scholarly journals FEATURE SELECTION AND CLASSIFICATION OF INTRUSION DETECTION SYSTEM USING ROUGH SET

2013 ◽  
pp. 48-51
Author(s):  
NIKITA GUPTA ◽  
NARENDER SINGH ◽  
VIJAY SHARMA ◽  
TARUN SHARMA ◽  
AMAN SINGH BHANDARI
Keyword(s):  
Feature Selection ◽  
Intrusion Detection ◽  
Rough Set ◽  
Intrusion Detection System ◽  
Rough Set Theory ◽  
Computer Network ◽  
Detection System ◽  
Classification Rules ◽  
Training Set

With the expansion of computer network there is a challenge to compete with the intruders who can easily break into the system. So it becomes a necessity to device systems or algorithms that can not only detect intrusion but can also improve the detection rate. In this paper we propose an intrusion detection system that uses rough set theory for feature selection, which is extraction of relevant attributes from the entire set of attributes describing a data packet and used the same theory to classify the packet if it is normal or an attack. After the simplification of the discernibility matrix we were to select or reduce the features. We have used Rosetta tool to obtain the reducts and classification rules. NSL KDD dataset is used as training set and is provided to Rosetta to obtain the classification rules.

scholarly journals PEMANFAATAN INTRUSION DETECTION SYSTEM (IDS) SEBAGAI OTOMATISASI KONFIGURASI FIREWALL BERBASIS WEB SERVICE MENGGUNAKAN ARSITEKTUR REPRESENTATIONAL STATE TRANSFER (REST)

Compiler ◽  
2013 ◽  
Vol 2 (2) ◽  
Author(s):  
Demmy Nanda Awangga ◽  
Haruno Sajati ◽  
Yenni Astuti
Keyword(s):  
Intrusion Detection ◽  
Web Service ◽  
Intrusion Detection System ◽  
Computer Network ◽  
Detection System ◽  
Ip Address ◽  
Final Project ◽  
Representational State Transfer ◽  
State Transfer ◽  
Representational State

Many things can destabilize a computer network connections, both with regard to hardware and software. Therefore, we need a technique for network security, one of them is firewall. The problems that arise in this final project is to build a linux based firewall automation application via web service by using REST (Representational State Transfer) architecture and IDS (Intrusion Detection System). The system buid firewall rules using linux operating system with the help o f 2 pieces o f IDS to detect theactivities of traffic data between the intruder and the server that will be recorded in the IDS database. The system will compare the server with IDS on the router to get the IP address o f the actual intruders, so it will be blocked by the firewall. The applications is used to prevents the ping o f death attack usingweb service and REST protocol so that firewall rules will run automatically.

Deploying Honeynets

2008 ◽  
pp. 1562-1579
Author(s):  
Ronald C. Dodge Jr. ◽  
Daniel Ragsdale
Keyword(s):  
Intrusion Detection ◽  
Detailed Analysis ◽  
Intrusion Detection System ◽  
Computer Network ◽  
Production Systems ◽  
Detection System ◽  
Network System ◽  
Network Resources ◽  
Malicious User ◽  
Malicious Activity

When competent computer network system administrators are faced with malicious activity on their networks, they think of the problem in terms of four distinct but related activities: detection, prevention, mitigation, and response. The greatest challenge of these four phases is detection. Typically, detection comes in the form of intrusion detection system (IDS) alerts and automated application and log monitors. These however are fraught with mischaracterized alerts that leave administrators looking for a needle in a haystack. One of the most promising emerging security tools is the honeynet Honeynets are designed to divert the malicious user or attacker to non-production systems that are carefully monitored and configured to allow detailed analysis of the attackers’ actions and also protection of other network resources. Honeynets can be configured in many different ways and implemented from a full DMZ to a carefully placed file that is monitored for access.

Deploying Honeynets

2011 ◽  
pp. 266-286
Author(s):  
Ronald C. Dodge Jr. ◽  
Daniel Ragsdale
Keyword(s):  
Intrusion Detection ◽  
Detailed Analysis ◽  
Intrusion Detection System ◽  
Computer Network ◽  
Production Systems ◽  
Detection System ◽  
Network System ◽  
Network Resources ◽  
Malicious User ◽  
Malicious Activity

When competent computer network system administrators are faced with malicious activity on their networks, they think of the problem in terms of four distinct but related activities: detection, prevention, mitigation, and response. The greatest challenge of these four phases is detection. Typically, detection comes in the form of intrusion detection system (IDS) alerts and automated application and log monitors. These however are fraught with mischaracterized alerts that leave administrators looking for a needle in a haystack. One of the most promising emerging security tools is the honeynet Honeynets are designed to divert the malicious user or attacker to non-production systems that are carefully monitored and configured to allow detailed analysis of the attackers’ actions and also protection of other network resources. Honeynets can be configured in many different ways and implemented from a full DMZ to a carefully placed file that is monitored for access.

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