Papers by Keyword: Intrusion Detection System (IDS)

Abstract: BP neural network is a multilayer feed-forward neural network, it achieved from input to output arbitrary nonlinear mapping, and weights are adjusted by using the back propagation learning algorithm. Intrusion detection systems using the learning ability of neural network to extract the network data profile, and it also can use the neural network has the ability of self-learning and parallel processing ability, through the construction of intelligent neural network classifier to identify abnormal, so as to achieve the purpose of detecting intrusion behavior. The paper proposes the development of intrusion detection system based on improved BP neural network. Experimental results show that the proposed algorithm has high efficiency.

Abstract: The efficiency of pattern matching algorithm used in detection engine decides the performance of intrusion detection system. This paper improves the data structure of SBOM Algorithm, which is well-known keyword matching algorithm, by adding or removing keywords dynamically. The results of experiments on 1999 DARPA intrusion Detection Evaluation Data Sets indicate that the implemented NIDS(Network Intrusion Detection System) is comparatively excellent for large keyword sets.

Abstract: The wireless sensor networks are widely used in many fields because of its characters such as large-scale, self-organization, dynamic, reliability and so on. But its developments have encountered many problems and the security is an important problem. The traditional security protection method cannot be applied directly to the wireless sensor networks such as the intrusion detection system due to its special characteristics with limited memory and storage space. In this paper, the security problems and related protection mechanisms in the wireless sensor networks are discussed and the intrusion detections are introduced. The essential reasons of security issues in wireless sensor networks are analyzed and some intrusion attacks methods are illustrated. The security pattern in the wireless sensor networks is provided and analyzed.

Abstract: In order to improve the design of intrusion detection model, this paper according to the analysis of generic intrusion detection model and intrusion detection model based on data mining, design for intrusion detection intrusion detection systems based on improved fuzzy C-means algorithm, In the model, the design of each module, Detailed description of the various parts and the parts functions of the model, and finally the feasibility of the model were analyzed. This method is effective to solve the problem of false detection rate in intrusion detection system, so that the performance of intrusion detection systems has a greater improvement.

Abstract: Intrusion detection system (IDS) can find the intrusion information before the computer be attacked, and can hold up and response the intrusion in real time. Artificial neural network algorithms play a key role in IDS. The intrusion detection system (ANN) algorithms can analyze the captured data and judge whether the data is intrusion. In this paper we used Back Propagation (BP) network and Radical Basis Function (RBF) network to the IDS. The result of the experiment improve that The RBF neural network is better than BP neural network in the ability of approximation, classification and learning speed. During the procedure there is a large amount of computes. On cloud platform the calculation speed has been greatly increased. So that we can find the invasion more quickly and do the processing works accordingly.

Abstract: With the popularity of Internet applications, network security has become one of the issues affecting the world economy. Currently, there is a large space to develop for intrusion detection systems as a relatively new field. For the faults of HIDS or NIDS network intrusion detection system, Papers has designed a hybrid HIDS and NIDS intrusion detection system model, and the introduction of Agent systems, finally through analysis the hybrid model of intrusion detection system, we can acquire its advantages.

Abstract: In this paper, the current intrusion detection systems are analyzed in the full study of the development trend of domestic and foreign country. According to the campus network can be divided into functional independence of the structural characteristics of the subnet, while taking full advantage of agent technology in the intrusion detection system technology, we have referenced to the agent technology and a variety of detection methods for the analysis and comparison, and have analyzed the existing distributed intrusion detection system ,we propose a monitoring and management center with a multi-agent intrusion detection model framework. This model uses a distributed architecture that combines network-and host-based intrusion detection method for intrusion detection.

Abstract: The compositions, principles and features of infrared sensors, ultrasonic sensors, microwave sensors and combined sensors in intrusion detection system are discussed in this paper, then the applications and installation skills of several common intrusion detection system are introduced.

Abstract: One of difficultest problem is to find these important features (namely, effective features) for intrusion detection system (IDS). In order to resolve the problem, a method is presented in the paper. The so-called important features are these features in which much information for IDS is provided. The information provided by a feature is measured by mean-squared error (namely, variance) of the feature. The correlativity between two features is measured by covariance. If the covariance is equal to zero, the two features are non-correlative. On condition that covariance is equal to zero, the new feature making the variance maximum is gained. The new feature is called first important features searched in the paper. In the same approach, the second, third … important features are gained. Tests show that the method developed in the article and IDS based on the important features sought in the method are useful and available.

Abstract: This paper studies the security problems of campus network and summarizes the current on the current security risks and threats that campus network faces, focusing on analysis of attack-defense strategies on DOS network layer, proposing the security program of campus network which uses firewall as well as network security intrusion detection system snort. This paper analyzes the functional advantages of the program and presents in details the setup deployment and collocation methods of network security intrusion detection system based on snort in the campus network, and its application results are also summarized.