11734040
Analyzing Security Protocols Using Association Rule Mining
Current studies to analyzing security protocols using formal methods require users to predefine authentication goals. Besides, they are unable to discover potential correlations between secure messages. This research attempts to analyze security protocols using data mining. This is done by extending the idea of association rule mining and converting the verification of protocols into computing the frequency and confidence of inconsistent secure messages. It provides a novel and efficient way to analyze security protocols and find out potential correlations between secure messages. The conducted experiments demonstrate our approaches.
7632435
Multi-level Semantic Analysis for Sports Video
There has been a huge increase in the utilization of video as one of the most preferred type of media due to its content richness for many significant applications including sports. To sustain an ongoing rapid growth of sports video, there is an emerging demand for a sophisticated content-based indexing system. Users recall video contents in a high-level abstraction while video is generally stored as an arbitrary sequence of audio-visual tracks. To bridge this gap, this paper will demonstrate the use of domain knowledge and characteristics to design the extraction of high-level concepts directly from audio-visual features. In particular, we propose a multi-level semantic analysis framework to optimize the sharing of domain characteristics.
45104603
A Similarity Search Algorithm to Predict Protein Structures
Accurate prediction of protein structures is very important for many applications such as drug discovery and biotechnology. Building side chains is an essential to get any reliable prediction of the protein structure for any given a protein main chain conformation. Most of the methods that predict side chain conformations use statistically generated data from known protein structures. It is a computationally intractable problem to search suitable side chains from all possible rotamers simultaneously using information of known protein structures. Reducing the number of possibility is a main issue to predict side chain conformation. This paper proposes an enumeration based similarity search algorithm to predict side chain conformations. By introducing “beam search” technique, a significant number of unrelated side chain rotamers can easily be eliminated. As a result, we can search for suitable residue side chains from all possible side chain conformations.
6262105
A New Indexing Method for High Dimensional Dataset
Indexing high dimensional datasets has attracted extensive attention from many researchers in the last decade. Since R-tree type of index structures are known as suffering “curse of dimensionality” problems, Pyramid-tree type of index structures, which are based on the B-tree, have been proposed to break the curse of dimensionality. However, for high dimensional data, the number of pyramids is often insufficient to discriminate data points when the number of dimensions is high. Its effectiveness degrades dramatically with the increase of dimensionality. In this paper, we focus on one particular issue of “curse of dimensionality”; that is, the surface of a hypercube in a high dimensional space approaches 100% of the total hypercube volume when the number of dimensions approaches infinite. We propose a new indexing method based on the surface of dimensionality. We prove that the Pyramid tree technology is a special case of our method. The results of our experiments demonstrate clear priority of our novel method.
17883721
Classification of self-consumable highlights for soccer video summaries
An effective scheme for soccer summarization is significant to improve the usage of this massively growing video data. The paper presents an extension to our recent work which proposed a framework to integrate highlights into play-breaks to construct more complete soccer summaries. The current focus is to demonstrate the benefits of detecting some specific audio-visual features during play-break sequences in order to classify highlights contained within them. The main purpose is to generate summaries which are self-consumable individually. To support this framework, the algorithms for shot classification and detection of near-goal and slow-motion replay scenes is described. The results of our experiment using 5 soccer videos (20 minutes each) show the performance and reliability of our framework
6445970
Integrative Security Management for Web-Based Enterprise Applications
In enterprise environment, security becomes increasingly important and costly. Enterprises are struggling to protect the increasing amount of disparate resources. Simple patchwork of security controls no longer suffices. Enterprises require a comprehensive solution that provides centralized security management, from authentication, to authorization and to auditing. To this end, we present a design and implementation of an integrative security management solution for Web-based enterprise applications, WebDaemon. It provides Single Sign-On to multiple Web applications. It also provides restricted access to Web-based content, portals, and Web applications based on Role-Based Access Control (RBAC) policies. The WebDaemon can help enterprises secure all Web resources with consistency of policy management and reduced administrative costs.
646545
Designing and Evaluating an XPath Dialect for Linguistic Queries
Linguistic research and natural language processing employ large repositories of ordered trees. XML, a standard ordered tree model, and XPath, its associated language, are natural choices for linguistic data and queries. However, several important expressive features required for linguistic queries are missing or hard to express in XPath. In this paper, we motivate and illustrate these features with a variety of linguistic queries. Then we propose extensions to XPath to support linguistic queries, and design an efficient query engine based on a novel labeling scheme. Experiments demonstrate that our language is not only sufficiently expressive for linguistic trees but also efficient for practical usage.
10274461
Pattern Classification Using Rectified Nearest Feature Line Segment
This paper proposes a new classification method termed Rectified Nearest Feature Line Segment (RNFLS). It overcomes the drawbacks of the original Nearest Feature Line (NFL) classifier and possesses a novel property that centralizes the probability density of the initial sample distribution, which significantly enhances the classification ability. Another remarkable merit is that RNFLS is applicable to complex problems such as two-spirals, which the original NFL cannot deal with properly. Experimental comparisons with NFL, NN(Nearest Neighbor), k-NN and NNL (Nearest Neighbor Line) using artificial and real-world datasets demonstrate that RNFLS offers the best performance.
2310959
XKvalidator: a constraint validator for XML
The role of XML in data exchange is evolving from one of merely conveying the structure of data to one that also conveys its semantics. In particular, several proposals for key and foreign key constraints have recently appeared, and aspects of these proposals have been adopted within XMLSchema.In this paper, we examine the problem of checking keys and foreign keys in XML documents using a validator based on SAX. The algorithm relies on an indexing technique based on the paths found in key definitions, and can be used for checking the correctness of an entire document (bulk checking) as well as for checking updates as they are made to the document (incremental checking). The asymptotic performance of the algorithm is linear in the size of the document or update. Furthermore, experimental results demonstrate reasonable performance.
21454000
Modelling software operational reliability via input domain-based reliability growth model
Operational reliability of programs depends upon many factors imposed by design, testing, and operation of the programs. In the testing stage, the main imperfect factors which can affect operational reliability are faults, testing time, fault correction, testing profile and operation profile. The proposed modelling process takes these factors into account. It consists of two testing stages and one operational stage. In the testing stages, partition testing and an input domain-based reliability growth model are used to evaluate the reliability growth. Based on the profile coverage between testing and operational profiles, a method is developed to partition the input domain, so that the testing profile can follow the given operational profile of a program. In the operational stage, the proposed reliability model uses the remaining faults from testing stages as the source of unreliability. A case study is conducted using the proposed models.