Online intrusion behaviors: Sequences and time intervals

Hao En Chueh, Shun Chuan Ho, Shih Peng Chang, Ping Yu Hsu

Research output: Contribution to journalArticlepeer-review


In this study we model the sequences and time intervals of online intrusion behaviors. To maintain network security, intrusion detection systems monitor network environments; however, most existing intrusion detection systems produce too many intrusion alerts, causing network managers to investigate many potential intrusions individually to determine their validity. To solve this problem, we combined a clustering analysis of the time intervals of online users' behaviors with a sequential pattern analysis to identify genuine intrusion behaviors. Knowledge of the patterns generated by intruder behaviors can help network managers maintain network security.

Original languageEnglish
Pages (from-to)1307-1312
Number of pages6
JournalSocial Behavior and Personality
Issue number10
StatePublished - Nov 2010


  • Intrusion behaviors
  • Intrusion detection system
  • Network security
  • Sequential pattern analysis


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