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The methods estimating vulnerability of perimeter security systems are developed in the current study. Appropriate estimations are based on the fuzzy inference methods of intruder undetection risks on security zones set in territory's perimeter.
Network intrusion detection need to consider a variety of factors which are fuzzy. At present, it is a difficult problem for intrusion detection system (IDS) to distinguish normal state from abnormal one exactly. To solve the problem, an intrusion detection model based on fuzzy choose-closed principle is presented. Applying theory of fuzzy set to process network intrusion parameters can distinguish...
A service-oriented environment has special characteristics that distinguishes it from other computing environments: (i) the environment is dynamic; (ii) the number of service providers is unbounded; (iii) services are owned by various stakeholders with different aims and objectives; (iv) there is no central authority that can control all the service providers and consumers; (v) service providers and...
Problems related to data privacy are studied in the areas of privacy preserving data mining (PPDM) and statistical disclosure control (SDC). Their goal is to avoid the disclosure of sensitive or proprietary information to third parties. In this paper a new synthetic data generation method is proposed and the information loss and disclosure risk are measured. The method is based on fuzzy techniques...
Anti-spam technology has been developed to the third generation technology, behavior recognition technology. There are many traditional classification models, among which, decision tree model is the one most widely used, and has a good intelligibility. But the absolutely clear attributes does not always exist in real world. This paper proposed a fuzzy decision tree based method for spam behavior recognition...
An improved fuzzy AHP method based on triangular fuzzy number is presented to deal with the problem of the risk assessment for information systems security. The calculation model for the information systems risk assessment is established. The judgments of the experts are depicted with triangular fuzzy number complementary judgment matrix, and the weights of the indices are obtained by the least variance...
This paper presents a novel fuzzy subspace-based approach to hidden Markov model. Features extracted from patterns are considered as feature vectors in a multi-dimensional feature space. Current hidden Markov modeling techniques treat features equally, however this assumption may not be true. We propose to consider subspaces in the feature space and assign a weight to each feature to determine the...
Intrusion detection technique has become increasingly important in the area of network security research. It is innovative that various soft computing approaches have been applied to the intrusion detection field. This paper presents an intelligent intrusion detection system which incorporates several soft computing techniques to implement either misuse or anomaly detection. Genetic algorithm is used...
Due to fuzzy logic can help in handling the imprecise nature and uncertainty of trust, some papers use several fuzzy logic methods(such as fuzzy inference and fuzzy comprehensive evaluation) to tackle trust modeling for P2P-based system. However, nobody summarizes difference of these fuzzy logic methods. In this paper, authors present a general fuzzy trust problem domain for P2P-based system, and...
This article aim at the MC Agent which kinds of the general computer immune system model (GECISM), basing on fuzzy-ID3 Algorithm and constructing decision tree with the data set made by the system invoke of the application procedures, thus generated the intrusion detection rules in the General computer immune system model, and carried on a contrastive diagnosis with the C4.5 algorithm generative rule,...
With the growing rate of network attacks, intelligent methods for detecting new attacks have attracted increasing interest. This paper presents an approach incorporating several soft computing techniques to construct a hierarchical neuro-fuzzy inference intrusion detection system which can implement either misuse or anomaly detection. In the proposed system principal component analysis neural network...
The evaluation system is developed for network attack effect in this paper, and present the process from launching an attack to the result of evaluation being outputted. Based on an evaluation index system suitable for the system, we analyses some theories and methods respectively which are adopted to realize their functions by the main modules. Synthesis account of evaluated effect is conducted with...
In this paper, we construct a fuzzy ontology model and propose using a fuzzy matching rule base to promote a fuzzy ontology generation frame which supports rough concept descriptions on intrinsic semantic level. To consider the rule base and express the fuzziness, the formal analysis of concept vector is developed for the generation of fuzzy ontology that can deal with uncertain information. The proposed...
With the extensive application of information system in all walks of life, security analysis and assessment carried out on the IS have become quite necessary. This paper has, on the basis of the fuzzy synthetic assessment method, suggested a security assessment model to the financial service IS, and applied it in the practical Information System Security Risk assessment to demonstrate the feasibility...
This paper describes a hybrid design for intrusion detection that combines anomaly detection with misuse detection. The proposed method includes an ensemble feature selecting classifier and a data mining classifier. The former consists of four classifiers using different sets of features and each of them employs a machine learning algorithm named fuzzy belief k-NN classification algorithm. The latter...
A great deal of noise data in the network connectivity information affect badly to build SVM optimal classification hyperplane and lead to higher classification error rate. In this paper, fuzzy membership function is applied into v-SVM; it acquires different values for each input data that accord to different effects on the classification result. Therefore different input samples points can make different...
In several previous investigations, the capability of fuzzy systems to solve different kinds of problems has been demonstrated. Evolutionary fuzzy system hybridizes the approximate reasoning method of fuzzy systems with the learning capability of evolutionary algorithms. The objective of this paper is to demonstrate the ability of evolutionary fuzzy system to deal with intrusion detection classification...
Classification rule mining is a practical data mining technique widely used in real world. In the previous work, we have put forward a fuzzy class association rule mining method based on genetic network programming and applied it to network intrusion detection system which proved its efficiency and advantage. In this paper, a detailed comparison not only between fuzzy class association rule minings(FCARMs)...
A game theoretic recommendation system is presented that aims to improve security alert dissemination and evaluation. The system increases the efficiency of its users (e.g. system administrators), who operate under time and resource limitations, by improving the information flow from security experts. Combining security alerts and local information the system recommends a resource allocation strategy...
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