Analysis of large-scale topological properties for peer-to-peer networks
In This work we present a thorough study of the topological properties of the Gnutella network, which provides insight into the nature of the underlying system, helps us design high performance algorithms and generates more realistic topologies for simulation experiments. We compare two theoretical models of growing networks with the present real data of the Gnutella network.

title: A Risk-Sensitive Intrusion Detection Model
abstract: Intrusion detection systems (IDSs) must meet the security goals while minimizing risks of wrong detections. In this paper, we study the issue of building a risk-sensitive intrusion detection model. To determinate whether a system calls sequence is normal or not, we consider not only the probability of this sequence belonging to normal sequences set or intrusion sequences set, but also the risk of a false detection. We define the risk model to formulate the expected risk of an intrusion detection decision, and present risk-sensitive machine learning techniques that can produce detection model to minimize the risks of false negatives and false positives. Meanwhile, this model is a hybrid model that combines misuse intrusion detection and anomaly intrusion detection. To achieve a satisfying performance, some techniques are applied to extend this model.

title: Fault-tolerant grid architecture and practice
abstract: Grid computing emerges as effective technologies to couple geographically distributed resources and solve large-scale computational problems in wide area networks. The fault tolerance is a significant and complex issue in grid computing systems. Various techniques have been investigated to detect and correct faults in distributed computing systems. Unreliable fault detection is one of the most effective techniques. Globus as a grid middleware manages resources in a wide area network. The Globus fault detection service uses the well-known techniques based on unreliable fault detectors to detect and report component failures. However, more powerful techniques are required to detect and correct both system-level and application-level faults in a grid system, and a convenient toolkit is also needed to maintain the consistency in the grid. A fault-tolerant grid platform (FTGP) based on an unreliable fault detector and the Globus fault detection service is presented in this paper. The platform offers effective strategies in such three aspects as grid key components, user tasks, and high-level applications.

title: Z Approach to Semantic Web
abstract: The Semantic Web (SW) service is a web application using Semantic Web techniques which usually involve cooperation between several intelligent agents. The design of SW systems requires precise modelling techniques to capture ontology domain properties and application functionalities. We believe that Z as a specification technique can contribute to the Semantic Web-based system development in many ways. In this paper, we firstly conduct a case study of applying Z to the design of a SW service system (online talk discovery), and then present translation techniques and tools which can extract the SW ontology from the Z model automatically. Furthermore, we discuss how existing Z tools, i.e. Z/EVES, can be used to improve the quality of SW ontology design.

title: Text Classification Improved through Automatically Extracted Sequences
abstract: We propose to use the n-multigram model to help the automatic text classification task. This model could automatically discover the latent semantic sequences contained in the document set of each category. Based on the n-multigram model and the n-gram language model, we put forward two text classification algorithms. The experiments on RCV1 show that our proposed algorithm based on n-multigram model can achieve the similar classification performance compared with the one based on n-gram model. However, the model size of our algorithm is only 4.21% of the latter one. Another proposed algorithm based on the combination of nmultigram model and n-gram model improves the micro- F1 and macro-F1 values by 3.5% and 4.5% respectively which support the validity of our approach.

title: Neighborhood formation and anomaly detection in bipartite graphs
abstract: Many real applications can be modeled using bipartite graphs, such as users vs. files in a P2P system, traders vs. stocks in a financial trading system, conferences vs. authors in a scientific publication network, and so on. We introduce two operations on bipartite graphs: 1) identifying similar nodes (Neighborhood formation), and 2) finding abnormal nodes (Anomaly detection). And we propose algorithms to compute the neighborhood for each node using random walk with restarts and graph partitioning; we also propose algorithms to identify abnormal nodes, using neighborhood information. We evaluate the quality of neighborhoods based on semantics of the datasets, and we also measure the performance of the anomaly detection algorithm with manually injected anomalies. Both effectiveness and efficiency of the methods are confirmed by experiments on several real datasets.

title: Online latent variable detection in sensor networks
abstract: Sensor networks attract increasing interest, for a broad range of applications. Given a sensor network, one key issue becomes how to utilize it efficiently and effectively. In particular, how can we detect the underlying correlations (latent variables) among many co-evolving sensor measurements? Can we do it incrementally? We present a system that can (1) collect the measurements from the real wireless sensors; (2) process them in real-time; and (3) determine the correlations (latent variables) among the sensor streams on the fly.

title: Design synthesis from interaction and state-based specifications
abstract: Interaction-based and state-based modeling are two complementary approaches of behavior modeling. The former focuses on global interactions between system components. The latter concentrates on the internal states of individual components. Both approaches have been proven useful in practice. One challenging and important research objective is to combine the modeling power of both effectively and then use the combination as the basis for automatic design synthesis. We present a combination of interaction-based and state-based modeling, namely, live sequence charts and Z, for system specification. We then propose a way of generating distributed design from the combinations. Our approach handles systems with intensive interactive behaviors as well as complex state structures