POSTER: Context-aware web security threat prevention

Lung Hao Lee*, Yen Cheng Juan, Kuei Ching Lee, Wei Lin Tseng, Hsin Hsi Chen, Yuen Hsien Tseng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


This paper studies the feasibility of an early warning system that prevents users from the dangerous situations they may fall into during web surfing. Our approach adopts behavioral Hidden Markov Models to explore collective intelligence embedded in users' browsing behaviors for context-aware category prediction, and applies the results to web security threat prevention. Largescale experiments show that our proposed method performs accuracy 0.463 for predicting the fine-grained categories of users' next accesses. In real-life filtering simulations, our method can achieve macro-averaging blocking rate 0.4293 to find web security threats that cannot be detected by the existing security protection solutions at the early stage, while accomplishes a low macro-averaging over-blocking rate 0.0005 with the passage of time. In addition, behavioral HMM is able to alert users for avoiding security threats by 8.4 hours earlier than the current URL filtering engine does. Our simulations show that the shortening of this lag time is critical to avoid severe diffusions of security threats.

Original languageEnglish
Title of host publicationCCS'12 - Proceedings of the 2012 ACM Conference on Computer and Communications Security
Number of pages3
Publication statusPublished - 2012
Event2012 ACM Conference on Computer and Communications Security, CCS 2012 - Raleigh, NC, United States
Duration: 2012 Oct 162012 Oct 18

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)1543-7221


Other2012 ACM Conference on Computer and Communications Security, CCS 2012
Country/TerritoryUnited States
CityRaleigh, NC


  • Collaborative filtering
  • Collective intelligence
  • Security assurance

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications


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