Skip to main content

Skiplist Timing Attack Vulnerability

  • Conference paper
  • First Online:
Book cover Data Privacy Management, Cryptocurrencies and Blockchain Technology (DPM 2019, CBT 2019)

Abstract

In this paper we address the structure and behavior of the probabilistic Skiplist data structure and present an exploit in the form of a timing attack on the structure. In this exploit, we show how to map the presumably hidden structure of a Skiplist by timing the return time of search queries. This data can then be used to perform operations on the Skiplist which will cause a degradation in its subsequent performance. In addition, we describe another exploitation of this data to use the Skiplist as a means of creating a hidden channel between two attackers. Finally, we propose a new variant of Skiplist we call a Splay Skiplist, which retains the \(O(\log n)\) performance of Skiplist while defending against the stated exploit.

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 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
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

Institutional subscriptions

References

  1. Aspnes, J., Shah, G.: Skip graphs. ACM Trans. Algorithms 3(4) (2007). https://doi.org/10.1145/1290672.1290674

    Article  MathSciNet  Google Scholar 

  2. Bagchi, A., Buchsbaum, A.L., Goodrich, M.T.: Biased skip lists. Algorithmica 42(1), 31–48 (2005). https://doi.org/10.1007/s00453-004-1138-6

    Article  MathSciNet  MATH  Google Scholar 

  3. Bethea, D., Reiter, M.K.: Data structures with unpredictable timing. In: Backes, M., Ning, P. (eds.) ESORICS 2009. LNCS, vol. 5789, pp. 456–471. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-04444-1_28

    Chapter  Google Scholar 

  4. Chen, J., Jindel, S., Walzer, R., Sen, R., Jimsheleishvilli, N., Andrews, M.: The memSQL query optimizer: a modern optimizer for real-time analytics in a distributed database. Proc. VLDB Endow. 9(13), 1401–1412 (2016). https://doi.org/10.14778/3007263.3007277

    Article  Google Scholar 

  5. Crosby, S.A., Wallach, D.S.: Denial of service via algorithmic complexity attacks. In: Proceedings of the 12th Conference on USENIX Security Symposium - Volume 12, SSYM 2003, p. 3. USENIX Association, Berkeley (2003). http://dl.acm.org/citation.cfm?id=1251353.1251356

  6. Ergun, F., Cenk Şahinalp, S., Sharp, J., Sinha, R.K.: Biased skip lists for highly skewed access patterns. In: Buchsbaum, A.L., Snoeyink, J. (eds.) ALENEX 2001. LNCS, vol. 2153, pp. 216–229. Springer, Heidelberg (2001). https://doi.org/10.1007/3-540-44808-X_18

    Chapter  Google Scholar 

  7. Futoransky, A., Saura, D., Waissbein, A.: Timing attacks for recovering private entries from database engines, January 2008

    Google Scholar 

  8. Goodrich, M.T., Tamassia, R., Schwerin, A.: Implementation of an authenticated dictionary with skip lists and commutative hashing. In: Proceedings DARPA Information Survivability Conference and Exposition II, DISCEX 2001, vol. 2, pp. 68–82, June 2001. https://doi.org/10.1109/DISCEX.2001.932160

  9. Goodrich, M.T., Kornaropoulos, E.M., Mitzenmacher, M., Tamassia, R.: More practical and secure history-independent hash tables. In: Askoxylakis, I., Ioannidis, S., Katsikas, S., Meadows, C. (eds.) ESORICS 2016. LNCS, vol. 9879, pp. 20–38. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45741-3_2

    Chapter  Google Scholar 

  10. Messeguer, X.: Skip trees, an alternative data structure to skip lists in a concurrent approach. ITA 31, 251–269 (1997)

    MathSciNet  MATH  Google Scholar 

  11. Pugh, W.: Skip lists: a probabilistic alternative to balanced trees. Commun. ACM 33(6), 668–676 (1990)

    Article  Google Scholar 

  12. Sleator, D.D., Tarjan, R.E.: Self-adjusting binary search trees. J. ACM 32(3), 652–686 (1985). https://doi.org/10.1145/3828.3835

    Article  MathSciNet  MATH  Google Scholar 

  13. Solis, J., Tsudik, G.: Simple and flexible revocation checking with privacy. In: Danezis, G., Golle, P. (eds.) PET 2006. LNCS, vol. 4258, pp. 351–367. Springer, Heidelberg (2006). https://doi.org/10.1007/11957454_20

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Eyal Nussbaum .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Nussbaum, E., Segal, M. (2019). Skiplist Timing Attack Vulnerability. In: Pérez-Solà, C., Navarro-Arribas, G., Biryukov, A., Garcia-Alfaro, J. (eds) Data Privacy Management, Cryptocurrencies and Blockchain Technology. DPM CBT 2019 2019. Lecture Notes in Computer Science(), vol 11737. Springer, Cham. https://doi.org/10.1007/978-3-030-31500-9_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-31500-9_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-31499-6

  • Online ISBN: 978-3-030-31500-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics