Title :
Multi Relational Mining in Network Intrusion Detection
Author_Institution :
Dept. of Comput. Eng., Huaiyin Inst. of Technol., Huaiyin
Abstract :
The network intrusion detection (NIDS) is faced with the question to detect many kinds of intrusion. In order to detect the complex attack, network intrusion detection system need to analysis massive data captured form different network safety equipments. So a new multi relational mining algorithm MRA2 is proposed. MRA2 depend on the association rules mining technology and the probability function dependency method which is proposed through extending the theory of function dependency. MRA2 is able to synthesize the various datalog resources to detect intrusion effectively and reappear to the complex network attack scenario.
Keywords :
data mining; probability; security of data; MRA2; association rules mining; multirelational mining; network intrusion detection; probability function dependency method; Association rules; Complex networks; Data analysis; Data mining; Face detection; Intrusion detection; Logic; Phase frequency detector; Relational databases; Safety devices; Intrusion detection; Multi Relational Mining; probability function dependency;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Print_ISBN :
978-0-7695-3305-6
DOI :
10.1109/FSKD.2008.505