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International Symposium on Cyberspace Safety and Security

CSS 2019: Cyberspace Safety and Security pp 77–89Cite as

Intrusion Detection Traps within Live Network Environment

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11983))

Abstract

The aim of this project is the design and implementation of the solution able to detect an intruder in the internal network. We advocate that, instead of deploying additional fake systems in the corporate network, the production systems themselves should be instrumented to provide active defense capabilities. The proposed concept of traps can be implemented in any corporate production network, with little upfront work and little maintenance.

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References

  1. Bilge, L., Dumitras, T.: Before we knew it: an empirical study of zero-day attacks in the real world. In: Proceedings of the 2012 ACM Conference on Computer and Communications Security, Raleigh, North Carolina, USA, 16–18 October 2012, pp. 833–844 (2012)

    Google Scholar 

  2. Pomsathit, A.: Performance analysis of IDS with honey pot on new media broadcasting. In: 2017 International Conference on Circuits, Devices and Systems, 5–8 September 2017, pp. 201–204 (2017)

    Google Scholar 

  3. Nawrocki, M., Wahlisch, M., Schmidt, T., Keil, C., Schonfelder, J.: A Survey on Honeypot Software and Data Analysis, arXiv preprint, arXiv:1608.06249 (2016). https://arxiv.org/pdf/1608.06249.pdf. Accessed 12 June 2019

  4. Opencanary.readthedocs.io: OpenCanary — OpenCanary 0.1 documentation (2019). https://opencanary.readthedocs.io/en/latest. Accessed 12 June 2019

  5. Morris, A.: Kippo detect (2019). https://github.com/andrew-morris/kippo_detect. Accessed 12 June 2019

  6. Wolfvan: Cowrie Detect (2019). GitHub. https://github.com/wolfvan/Cowrie_Detect. Accessed 12 June 2019

  7. Campbell, R., Padayachee, K., Masombuka, T.: A survey of honeypot research: trends and opportunities. In: 2015 10th International Conference for Internet Technology and Secured Transactions (ICITST), pp. 208–212 (2015)

    Google Scholar 

  8. Wafi, H., Fiade, A., Hakiem, N., Bahaweres, R.: Implementation of a modern security systems honeypot: honey network on wireless networks. In: 2017 International Young Engineers Forum (YEF-ECE), pp. 91–96 (2017)

    Google Scholar 

  9. Artail, H., Safa, H., Sraj, M., Kuwatly, I., Al-Masri, Z.: A hybrid honeypot framework for improving intrusion detection systems in protecting organizational networks. Comput. Secur. 25(4), 274–288 (2006)

    Article  Google Scholar 

  10. Gaspari, F., Jajodia, S., Mancini, L.V., Panico, A.: AHEAD: a new architecture for active defense. In: Proceedings of the 2016 ACM Workshop on Automated Decision Making for Active Cyber Defense, Vienna, Austria, 24 October 2016, pp. 11–16 (2016). ISBN 978-1-4503-4566-8

    Google Scholar 

  11. Elastic.co: Powering Data Search, Log Analysis, Analytics | Elastic (2019). https://ww.elastic.co/products. Accessed 12 June 2019

  12. VMWare (2019). https://www.vmware.com/products/esxi-and-esx.html. Accessed 12 June 2019

  13. Ibm.com: Monitor file system activity with inotify (2019). https://www.ibm.com/developerworks/library/l-ubuntu-inotify/index.html. Accessed 12 June 2019

  14. Elastic.co: Filebeat: Lightweight Log Analysis & Elasticsearch | Elastic (2019). https://www.elastic.co/products/beats/filebeat. Accessed 12 June 2019

  15. Kaur, N., Singh, M.: Improved file system security through restrictive access. In: 2016 International Conference on Inventive Computation Technologies (ICICT), vol. 3 (2016). https://doi.org/10.1109/inventive.2016.7830207

  16. Gibbs, M.: Sharing with samba. Netw. World 20(30), 28 (2003). https://www.networkworld.com/article/2335460/sharing-with-samba.html. Accessed 12 June 2019

  17. Msdn.microsoft.com: FindFirstChangeNotification function (Windows) (2019). https://msdn.microsoft.com/enus/library/windows/desktop/aa364417(v=vs.85).aspx. Accessed 12 June 2019

  18. Stockman, M., Rein, R., Heile, A.: An open-source honeynet system to study system banner message effects on hackers. In: Proceedings of the 4th Annual ACM Conference on Research in Information Technology, Chicago, Illinois, USA, 30 September–03 October 2015, pp. 19–22 (2015). https://doi.org/10.1145/2808062.2808069. ISBN 978-1-4503-3836-3

  19. Gao, C., Lv, S., Wei, Y., Wang, Z., Liu, Z., Cheng, X.: An effective searchable symmetric encryption with enhanced security for mobile devices. IEEE Access 6, 38860–38869 (2018). ISSN 2169-3536

    Article  Google Scholar 

  20. Wang, C., Zhao, Z., Gong, L., Zhu, L., Liu, Z., Cheng, X.: A distributed anomaly detection system for in-vehicle network using HTM. IEEE Access 6(1), 9091–9098 (2018)

    Article  Google Scholar 

  21. Wang, C., Zhu, L., Gong, L., Zhao, Z., Yang, L., Liu, Z., Cheng, X.: Accurate sybil attack detection based on fine-grained physical channel information. Sensors 18(3), 878 (2018). ISSN 1424-8220

    Article  Google Scholar 

  22. Dinculeană, D., Cheng, X.: Vulnerabilities and limitations of MQTT protocol used between IoT devices. Appl. Sci. 9(5), 848 (2019)

    Article  Google Scholar 

  23. Shi F, Chen Z, Cheng X: Behaviour modelling and individual recognition of sonar transmitter for secure communication in UASNs. IEEE Access (2019). https://doi.org/10.1109/access.2019.2923059. Print ISSN 2169-3536, Online ISSN 2169-3536

  24. Men, J., Xu, G., Han, Z., Sun, Z., Zhou, X., Lian, W., Cheng, X.: Finding sands in the eyes: vulnerabilities discovery in IoT with EUFuzzer on human machine interface. IEEE Access 7, 103751–103759 (2019)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Faculty of Science and Technology, Middlesex University, London, UK

    Xiaochun Cheng & Matus Mihok

Authors
  1. Xiaochun Cheng
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  2. Matus Mihok
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Corresponding author

Correspondence to Xiaochun Cheng .

Editor information

Editors and Affiliations

  1. Rutgers University, Newark, NJ, USA

    Jaideep Vaidya

  2. Beihang University, Beijing, China

    Xiao Zhang

  3. Guangzhou University, Guangzhou, China

    Jin Li

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Cheng, X., Mihok, M. (2019). Intrusion Detection Traps within Live Network Environment. In: Vaidya, J., Zhang, X., Li, J. (eds) Cyberspace Safety and Security. CSS 2019. Lecture Notes in Computer Science(), vol 11983. Springer, Cham. https://doi.org/10.1007/978-3-030-37352-8_7

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  • DOI: https://doi.org/10.1007/978-3-030-37352-8_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37351-1

  • Online ISBN: 978-3-030-37352-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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