DocumentCode :
1812644
Title :
ICAS: An inter-VM IDS Log Cloud Analysis System
Author :
Yang, Shun-Fa ; Chen, Wei-Yu ; Wang, Yao-Tsung
Author_Institution :
Free Software Lab., Nat. Center for High-Performance Comput., Taichung, Taiwan
fYear :
2011
fDate :
15-17 Sept. 2011
Firstpage :
285
Lastpage :
289
Abstract :
Cloud computing can reduce mainframe management costs, so more and more users choose to build their own cloud hosting environment. In cloud computing, all the commands through the network connection, therefore, information security is particularly important. In this paper, we will explore the types of intrusion detection systems, and integration of these types, provided an effective and output reports, so system administrators can understand the attacks and damage quickly. With the popularity of cloud computing, intrusion detection system log files are also increasing rapidly, the effect is limited and inefficient by using the conventional analysis system. In this paper, we use Hadoop´s MapReduce algorithm analysis of intrusion detection System log files, the experimental results also confirmed that the calculation speed can be increased by about 89%. For the system administrator, IDS Log Cloud Analysis System (called ICAS) can provide fast and high reliability of the system.
Keywords :
cloud computing; security of data; virtual machines; Hadoop MapReduce algorithm analysis; ICAS; cloud computing; cloud hosting environment; conventional analysis system; information security; interVM IDS log cloud analysis system; intrusion detection system log files; mainframe management cost reduction; Cloud computing; Computer architecture; Correlation; File systems; Intrusion detection; Monitoring; Cloud Computing; Hadoop; IDS; MapReduce;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing and Intelligence Systems (CCIS), 2011 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-61284-203-5
Type :
conf
DOI :
10.1109/CCIS.2011.6045076
Filename :
6045076
Link To Document :
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