Online Intrusion Behaviors: Sequences and Time Intervals
2010 ◽
Vol 38
(10)
◽
pp. 1307-1312
Keyword(s):
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.
2013 ◽
pp. 249-256
Keyword(s):
2018 ◽
Vol 7
(1)
◽
pp. 7
2014 ◽
Vol 596
◽
pp. 852-855
◽
2020 ◽
Vol 28
(Supp02)
◽
pp. 65-91