A New Model for Dynamic Intrusion Detection

2005 ◽  
pp. 72-84 ◽  
Author(s):  
Tao Li ◽  
Xiaojie Liu ◽  
Hongbin Li
Keyword(s):  
Intrusion Detection ◽  
New Model

A Novel Approach for Intrusion Detection Based on Model Checking Interval Temporal Logic with Past Construct

2014 ◽  
Vol 680 ◽  
pp. 451-454
Author(s):  
Peng Zhe Qiao ◽  
Wei Jun Zhu
Keyword(s):  
Model Checking ◽  
Intrusion Detection ◽  
Temporal Logic ◽  
Pattern Matching ◽  
New Method ◽  
Network Attacks ◽  
New Model ◽  
Interval Temporal Logic ◽  
Novel Approach ◽  
Attack Models

Compared with the Intrusion Detection (ID) based on pattern matching, the model-checking-based methods can find the complex attacks. But their rates of missing report are still high. To solve this problem, we firstly use the Interval Temporal Logic with Past Construct (ITLPC) formulae to describe some signatures for network attacks. And then, we can use some automata to establish models of audit logs. On the basis of it, automata, i.e., attack models, and ITLPC formulae, i.e., signatures, constitute the two inputs of the ITLPC model checking algorithm. Therefore, a new model-checking-based ID algorithm is obtained by calling the ITLPC algorithm. Compared with the existing methods, the new method is more powerful, as shown in the experimental simulations.

A New Model of Intrusion Detection Based on Data Warehouse and Data Mining

2011 ◽  
Vol 383-390 ◽  
pp. 303-307 ◽  
Author(s):  
Bei Qi ◽  
Yun Feng Dong
Keyword(s):  
Data Mining ◽  
Intrusion Detection ◽  
Data Warehouse ◽  
Network Traffic ◽  
Traffic Monitoring ◽  
Experimental Result ◽  
Double Layers ◽  
New Model ◽  
Network Intrusion ◽  
Security Of Network

Now, security of network is threaten from double layers inside and outside network, the inherent defect of firewall technology makes the intrusion detection and network traffic analysis as the main means of defense, aiding firewall. Now network intrusion detection have problem of higher false alarm rate, we apply the data warehouse and the data mining in intrusion detection and the technology of network traffic monitoring and analysis, propose a new model of intrusion detection based on the data warehouse and the data mining. The experimental result indicates this model can find effectively many kinds behavior of network intrusion and have higher intelligence and environment accommodation.

Network Security Prevention Model Based-Immune

2009 ◽  
Vol 16-19 ◽  
pp. 881-885
Author(s):  
Ya Ping Jiang ◽  
Shi Hui Cheng ◽  
Yong Gan
Keyword(s):  
Network Security ◽  
Intrusion Detection ◽  
Intrusion Prevention ◽  
New Model ◽  
Network Intrusion ◽  
Prevention System ◽  
Prevention Model ◽  
Prevention Method ◽  
Neighbor Network ◽  
Intrusion Detection And Prevention

With the concepts of self, nonself, antibody, vaccine and antigen in an intrusion detection and prevention system presented in this paper, the architecture of network intrusion and prevention based on immune principle is proposed. The intrusion information gotten from current monitored network is encapsulated and sent to the neighbor network as bacterin; therefore the neighbor network can make use of the bacterin and predict the danger of network. The experimental results show that the new model not only actualizes an active prevention method but also improves the ability of intrusion detection and prevention than that of the traditional passive intrusion prevention systems.

A New Research on Instrusion Detection System Based on Artificial Immune

2013 ◽  
Vol 380-384 ◽  
pp. 2728-2731
Author(s):  
Lan Shi ◽  
Yan Rui Zhang
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Simulation Experiment ◽  
Detection System ◽  
The Self ◽  
Traditional Model ◽  
Artificial Immune ◽  
New Model ◽  
New Research

The paper proposed a new model by applying biological immune into intrusion detection system, in this new model, generated algorithm of the mature detection get improved, the self-et realized dynamic, co-evolution module can effectively find the system potential vulnerabilities and generate the corresponding patch to strengthen the system. As of result, simulation experiment for this new model is did, through the analysis of the result for simulation experiment, it shows that the new model and method has higher rate in making matured detector than the traditional model and method, and new model also has higher detecting rate on intrusion detection. To sum up, the co-evolution method is able to strengthen the system effectively.

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