scholarly journals Intrusion Detection System from External Threats using Data Mining

2019 ◽  
Vol 9 (2) ◽  
pp. 2069-2072
Keyword(s):  
Data Mining ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Network Intrusion Detection ◽  
Assessment Procedure ◽  
External Threats ◽  
Network Intrusion ◽  
Using Data ◽  
Alarm Message

Network Intrusion Detection is a significant apparatus to distinguish and examine security dangers to a correspondence arrange. It supplements other system security procedures, for example, firewalls, by giving data about the recurrence and nature of assaults. A system interruption discovery framework (NIDS) frequently comprises of a sensor that examines each bundle on the system under perception, and advances the parcels which are considered fascinating, together with an alarm message to a backend framework, that stores them for further examination and relationship with different occasions. The assessment procedure of the MAC address contrasted with the CADL is improved and streamlined with the help of the J48 choice tree calculation. The pursuit procedure is completed in the created arrangement esteem through tree based characterization.

Research on Network Intrusion Detection Based on Data Mining Technology

2015 ◽  
Vol 713-715 ◽  
pp. 2081-2084 ◽  
Author(s):  
Zeng Ying He
Keyword(s):  
Data Mining ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Normal Activity ◽  
Network Intrusion Detection ◽  
Test Results ◽  
Mining Technology ◽  
Network Intrusion ◽  
Network Intrusion Detection System

Aiming at some deficiencies of existing network intrusion detection system, the paper proposes a network intrusion detection system model based on data mining, applying data mining technology to network intrusion detection, and constructed the final test results of the system on the basis of Snort design. Experimental results demonstrate that this data mining based on cluster algorithm can effectively establish models of network normal activity and significantly accelerate intrusion detection, whilst its association analyzer can effectively unearth some new intrusion patterns from abnormal logs, and automatically construct intrusion detection rules.

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