Skip to main content

HyperSec: Visual Analytics for Blockchain Security Monitoring

  • Conference paper
  • First Online:
ICT Systems Security and Privacy Protection (SEC 2021)

Abstract

Today, permissioned blockchains are being adopted by large organizations for business critical operations. Consequently, they are subject to attacks by malicious actors. Researchers have discovered and enumerated a number of attacks that could threaten availability, integrity and confidentiality of blockchain data. However, currently it remains difficult to detect these attacks. We argue that security experts need appropriate visualizations to assist them in detecting attacks on blockchain networks. To achieve this, we develop HyperSec, a visual analytics monitoring tool that provides relevant information at a glance to detect ongoing attacks on Hyperledger Fabric. For evaluation, we connect the HyperSec prototype to a Hyperledger Fabric test network. The results show that common attacks on Fabric can be detected by a security expert using HyperSec’s visualizations.

B. Putz and F. Böhm—Contributed equally to this manuscript.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    https://github.com/sigma67/hypersec.

  2. 2.

    https://airbnb.io/visx/.

  3. 3.

    https://jira.hyperledger.org.

  4. 4.

    https://github.com/sivachokkapu/revive-cc.

References

  1. Baset, S., Prehoda, B.: Hyperledger Labs Blockchain Analyzer, March 2021. https://github.com/hyperledger-labs-archives/blockchain-analyzer. 30 May 2019

  2. Ben-Asher, N., Gonzalez, C.: Effects of cyber security knowledge on attack detection. Comput. Hum. Behav. 48, 51–61 (2015). https://doi.org/10.1016/j.chb.2015.01.039

    Article  Google Scholar 

  3. Bogner, A.: Seeing is understanding: anomaly detection in blockchains with visualized features. In: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing, New York, NY, USA, pp. 5–8. ACM (2017). https://doi.org/10.1145/3123024.3123157

  4. Boshmaf, Y., Al Jawaheri, H., Al Sabah, M.: BlockTag: design and applications of a tagging system for blockchain analysis. In: Dhillon, G., Karlsson, F., Hedström, K., Zúquete, A. (eds.) SEC 2019. IAICT, vol. 562, pp. 299–313. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22312-0_21

    Chapter  Google Scholar 

  5. Calder, A.: NIST Cybersecurity Framework (2018). https://doi.org/10.2307/j.ctv4cbhfx

  6. Chi, E.: A taxonomy of visualization techniques using the data state reference model. In: Proceedings of the IEEE Symposium on Information Visualization 2000, pp. 69–75. IEEE Computer Society (2000). https://doi.org/10.1109/INFVIS.2000.885092

  7. Dabholkar, A., Saraswat, V.: Ripping the fabric: attacks and mitigations on hyperledger fabric. In: Shankar Sriram, V.S., Subramaniyaswamy, V., Sasikaladevi, N., Zhang, L., Batten, L., Li, G. (eds.) ATIS 2019. CCIS, vol. 1116, pp. 300–311. Springer, Singapore (2019). https://doi.org/10.1007/978-981-15-0871-4_24

    Chapter  Google Scholar 

  8. Di Battista, G., Di Donato, V., Patrignani, M., Pizzonia, M., Roselli, V., Tamassia, R.: Bitconeview: visualization of flows in the bitcoin transaction graph. In: 2015 IEEE Symposium on Visualization for Cyber Security (VizSec), pp. 1–8. IEEE (2015). https://doi.org/10.1109/VIZSEC.2015.7312773

  9. Homoliak, I., Venugopalan, S., Reijsbergen, D., Hum, Q., Schumi, R., Szalachowski, P.: The security reference architecture for blockchains: towards a standardized model for studying vulnerabilities, threats, and defenses. IEEE Commun. Surv. Tutor. (2020). https://doi.org/10.1109/COMST.2020.3033665

    Article  Google Scholar 

  10. Jensen, T., Hedman, J., Henningsson, S.: How TradeLens delivers business value with blockchain technology. MIS Quart. Execut. (2019). https://doi.org/10.17705/2msqe.00018

  11. Kacherginsky, P.: Attacking and Defending Blockchain Nodes. In: DEFCON 2020, p. 54 (2020)

    Google Scholar 

  12. Keim, D., Andrienko, G., Fekete, J.-D., Görg, C., Kohlhammer, J., Melançon, G.: Visual analytics: definition, process, and challenges. In: Kerren, A., Stasko, J.T., Fekete, J.-D., North, C. (eds.) Information Visualization. LNCS, vol. 4950, pp. 154–175. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-70956-5_7. iSSN: 03029743

    Chapter  Google Scholar 

  13. McGinn, D., Birch, D., Akroyd, D., Molina-Solana, M., Guo, Y., Knottenbelt, W.J.: Visualizing dynamic bitcoin transaction patterns. Big Data 4(2), 109–119 (2016). https://doi.org/10.1089/big.2015.0056

    Article  Google Scholar 

  14. Meyer, M., Sedlmair, M., Quinan, P.S., Munzner, T.: The nested blocks and guidelines model. Inf. Vis. 14(3), 234–249 (2015). https://doi.org/10.1177/1473871613510429

    Article  Google Scholar 

  15. Miksch, S., Aigner, W.: A matter of time: applying a data-users-tasks design triangle to visual analytics of time-oriented data. Comput. Graph. 38, 286–290 (2014). https://doi.org/10.1016/j.cag.2013.11.002

    Article  Google Scholar 

  16. Munzner, T.: A nested model for visualization design and validation. IEEE Trans. Visual Comput. Graphics 15(6), 921–928 (2009). https://doi.org/10.1109/TVCG.2009.111

    Article  Google Scholar 

  17. Putz, B., Pernul, G.: Detecting blockchain security threats. In: 2020 IEEE International Conference on Blockchain (Blockchain), pp. 313–320. IEEE (2020). https://doi.org/10.1109/Blockchain50366.2020.00046

  18. Putz, B., Pernul, G.: Trust factors and insider threats in permissioned distributed ledgers. In: Hameurlain, A., Wagner, R. (eds.) Transactions on Large-Scale Data- and Knowledge-Centered Systems XLII. LNCS, vol. 11860, pp. 25–50. Springer, Heidelberg (2019). https://doi.org/10.1007/978-3-662-60531-8_2

    Chapter  Google Scholar 

  19. Sundara, T., Gaputra, I., Aulia, S.: Study on blockchain visualization. Int. J. Inform. Visual. 1(3), 76–82 (2017). https://doi.org/10.30630/joiv.1.3.23

    Article  Google Scholar 

  20. The Linux Foundation: DLTLabs Case Study - Hyperledger (2020). https://www.hyperledger.org/learn/publications/dltlabs-case-study

  21. The Linux Foundation: Hyperledger Explorer (2020). https://www.hyperledger.org/use/explorer

  22. The Linux Foundation: Hyperledger Fabric 2.3 Documentation (2020). https://hyperledger-fabric.readthedocs.io/en/release-2.3

  23. Tovanich, N., Heulot, N., Fekete, J., Isenberg, P.: Visualization of blockchain data: a systematic review. IEEE Trans. Visual. Compute. Graphics 1 (2019). https://doi.org/10.1109/TVCG.2019.2963018

  24. Zheng, P., Zheng, Z., Luo, X., Chen, X., Liu, X.: A detailed and real-time performance monitoring framework for blockchain systems. In: Proceedings - International Conference on Software Engineering (2018). https://doi.org/10.1145/3183519.3183546, iSSN: 02705257

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Benedikt Putz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Putz, B., Böhm, F., Pernul, G. (2021). HyperSec: Visual Analytics for Blockchain Security Monitoring. In: Jøsang, A., Futcher, L., Hagen, J. (eds) ICT Systems Security and Privacy Protection. SEC 2021. IFIP Advances in Information and Communication Technology, vol 625. Springer, Cham. https://doi.org/10.1007/978-3-030-78120-0_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-78120-0_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78119-4

  • Online ISBN: 978-3-030-78120-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics