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Research of high performance intrusion detection platform
一种高性能入侵检测平台的研究*

WEI Zhong,CHEN Chang song,
魏忠
,陈长松

计算机应用研究 , 2008,
Abstract: In order to solve the need of host-based intrusion detection,developed in view of many kinds of operating system platform(Windows,HP UNIX,IBM AIX,SUN)which was different with the traditional network intrusion detection platform system,this system using the control center-event to collect-the host-poke head in three systems build up high performance intrusion detection platform gathers the network intrusion detection as well as the audit system and the intelligent response system.
Intrusion Detection Model Based on Intention Modeling
基于对手思维建模的分布式入侵检测模型*

LU Jun,WANG Chong-jun,WANG Jun,CHEN Shi-fu,
陆俊
,王崇骏,王珺,陈世福

计算机应用研究 , 2007,
Abstract: Through researching the past and resent network intrusion and intrusion detection system,intention modeling and intention recognition to intrusion detection system and propose an intrusion detection system model IRAIDS were introduced,which helps to solve distributed intelligent network intrusions.
An Intrusion Prediction Technique Based on Co-evolutionary Immune System for Network Security (CoCo-IDP)  [cached]
Mohammad Reza Ahmadi
International Journal of Network Security , 2009,
Abstract: Forecasting the unknown and detecting the known threats and targeted attacks are the most concern of network security especially in large scale environment. We have presented an intrusion detection and prediction system using cooperative co-evolutionary immune system for distributed data networks. This is an intelligent technique based on genetic algorithm and co-evolutionary immune system where the detectors can discriminate the existing incidents and predicting the new incidents in a distributed environment. We have prepared a prototype of CoCo-IDP in a Jini platform running grid computing in distributed systems. Evaluation results show that, the CoCo-IDP can adaptively converge for the best answer and can detect or predict the incidents in a selected boundary. Moreover, the system generates the flexible detectors with diversity in a variable threshold. In comparison with pure Immune System (IS), the obtained results show that the proposed system has simpler rules, more powerful detection and prediction capabilities with high accuracy metric. We have compared the probability of detection and false accuracy rate in KDD database with several well known methods for proof and validation of our results.
An Intelligent Grid Intrusion Detection System
智能网格入侵检测系统

WEI Yu-Xin,WU Mu-Qing,
魏宇欣
,武穆清

软件学报 , 2006,
Abstract: Adopt the advanced distributed system combined with intelligent intrusion detection technology is one of the key technologies to be applied in the intrusion detection system.Through the study on grid and intelligent intrusion detection technology,an intelligent Grid Intrusion Detection System(GIDS)is proposed which deploys in the grid environment and uses neural network detection technology.In order to realize the load balance between the detection engines,a scheduling strategy is used based on the resource performance value.In addition,Multiplicative Increase Linear Decrease(MILD)is applied to alerts aggregation.The GIDS,which fully exploits resources in the grid and realizes load balance,has high effectiveness in detecting the malicious attacks under heavy network traffic environment.Experimental results show that the performance of GIDS is good.
Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM  [PDF]
S. Ganapathy,P. Yogesh,A. Kannan
Computational Intelligence and Neuroscience , 2012, DOI: 10.1155/2012/850259
Abstract: Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set. 1. Introduction Mobile ad hoc networks (MANETs) consist of mobile nodes that work independently without an infrastructure. They are useful in application areas like disaster management emergency and rescue operations where it is not possible to have well-defined infrastructure. MANETs are characterized by its great flexibility. However, MANET’s inherent vulnerability increases their security risks. Though MANETs are dynamic and cooperative in nature, it needs efficient and effective security mechanisms to safeguard the mobile nodes. Intrusion detection and prevention are primary mechanisms to reduce possible intrusions. Intrusion detection using classification algorithms effectively discriminates “normal” behavior from “abnormal” behavior. Therefore, intrusion detection and prevention system can be used as a secondary mechanism of defense in any wireless environment and mobile databases so that it can be a part of the reliable communication in MANETs [1]. Intrusion detection systems (IDS) play a major role in providing security to networks. In this paper, we introduce a new intelligent agent-based intrusion detection model for securing the mobile ad hoc networks. The main function of the proposed intrusion detection system is to monitor the computer system and network in order to find the intrusion activities in the system. In such system, attacks are divided into two categories, namely, host-based attacks and network-based attacks. Hence, IDSs are also
Intelligent Resilient Framework of Multi-SoftMan Intrusion Prevention System Model
Multi—SoftMan入侵防御系统模型的智能弹性架构

MA Zhan-fei,ZHENG Xue-feng ZENG Guang-ping TU Xu-yan,
马占飞
,郑雪峰,曾广平,涂序彦

计算机科学 , 2008,
Abstract: SoftMan is a new concept based on production of distributed technique, agent, intelligent robot and artificial life, and its corresponding theory and technology fruits provide a good foundation and reference for studying the present intrusion detection systems (IDS). Inspired by the intelligence recognition capability of SoftMan , a novel Multi-SoftMan intrusion prevention system (MSMIPS) negotiation control model and relevant algorithm are presented and researched deeply for network security systems, which...
The development of the architecture of Distributed Network Intrusion Detection System (D-NIDS)  [PDF]
Andrey Bushev,Sergey Vlasenko,Ilya Glotov,Yuri Monakhov,Aleksey Tishin
Computer Science , 2013,
Abstract: This paper presents the development of the architecture of Distributed Network Intrusion Detection System.
Improved Apriori and KNN approach for Virtual machine based intrusion detection  [PDF]
Suneetha Valluru#1 , Mrs N. Rajeswari#2
International Journal of Engineering Trends and Technology , 2012,
Abstract: Nowadays, as information systems are usually more accessible to the world wide web, the advantage of secure networks is tremendously increased. New intelligent Intrusion Detection Systems (IDSs) that based on sophisticated algorithms as an alternative to current signature-base detections are really in demand. Intrusion detection is one of network security area of technology main research directions. Data mining technology was applied to network intrusion detection system (NIDS), may discover the new pattern due to massive network data, to scale back the workload of the manual compilation intrusion behavior patterns and normal behavior patterns.Virtualization is now a more popular service hosting platform. Recently, intrusion detection systems (IDSs) which utilize virtualization are now introduced. A particular challenge inside current virtualization-based IDS systems is considered in this project. In this particular proposed system a new chi-square based feature selection that evaluates the relative importance of individual features. After feature selection proposed techniques like KNN and Modified apriori are applied on the data with less false positive rates.
Design and Implementation of Secure Nodes in the Based-Internet-of-Things Intelligent Household  [PDF]
Xiangdong Hu, Hongru Xu, Kaimin Han
Journal of Computer and Communications (JCC) , 2014, DOI: 10.4236/jcc.2014.27001
Abstract:

As one of the most important uses of the Internet of things (IOT), the intelligent household is becoming more and more popular. There are many fragile nodes in the intelligent household and they are bound to encounter some potential risks of hostile attacks, such as eavesdropping, denial of service, error instructs, non-authorized access or fabrication and others. This paper presents a method of design and implement of secure nodes for the intelligent household based on the IOT technology, besides giving the hardware model of nodes, the management of key, the access authentication of network, the transmission of encrypted data, and the alarm based on intrusion detection and other security mechanisms. That is, to improve the security of the based-IOT intelligent household from the viewpoint of nodes security. A test platform is built and the results of simulation prove that the proposed method can effectively improve the security of the intelligent household from access safety and transmission security.

Data Acquisition Module Research and Implementation of Distributed Intrusion Detection System  [cached]
Li Liu
Modern Applied Science , 2010, DOI: 10.5539/mas.v4n4p140
Abstract: This article first introduced the invasion and the concept of intrusion detection, and then described the data acquisition module in the Distributed Intrusion Detection. Finally, with a programming package intercepted, and through experiments to prove that good data packets intercepted.
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