Skip to main content
SpringerLink
Log in
Book cover

International Conference on Collaborative Computing: Networking, Applications and Worksharing

CollaborateCom 2018: Collaborative Computing: Networking, Applications and Worksharing pp 222–232Cite as

Important Member Discovery of Attribution Trace Based on Relevant Circle (Short Paper)

  • Conference paper
  • First Online:

  • 852 Accesses

Abstract

Cyberspace attack is a persistent problem since the existing of internet. Among many attack defense measures, collecting information about the network attacker and his organization is a promising means to keep the cyberspace security. The exposing of attackers halts their further operation. To profile them, we combine these retrieved attack related information pieces to form a trace network. In this attributional trace network, distinguishing the importance of different trace information pieces will help in mining more unknown information pieces about the organizational community we care about. In this paper, we propose to adopt relevant circle to locate these more important vertices in the trace network. The algorithm first uses Depth-first search to traverse all vertices in the trace network. Then it discovers and refines relevant circles derived from this network tree, the rank score is calculated based on these relevant circles. Finally, we use the classical 911 covert network dataset to validate our approach.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Learn about institutional subscriptions

References

  1. Butt, W.H., Akram, M.U., Khan, S.A., Javed, M.Y.: Covert network analysis for key player detection and event prediction using a hybrid classifier. Sci. World J. 2014, 13 (2014). 615431

    Article  Google Scholar 

  2. Chitrapura, K.P., Kashyap, S.R.: Node ranking in labeled directed graphs. In: Thirteenth ACM International Conference on Information and Knowledge Management, pp. 597–606 (2004)

    Google Scholar 

  3. Dasgupta, S., Prakash, C.: Intelligent detection of influential nodes in networks. In: International Conference on Electrical, Electronics, and Optimization Techniques (2016)

    Google Scholar 

  4. Farley, J.D.: Breaking Al Qaeda cells: a mathematical analysis of counterterrorism operations (a guide for risk assessment and decision making). Stud. Conflict Terrorism 26(6), 399–411 (2003)

    Article  Google Scholar 

  5. Ferrara, E., Meo, P.D., Catanese, S., Fiumara, G.: Detecting criminal organizations in mobile phone networks. Expert Syst. Appl. 41(13), 5733–5750 (2014)

    Article  Google Scholar 

  6. Halappanavar, M., Sathanur, A.V., Nandi, A.K.: Accelerating the mining of influential nodes in complex networks through community detection, pp. 64–71 (2016)

    Google Scholar 

  7. Krebs, V.E.: Mapping networks of terrorist cells, pp. 43–52 (2002)

    Google Scholar 

  8. Langohr, L., Toivonen, H.: Finding representative nodes in probabilistic graphs. In: Berthold, M.R. (ed.) Bisociative Knowledge Discovery. LNCS (LNAI), vol. 7250, pp. 218–229. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31830-6_15

    Chapter  Google Scholar 

  9. Memon, B.R.: Identifying important nodes in weighted covert networks using generalized centrality measures. In: Intelligence and Security Informatics Conference, pp. 131–140 (2012)

    Google Scholar 

  10. Sheikhahmadi, A., Nematbakhsh, M.A., Shokrollahi, A.: Improving detection of influential nodes in complex networks. Physica A Stat. Mech. Appl. 436, 833–845 (2015)

    Article  Google Scholar 

  11. Singer, P.W.: Cybersecurity and Cyberwar: What Everyone Needs to Know. Oxford University Press, Oxford (2014)

    Google Scholar 

  12. Taha, K., Yoo, P.D.: SIIMCO: a forensic investigation tool for identifying the influential members of a criminal organization. IEEE Trans. Inf. Forensics Secur. 11(4), 811–822 (2016)

    Google Scholar 

  13. Taha, K., Yoo, P.D.: Using the spanning tree of a criminal network for identifying its leaders. IEEE Trans. Inf. Forensics Secur. PP(99), 1 (2017)

    Google Scholar 

  14. Wiil, U.K., Gniadek, J., Memon, N.: Measuring link importance in terrorist networks. In: International Conference on Advances in Social Networks Analysis and Mining, pp. 225–232 (2010)

    Google Scholar 

  15. Xu, J., Yun, X., Zhang, Y., Sang, Y., Cheng, Z.: NetworkTrace: probabilistic relevant pattern recognition approach to attribution trace analysis. In: 2017 IEEE Trustcom/BigDataSE/ICESS, pp. 691–698, August 2017. https://doi.org/10.1109/Trustcom/BigDataSE/ICESS.2017.301

  16. Xu, J.J., Chen, H.: Crimenet explorer: a framework for criminal network knowledge discovery. ACM Trans. Inf. Syst. 23(2), 201–226 (2005)

    Article  MathSciNet  Google Scholar 

  17. Wei, Z., Yang, S., Wenwu, C.: A game model of APT attack for distributed network. In: Xhafa, F., Caballé, S., Barolli, L. (eds.) 3PGCIC 2017. LNDECT, vol. 13, pp. 224–234. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-69835-9_21

    Chapter  Google Scholar 

Download references

Acknowledgment

This work was supported by the National Natural Science Foundation of China (No. U1736218).

Author information

Authors and Affiliations

  1. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China

    Jian Xu, Xiaochun Yun, Yongzheng Zhang & Zhenyu Cheng

  2. School of Cyber Security, University of Chinese Academy of Sciences, Beijing, 100093, China

    Jian Xu, Xiaochun Yun, Yongzheng Zhang & Zhenyu Cheng

  3. National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing, 100093, China

    Xiaochun Yun

Authors
  1. Jian Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaochun Yun
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yongzheng Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhenyu Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiaochun Yun .

Editor information

Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. University of West London, London, UK

    Xinheng Wang

  3. Hangzhou Dianzi University, Hangzhou Shi, Zhejiang, China

    Yuyu Yin

  4. London South Bank University, London, UK

    Muddesar Iqbal

Rights and permissions

Reprints and permissions

Copyright information

© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Xu, J., Yun, X., Zhang, Y., Cheng, Z. (2019). Important Member Discovery of Attribution Trace Based on Relevant Circle (Short Paper). In: Gao, H., Wang, X., Yin, Y., Iqbal, M. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 268. Springer, Cham. https://doi.org/10.1007/978-3-030-12981-1_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-12981-1_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-12980-4

  • Online ISBN: 978-3-030-12981-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation