Investigation, vol. 31, 100884, 2019.
  16. A. Kroll, I. C. Davey, and E. W. Felten "The Economics of Bitcoin Mining, or Bitcoin in the Presence of Adversaries," The 12th Workshop on the Economics of Information Security, Washington DC, 11-12 June 2013.
  17. Lewenberg, Y. Bachrach, Y. Sompolinsky, A. Zohar, and J. S. Rosenschein, "Bitcoin Mining Pools: A Cooperative Game Theoretic Analysis," AAMAS 15 Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, pp. 919–927, 2015.
  18. Juels, A. Kosba, and E. Shi, "The Ring of Gyges: Investigating the Future of Criminal Smart Contracts," Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, pp. 283-295, 2016.
  19. Y. Huang, and H. Dharmdasani, et al., "Botcoin: Monetizing Stolen Cycles," Proceedings of the 2014 Network and Distributed System Security Symposium. NDSS, 2014.
  20. T. Ali, D. Clarke, and P. McCorry, "Bitcoin:Perils of an Unregulated Global P2P Currency," Cambridge International Workshop on Security Protocols, pp. 294-306, 2015.
  21. Solaymani, "A Review on Energy and Renewable Energy Policies in Iran," Sustainability, vol. 13, no. 13, p.7328, 2021.
  22. Zakir al-Hosseini, "Data Security," Nas Publications, fifth Edition, 2012.
  23. Feng, S. Xu, et al., "Anomaly Detection for Electricity Consumption in Cloud Computing: Framework, Methods, Applications, and Challenges," EURASIP Journal on Wireless Communications and Networking, vol. 2020, no. 1, p.194, 2020.
  24. Hofstede, P. Celeda, et al., "Flow Monitoring Explained: from Packet Capture to Data Analysis with Netflow and Ipfix," IEEE Communications Surveys & Tutorials, vol. 16, no. 4, pp. 2037-2064, 2014.
  25. T. Ali, P. McCorry, P. H. J. Lee, and F. Hao, "Zombiecoin: Powering Next Generation Botnets with Bitcoin," Financial Cryptography and Data Security Springer, pp. 34-48, 2015.
  26. Liang, C. B. Saner, et al., "Sustainable Energy-Based Cryptocurrency Mining," 2022 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia), pp, 789-793, 2022.
  27. T. McDoald, K. S. Hayibo, F. Hafting, and J. M. Pearce, "Economics of Open-Source Solar Photovoltaic Powered Cryptocurrency Mining,", Available at SSRN 4205879, 2023.
  28. Rorich, K. Moloi, T. F. Mazibuko, and I. E. Davidson, "Cryptocurrency Mining Powered by Renewable Energy Using A DC-DC Connection,"31st Southern African Universities Power Engineering Conference (SAUPEC), pp. 1-7, 2023.
Journal of Green Energy Research and Innovation
Volume 1, Issue 3
Summer 2024
Pages 96-109

  • Receive Date 20 January 2024
  • Revise Date 20 February 2024
  • Accept Date 02 March 2024
  • Publish Date 01 September 2024

Home

Guide for Authors

Submit Manuscript

Reviewers

Contact Us