TY  - JOUR
T1  - Toward Mining Salient Attributes Based on Developing Principle Component
Analysis Algorithm
AU - Hashim Al-Saedi, Karim 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 14
SP  - 5890
EP  - 5896
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.5890.5896
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.5890.5896
KW  - reliable
KW  -data mining
KW  -network security
KW  -Attributes extraction
KW  -detection
KW  -database
AB  - An intrusion detection system gathers and tests information from different parts within a computer
network to characterize possible security threats that include threats from both outside and inside of the
organization. This system generates a large volume of alerts by detecting these threats which contains
irrelevant and redundant attributes. Attribute selection, therefore is an important step in data mining. Most
researches use all attributes in their databases while some of these features may be irrelevant or redundant and
they do not participate to the process of intrusion detection. Therefore, different attribute ranking and attribute
selection techniques are proposed. In this study, presented salient attributes mining technique according on
improved principle component analysis algorithm which are utilized to select, rank reliable attributes and remove
inefficient attributes to have a more precise and reliable intrusion detection process standard database.
ER  -