Input manipulation attacks are becoming one of the most common attacks against Web Applications and Web Services security. As the use of firewalls and other security mechanisms are not effective against application-le...
详细信息
Input manipulation attacks are becoming one of the most common attacks against Web applications and Web services security. As the use of firewalls and other security mechanisms are not effective against application-le...
详细信息
Input manipulation attacks are becoming one of the most common attacks against Web applications and Web services security. As the use of firewalls and other security mechanisms are not effective against application-level attacks, new means of defense are needed. This paper presents a framework proposal to solve this problem, securing applications against input manipulation attacks. The proposed mechanism offers a reusable approach by the use of XML files and a XML Schema for security parameters specification. Furthermore, a case of study and experiment results are presented. The experiment demonstrates how common input manipulation flaws could be observed.
Clustering is the process of discovering groups within multidimensional data, based on similarities, with a minimal, if any, knowledge of their structure. Distributed data clustering is a recent approach to deal with ...
详细信息
Clustering is the process of discovering groups within multidimensional data, based on similarities, with a minimal, if any, knowledge of their structure. Distributed data clustering is a recent approach to deal with geographically distributed databases, since traditional clustering methods require centering all databases in a single dataset. Moreover, current privacy requirements in distributed databases demand algorithms with the ability to process clustering securely. Among the unsupervised neural network models, the self-organizing map (SOM) plays a major role. SOM features include information compression while trying to preserve the topological and metric relationship of the primary data space. This paper presents a strategy for efficient cluster analysis in geographically distributed databases using SOM networks. Local datasets relative to database vertical partitions are applied to distinct maps in order to obtain partial views of the existing clusters. Units of each local map are chosen to represent original data and are sent to a central site, which performs a fusion of the partial results. Experimental results are presented for different datasets.
This article presents a novel approach for detection of non-conventional events in videos scenes. This novel approach consists in analyzing in real-time video from a security camera to detect, segment and tracking obj...
详细信息
This article presents a novel approach for detection of non-conventional events in videos scenes. This novel approach consists in analyzing in real-time video from a security camera to detect, segment and tracking objects in movement to further classify its movement as conventional or non-conventional. From each tracked object in the scene features such as position, speed, changes in directions and in the bounding box sizes are extracted. These features make up a feature vector. At the classification step, feature vectors generated from objects in movement in the scene are matched almost in real-time against reference feature vectors previously labeled which are stored in a database and an algorithm based on the instance-based learning paradigm is used to classify the object movement as conventional or non-conventional. Experimental results on video clips from two databases (Parking Lot and CAVIAR) have shown that the proposed approach is able to detect non-conventional events with accuracies between 77% and 82%.
This paper presents a novel approach to the task of automatic music genre classification which is based on multiple feature vectors and ensemble of classifiers. Multiple feature vectors are extracted from a single mus...
详细信息
This paper presents a novel approach to the task of automatic music genre classification which is based on multiple feature vectors and ensemble of classifiers. Multiple feature vectors are extracted from a single music piece. First, three 30-second music segments, one from the beginning, one from the middle and one from end part of a music piece are selected and feature vectors are extracted from each segment. Individual classifiers are trained to account for each feature vector extracted from each music segment. At the classification, the outputs provided by each individual classifier are combined through simple combination rules such as majority vote, max, sum and product rules, with the aim of improving music genre classification accuracy. Experiments carried out on a large dataset containing more than 3,000 music samples from ten different Latin music genres have shown that for the task of automatic music genre classification, the features extracted from the middle part of the music provide better results than using the segments from the beginning or end part of the music. Furthermore, the proposed ensemble approach, which combines the multiple feature vectors, provides better accuracy than using single classifiers and any individual music segment.
More than 80% of AIDS (seropositive) diagnoses during 2001 were among residents of the poorest counties, although these counties represented only one quarter of the population living with diagnosed HIV due to the high...
More than 80% of AIDS (seropositive) diagnoses during 2001 were among residents of the poorest counties, although these counties represented only one quarter of the population living with diagnosed HIV due to the highly active anti-retroviral therapy (HAART). That is the declines in deaths among persons with AIDS since 2001 were caused primarily by the slower progression of HIV -associated immune deficiency among persons who used HAART. However, AIDS diagnoses and deaths were relatively constant among the poor. The populations in which the HIV epidemic is becoming concentrated (racial, ethnic) need increased access to prevention programs and health care services so the importance of this low cost HIV and AIDS estimator. During the last 10 years, groups with less access to medical care have been affected more and more by the HIV epidemic. To monitoring the status of the epidemic and evaluating the effectiveness of prevention, cheaper HIV diagnoses will be essential. This work presents a novel numerical method of analysis for HIV diagnoses in possible contaminated blood laboratory tests. It turns possible quick estimation in early stages where the numbers of HIV cells are small. The implemented system of pattern recognition is based not only on conventional feature extraction but use also chaotic measurements (fractal dimension and lacunarity estimators). The presented methodology estimates AIDS using secure and relatively low in price techn iques. It is very adequate for underdeveloped or developing nations of Africa, Asia, and Latin America where greater the proportion of the population below the poverty level.
For a given data set, its set of attributes defines its data space representation. The quality of a data space representation is one of the most important factors influencing the performance of a data mining algorithm...
详细信息
Wireless networks represent the new computer paradigm. They have as main function to provide users with permanent access, independently of their physical location. With the decrease in the costs of portable devices an...
详细信息
Distributed genetic algorithms (DGAs) constitute an interesting approach to undertake the premature convergence problem in evolutionary optimization. This is done by spatial partitioning a huge panmitic population int...
详细信息
Distributed genetic algorithms (DGAs) constitute an interesting approach to undertake the premature convergence problem in evolutionary optimization. This is done by spatial partitioning a huge panmitic population into several semi-isolated groups, called demes, each evolving in parallel by its own pace, and possibly exploring different regions of the search space. At the center of such approach lies the migratory process that simulates the swapping of individuals belonging to different demes, in such a way to ensure the sharing of good genetic material. In this paper, we model the migration step in DGAs as an explicit means to promote cooperation among genetic agents, autonomous entities encapsulating GA instances for possibly tackling different sub-problems of a complicated task. The focus is on the characterization of adaptive migration policies in which the choice of what individuals to migrate and/or replace is not defined a priori but according to a more knowledge-oriented rule. Comparative results obtained for a data-mining task were conducted, in order to assess the performance of adaptive migration according to efficiency/effectiveness criteria.
Wireless networks represent the new computer paradigm. They have as main function to provide users with permanent access, independently of their physical location. With the decrease in the costs of portable devices an...
详细信息
Wireless networks represent the new computer paradigm. They have as main function to provide users with permanent access, independently of their physical location. With the decrease in the costs of portable devices and the increase in their capacity, a new concept called ad hoc network appeared. Through this technology, communication is made directly between mobile computers. In this paper, the proposal and validation of a mechanism based on the bandwidth management principle are done to guarantee QoS (Quality of Service) in ad hoc wireless networks. Therefore, a software is developed to simulate ad hoc environments, making connections following the approach of the already proposed mechanism. Several experiences demonstrating the advantages of this method were carried out. They proved that this method guarantees a better use of the transmission channel and, at the same time, accepts more connections.
暂无评论