Skip to main content

Towards Visualizing Mobile Network Data

  • Conference paper
  • First Online:
Information Sciences and Systems 2013

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 264))

Abstract

This paper presents the research directions that the visualization in the NEMESYS project will follow, so as to visualize mobile network data and detect possible anomalies. These directions are based on the previous approaches on network security visualization and attack attribution techniques, while possible extensions are also discussed based on the presented approaches.

This work has been partially supported by the European Commission through project FP7-ICT-317888-NEMESYS funded by the 7th framework program. The opinions expressed in this paper are those of the authors and do not necessarily reflect the views of the European Commission.

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 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
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

References

  1. Gelenbe E, Gorbil G, Tzovaras D, Liebergeld S, Garcia D, Baltatu M, Lyberopoulos G (2013) Nemesys: enhanced network security for seamless service provisioning in the smart mobile ecosystem. In: Proceedings of 28th international symposium on computer and information sciences (ISCIS’13), Oct 2013, accepted for publication

    Google Scholar 

  2. Delosieres L, Garcia D (2013) Infrastructure for detecting android malware. In: Proceedings of 28th international symposium on computer and information sciences (ISCIS’13), Oct 2013, accepted for publication

    Google Scholar 

  3. Baltatu M, D’Alessandro R, D’Amico R (2013) NEMESYS: first year project experience in Telecom Italia Information Technology. In: Proceedings of 28th international symposium on computer and information sciences (ISCIS’13), Oct. 2013, accepted for publication

    Google Scholar 

  4. Liebergeld S, Lange M (2013) Android security, pitfalls, lessons learned and BYOD. In: Proceedings of 28th international symposium on computer and information sciences (ISCIS’13), Oct. 2013, accepted for publication

    Google Scholar 

  5. Abdelrahman O, Gelenbe E, Gorbil G, Oklander B (2013) Mobile network anomaly detection and mitigation: the NEMESYS approach. In Proceedings of 28th international symposium on computer and information sciences (ISCIS’13), Oct. 2013, accepted for publication

    Google Scholar 

  6. Shiravi H, Shiravi A, Ghorbani AA (2011) A survey of visualization systems for network security. IEEE Trans Visual Comput Graphics 1(1):1–19

    Google Scholar 

  7. Shen Z, Ma KL (2008) Mobivis: a visualization system for exploring mobile data. In: Visualization symposium, 2008. PacificVIS’08. IEEE Pacific, pp 175–182, IEEE, 2008

    Google Scholar 

  8. Eagle N, Pentland A (2006) Reality mining: sensing complex social systems. Pers Ubiquit Comput 10(4):255–268

    Article  Google Scholar 

  9. Lambert MJ (2005) Visualizing and analyzing human-centered data streams. PhD thesis, Massachusetts Institute of Technology

    Google Scholar 

  10. Tsigkas O, Tzovaras D (2012) Analysis of Rogue Anti-Virus Campaigns using hidden structures in k-Partite graphs. Cryptology and network Security, pp 114–125, Springer, Berlin

    Google Scholar 

  11. Tsigkas O, Thonnard O, Tzovaras D (2012) Visual spam campaigns analysis using abstract graphs representation. In: Symposium on visualization for cyber security, Seattle, WA, USA

    Google Scholar 

  12. Papadopoulos S, Moustakas K, Tzovaras D (2012) Hierarchical visualization of BGP routing changes using entropy measures. In: Bebis G, Boyle R, Parvin B, Koracin D, Fowlkes C, Wang S, Choi MH, Mantler S, Schulze J, Acevedo D, Mueller K, Papka M (eds) Advances in visual computing, vol 7432 of Lecture notes in computer science. Springer, Berlin Heidelberg, pp 696–705

    Google Scholar 

  13. Fuchs J, Fischer F, Mansmann F, Bertini E, Isenberg P et al (2013) Evaluation of alternative glyph designs for time series data in a small multiple setting. In: Proceedings of the conference on human factors in computing systems (CHI)

    Google Scholar 

  14. Zhao L, Yang J, Fan J (2009) A fast method of coarse density clustering for large data sets. In: 2nd international conference on biomedical engineering and informatics, 2009. BMEI’09, pp 1–5, IEEE

    Google Scholar 

  15. Adrienko N, Adrienko G (2011) Spatial generalization and aggregation of massive movement data. IEEE Trans Visual Comput Graphics 17(2):205–219

    Article  Google Scholar 

  16. Vinh NX, Epps J (2010) Mincentropy: a novel information theoretic approach for the generation of alternative clusterings. In: IEEE 10th international conference on data mining (ICDM), pp 521–530, IEEE

    Google Scholar 

  17. Schaeffer SE (2007) Graph clustering. Comput Sci Rev 1(1):27–64

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Stavros Papadopoulos .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this paper

Cite this paper

Papadopoulos, S., Tzovaras, D. (2013). Towards Visualizing Mobile Network Data. In: Gelenbe, E., Lent, R. (eds) Information Sciences and Systems 2013. Lecture Notes in Electrical Engineering, vol 264. Springer, Cham. https://doi.org/10.1007/978-3-319-01604-7_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-01604-7_37

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01603-0

  • Online ISBN: 978-3-319-01604-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics