Intrusion detection using rough set classification

Recently machine learning-based intrusion detection approaches have been subjected to extensive researches because they can detect both misuse and anomaly. In this paper, rough set classification (RSC), a modern learning algorithm, is used to rank the features extracted for detecting intrusions and generate intrusion detection models. Feature ranking is a very critical step when building the model. RSC performs feature ranking before generating rules, and converts the feature ranking to minimal hitting set problem addressed by using genetic algorithm (GA). This is done in classical approaches using Support Vector Machine (SVM) by executing many iterations, each of which removes one useless feature. Compared with those methods, our method can avoid many iterations. In addition, a hybrid genetic algorithm is proposed to increase the convergence speed and decrease the training time of RSC. The models generated by RSC take the form of'IF-THEN' rules, which have the advantage of explication. Tests and comparison of RSC with SVM on DARPA benchmark data showed that for Probe and DoS attacks both RSC and SVM yielded highly accurate results (greater than 99% accuracy on testing set).

Robust adaptive fuzzy control for a class of perturbed pure-feedback nonlinear systems

A new design scheme of direct adaptive fuzzy controller for a class of perturbed pure-feedback nonlinear systems is proposed. The design is based on backstepping and the approximation capability of the first type fuzzy systems. A continuous robust term is adopted to minify the influence of modeling errors or disturbances. By introducing the modified integral-type Lyapunov function, the approach is able to avoid the requirement of the upper bound of the first time derivation of the high frequency control gain. Through theoretical analysis, the closed-loop control system is proven to be semi-globally uniformly ultimately bounded, with tracking error converging to a residual set.

Approach for workflow modeling using π-calculus

As a variant of process algebra, π calculus can describe the interactions between evolving processes. By modeling activity as a process interacting with other processes through ports, this paper presents a new approach: representing workflow models using π calculus. As a result, the model can characterize the dynamic behaviors of the workflow process in terms of the LTS (Labeled Transition Semantics) semantics of π calculus. The main advantage of the workflow model's formal semantic is that it allows for verification of the model's properties, such as deadlock free and normal termination. Moreover, the equivalence of workflow models can be checked through weak bisimulation theorem in the π calculus, thus facilitating the optimization of business processes.

Thermal Decomposition Mechanism and Non Isothermal Kinetics of Complex of [La_2(P-MBA)_6(PHEN)_2]2H_2O

The complex of [La 2(P MBA) 6(PHEN) 2]2H 2O (P MBA: p methylbenzoate and PHEN: 1,10 phenanthroline) was prepared and characterized by elemental analysis and IR spectroscopy. The thermal behavior of [La 2(P MBA) 6(PHEN) 2]2H 2O in dynamic nitrogen atmosphere was investigated by TG DTG techniques. The results show that the thermal decomposition process of the [La 2(P MBA) 6(PHEN) 2]2H 2O occurs in five steps. The empirical kinetic model for the first step thermal decomposition obtained by Malek method is SB(m,n). The activation energy E and the pre exponential factor lnA for this step reaction are 76.4 kJ·mol -1 and 24.92, respectively.

Non-isothermal decomposition kinetics and lifetime of Tb2(0-MBA)6(PHEN)2

The thermal decomposition of Tb_2(O-MBA)_6(PHEN)_2 (O-MBA: o-methylbenzoate;PHEN: 1,10-phenanthroline) and its kinetics were studied under the non-isothermal condition bythermogravimetry-derivative thermogravimetry (TG-DTG) techniques. Kinetic parameters were obtainedfrom analysis of TG-DTG curves by the Achar method and the Madhusudanan-Krishnan-Ninan (MKN) method.The most probable mechanism function was suggested by comparing the kinetic parameters. The kineticequation for the first stage can be expressed as dα/dt = Aexp(-E/RT)·3(1 - α)^(2/3). Thelifetime equation at mass loss of 10% was deduced as lnτ= -28.7429 + 19797.795/T by isothermalthermogravimetric analysis.

Building GIS Web Services on JXTA Network

In recent years, Web services and Peer-to-Peer (or simply P2P) appear as two of the hottest research topics in network computing. On the one hand, by adopting a decentralized, network-based style, P2P technologies can make P2P systems enhance overall reliability and fault-tolerance, increase autonomy, and enable ad-hoc communication and collaboration. On the other hand, Web services provides a good approach to integrate various heterogeneous systems and applications into a cooperative environment. This paper presents the techniques of combining Web services and P2P technologies into GIS to construct a new generation of GIS, which is more flexible and cooperative. As a case study, an ongoing project JGWS is introduced, which is an experimental GIS Web services platform built on JXTA. This paper also explores the schemes of building GIS Web services in a P2P environment.

Fuzzy inference systems with no any rule base and linearly parameter growth

A class of new fuzzy inference systems New-FISs is presented.Compared with the standard fuzzy system, New-FIS is still a universal approximator and has no fuzzy rule base and linearly parameter growth. Thus, it effectively overcomes the second "curse of dimensionality":there is an exponential growth in the number of parameters of a fuzzy system as the number of input variables,resulting in surprisingly reduced computational complexity and being especially suitable for applications,where the complexity is of the first importance with respect to the approximation accuracy.

Thermal decomposition kinetics and lifetime of the complex of Tb_2(BA)_6(PHEN)_2

The thermal behavior of Tb_2(BA)_6(PHEN)_2 (BA: benzoate, and PHEN:1,10-phenanthroline) in a static air atmosphere was investigated by TG-DTG, SEM and IR techniques.By the kinetic method of processing thermal analysis data put forward by Malek et al., it is definedthat the kinetic model for the first-step thermal decomposition is SB(m, n). The activation energyE for this step reaction is 99.07 kJ/mol, the entropy of activation ΔS~≠ is -84.72 J/mol, theenthalpy of activation ΔH~≠ is 94.26 kJ/mol, the free energy of activation ΔG~≠ is 144.77 kJ/moland the pre-exponential factor lnA is 20.93. The lifetime equation at mass-loss of 10% was deducedas lnτ = -29.0312 + 19760.83/T by isothermal thermogravimetric analysis.

Distributed certification application via a trusted dealer

Distributed certification via threshold cryptography is much more secu re than other ways to protect certification authority (CA) 's private key,and c an tolerate some intrusions. As the original system such as ITTC,etc.,is unsaf e ,inefficient and impracitcal in actual network environment,this paper brings u p a new distributed certification scheme,which although it generates key shares concentratively,it updates key shares distributedly,and so,avoids single-po in t failure like ITTC. It not only enhances robustness with Feldman verification and SSL protocol,but can also change the threshold (t,k) flexibly and robu stly,and so,is much more practical. In this work,the authors implement the prototype sy stem of the new scheme and test and analyze its performance.

MINING CYCLIC GENERALIZED ASSOCIATION RULES

Discovering cyclic generalized association rules from transaction datbases can reveal the relationship of differ-ent levels of the taxonomies and display cyclic variations over time.Information about such variations is great use of better identifying trends in associations and forecast-ing.Because cyclic rules are quite sensitive to a littlenoise,this paper uses the noise-ratio as the criterion of i-dentifing cydclic itemsets for dealing with the problem and utilizes the cycle-pruning technique to reduce the comput-ing time of the data mining process by exploiting the real-tionship between the cycle and generalized frequent item-sets.The paper gives the algorithm of mining cyclic gen-eralized itemsets(CGI).Experiment shows that the CGI algorithm can efficiently yield results.

Positive Solutions of a Second-Order Three-point Boundary Value Problem

The existence of positive solutions is established for a nonlinear second-order three-point boundary value problem. The result improves and extends the main result in Electron J. Differential Equations, 34(1999), 1-8.

Design and Evaluation of Dynamic Replication Strategies for a High—Performance Data Grid

Physics experiments that generate large amounts of data need to be able to share it with researchers around the world .High performance grids facilitate the distribution of such data to geographically remote places.Dynamic replication can be used as a technique to reduce bandwidth consumption and access latency in accessuing these huge amounts of data.We describe a simulation framework that we have developed to model a grid scenario,which enables comparative studies of alternative dynamic replication strategies.We present preliminary results obtained with this simulator,in which we evaluate the performance of six different replication strategies for three different kinds of access patterns.The simulation results show that the best strategy has significant savings in latency and bandwidth consumption if the access patterns contain a moderate amount of gerographical locality.

Cardiac MR image segmentation using CHNN and level set method

Although cardiac magnetic resonance imaging (MRI) can provide high spatial resolution image, the area gray level inhomogenization, weak boundary and artifact often can be found in MR images. So, the MR images segmentation using the gradient-based methods is poor in quality and efficiency. An algorithm, based on the competitive hopfield neural network (CHNN) and the curve propagation, is proposed for cardiac MR images segmentation in this paper. The algorithm is composed of two phases. In first phase, a CHNN is used to classify the image objects, and to make gray leve lbomogenization and to recognize weak boundaries in objects. In second phase, based on the classified results, the level set velocity function is created and the object boundaries are extracted with the curve propagation algorithm of the narrow band-based level set. The test results are promising and encouraging.

Robust adaptive neural network control with supervisory controller

The problem of direct adaptive neural network control for a class of uncertain nonlinear systems with unknown constant control gain is studied in this paper. Based on the supervisory control strategy and the approximation capability of multilayer neural networks (MNNs), a novel design scheme of direct adaptive neural network controller is proposed. The adaptive law of the adjustable parameter vector and the matrix of weights in the neural networks and the gain of sliding mode control term to adaptively compensate for the residual and the approximation error of MNNs is determined by using a Lyapunov method. The approach does not require the optimal approximation error to be square-integrable or the supremum of the optimal approximation error to be known. By theoretical analysis, the closed-loop control system is proven to be globally stable in the sense that all signals involved are bounded, with tracking error converging to zero. Simulation results demonstrate the effectiveness of the approach.

Research on Optimize Prediction Model and Algorithm about Chaotic Time Series

We put forward a chaotic estimating model, by using the parameter of the chaotic system, sensitivity of the parameter to inching and control the disturbance of the system, and estimated the parameter of the model by using the best update option. In the end, we forecast the intending series value in its mutually space. The example shows that it can increase the precision in the estimated process by selecting the best model steps. It not only conquer the abuse of using detention inlay technology alone, but also decrease blindness of using forecast error to decide the input model directly, and the result of it is better than the method of statistics and other series means. Key words chaotic time series - parameter identification - optimal prediction model - improved change ruler method CLC number TP 273 Foundation item: Supported by the National Natural Science Foundation of China (60373062)Biography: JIANG Wei-jin (1964-), male, Professor, research direction: intelligent compute and the theory methods of distributed data processing in complex system, and the theory of software.

Grid Technologies ＆ Applications：Architecture ＆ Achievements

The 18 months since CHEP'2000 have seen significant advances in Grid computing,both within and outside high energy physics,While in early 2000,Grid Computing was a novel concept that most CHEP attendees were being exposed to for the first time,we now see considerable consensus on Grid architecture,a solid and widely adopeted technology base,major funding initiatives,a wide variety of projects developing applications and technologies,and major deployment projects aimed at creating robust Grid infrastructures,I provide a summary of major developments and trends,focusing on the Globus open source Grid software project and the GriPhyN data grid project.

Wavelet Energy Feature Extraction and Matching for Palmprint Recognition

According to the fact that the basic features of a palmprint, includingprincipal lines, wrinkles and ridges, have different resolutions, in this paper we analyzepalmprints using a multi-resolution method and define a novel palmprint feature, which calledwavelet energy feature (WEF), based on the wavelet transform. WEF can reflect the wavelet energydistribution of the principal lines, wrinkles and ridges in different directions at differentresolutions (scales), thus it can efficiently characterize palmprints. This paper also analyses thediscriminabilities of each level WEF and, according to these discriminabilities, chooses a suitableweight for each level to compute the weighted city block distance for recognition. The experimentalresults show that the order of the discriminabilities of each level WEF, from strong to weak, is the4th, 3rd, 5th, 2nd and 1st level. It also shows that WEF is robust to some extent in rotation andtranslation of the images. Accuracies of 99.24% and 99.45% have been obtained in palmprintverification and palmprint identification, respectively. These results demonstrate the power of theproposed approach.

Online Palmprint Identification System for Civil Applications

In this paper, a novel biometric identification system is presented toidentify a person''s identity by his/her palmprint. In contrast to existing palmprint systems forcriminal applications, the proposed system targets at the civil applications, which requireidentifying a person in a large database with high accuracy in real-time. The system is constitutedby four major components: User Interface Module, Acquisition Module, Recognition Module and ExternalModule. More than 7,000 palmprint images have been collected to test the performance of the system.The system can identify 400 palms with a low false acceptance rate, 0.02%, and a high genuineacceptance rate, 98.83%. For verification, the system can operate at a false acceptance rate, 0.017%and a false rejection rate, 0.86%. The execution time for the whole process including imagecollection, preprocessing, feature extraction and matching is less than 1 second.