Title :
Application of the improved PrefixSpan algorithm in Intrusion Detection
Author :
Xie, Qingsen ; Yang, Tianqi
Author_Institution :
Dept. of Comput. Sci., Jinan Univ., Guangzhou, China
Abstract :
The PrefixSpan algorithm, which is broadly applied to data mining field, is one of the most high-efficiency classical algorithms. Taking account of insufficiency of PrefixSpan algorithm, the thesis trys to optimize the algorithm by reducing frequency of exchanging between the memory and the external memory in the Prefix part, and reducing the size of the projection database by discarding the non-frequent items which created in the process of sequence patterns mining. The result of test demonstrates that the operating efficiency is enhanced more than 30%. The conclusion of the experimental analysis shows that the improved algorithm is applicable to the invasion detection.
Keywords :
data mining; security of data; PrefixSpan algorithm; data mining field; intrusion detection; invasion detection; projection database; sequence patterns mining; Algorithm design and analysis; Data engineering; Data mining; Data preprocessing; Databases; Intrusion detection; Laboratories; PrefixSpan algorithm; data mining; invasion detection; sequence pattern;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2010 8th World Congress on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-6712-9
DOI :
10.1109/WCICA.2010.5554651
