DocumentCode
3085188
Title
Detect Stepping-Stone Insider Attacks by Network Traffic Mining and Dynamic Programming
Author
Yang, Jianhua ; Ray, Lydia ; Zhao, Guoqing
Author_Institution
TSYS Sch. of Comput. Sci., Columbus State Univ., Columbus, GA, USA
fYear
2011
fDate
22-25 March 2011
Firstpage
151
Lastpage
158
Abstract
Stepping-stone is the most popular way used to attack other computers. Some insiders use stepping-stone to launch their attacks pretending to be outsiders. In this paper, we propose a novel algorithm to detect stepping-stone insider attacks through comparing outgoing and incoming connections. We modify the existing packet matching algorithm by introducing sliding window to make the algorithm more efficient and practicable. The algorithm to compute the similarity between two time-pair sequences through finding the longest common sub sequence is proposed. The stepping-stone insider attacks detection algorithm is easy to be implemented and to use since there is no threshold needed. The experimental results showed the effectiveness of the algorithm to detect stepping-stone insider attacks.
Keywords
data mining; dynamic programming; security of data; telecommunication traffic; dynamic programming; network traffic mining; packet matching algorithm; sliding window; stepping-stone insider attack detection; time-pair sequences; Algorithm design and analysis; Clustering algorithms; Computers; Data mining; Dynamic programming; Markov processes; Sensors; Network security; chaff-perturbation; insider detection; masquerader; stepping-stone; time-jittering; traitor;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Information Networking and Applications (AINA), 2011 IEEE International Conference on
Conference_Location
Biopolis
ISSN
1550-445X
Print_ISBN
978-1-61284-313-1
Electronic_ISBN
1550-445X
Type
conf
DOI
10.1109/AINA.2011.33
Filename
5763360
Link To Document