The concept of `diversity' has been one of the main open issues in the field of multiple classifier systems. In this paper we address a facet of diversity related to its effectiveness for ensemble construction, namely, explicitly using diversity measures for ensemble construction techniques based on the kind of overproduce and choose strategy known as ensemble pruning. Such a strategy consists of selecting the (hopefully) more accurate subset of classifiers out of an original, larger ensemble. Whereas several existing pruning methods use some combination of individual classifiers' accuracy and diversity, it is still unclear whether such an evaluation function is better than the bare estimate of ensemble accuracy. We empirically investigate this issue by comparing two evaluation functions in the context of ensemble pruning: the estimate of ensemble accuracy, and its linear combination with several well-known diversity measures. This can also be viewed as using diversity as a regularizer, as suggested by some authors. To this aim we use a pruning method based on forward selection, since it allows a direct comparison between different evaluation functions. Experiments on thirty-seven benchmark data sets, four diversity measures and three base classifiers provide evidence that using diversity measures for ensemble pruning can be advantageous over using only ensemble accuracy, and that diversity measures can act as regularizers in this context.

In this paper we propose cryptosystems based on subgroup distortion in hyperbolic groups. We also include concrete examples of hyperbolic groups as possible platforms.

A class of Xorshift Random Number Generators (RNGs) are introduced by Marsaglia. We have proposed an algorithm which constructs a primitive Xorshift RNG from a given prim- itive polynomial. We also have shown a weakness present in those RNGs and suggested its solution. A separate algorithm also proposed which returns a full periodic Xorshift generator with desired number of Xorshift operations.

SQL Injection is one of the vulnerabilities in OWASP's Top Ten List forWeb Based Application Exploitation. These type of attacks take place on Dynamic Web applications as they interact with databases for various operations. Current Content Management System like Drupal, Joomla or Wordpress have all information stored in their databases. A single intrusion into these type of websites can lead to overall control of websites by an attacker. Researchers are aware of basic SQL Injection attacks, but there are numerous SQL Injection attacks which are yet to be prevented and detected. Over here, we present the extensive review for the Advanced SQL Injection attack such as Fast Flux SQL Injection, Compounded SQL Injection and Deep Blind SQL Injection. We also analyze the detection and prevention using the classical methods as well as modern approaches. We will be discussing the Comparative Evaluation for prevention of SQL Injection.

The paper concerns a risk assessment and management methodology in critical infrastructures. The aim of the paper is to present researches on risk management within the experimentation tool based on the OSCAD software. The researches are focused on interdependent infrastructures where the specific phenomena, like escalating and cascading effects, may occur. The objective of the researches is to acquire knowledge about risk issues within interdependent infrastructures, to assess the usefulness of the OSCAD-based risk manager in this application domain, and to identify directions for further R&D works. The paper contains a short introduction to risk management in critical infrastructures, presents the state of the art, and the context, plan and scenarios of the performed validation experiments. Next, step by step, the validation is performed. It encompasses two collaborating infrastructures (railway, energy). It is shown how a hazardous event impacts the given infrastructure (primary and secondary eects) and the neighbouring infrastructure. In the conclusions the experiments are summarized, the OSCAD software assessed and directions of the future works identified.

The availability of cheap and widely applicable person identification techniques is essential due to a wide-spread usage of online services. The dynamics of typing is characteristic to particular users, and users are hardly able to mimic the dynamics of typing of others. State-of-the-art solutions for person identification from the dynamics of typing are based on machine learning. The presence of hubs, i.e., few instances that appear as nearest neighbours of surprisingly many other instances, have been observed in various domains recently and hubness-aware machine learning approaches have been shown to work well in those domains. However, hubness has not been studied in the context of person identification yet, and hubnessaware techniques have not been applied to this task. In this paper, we examine hubness in typing data and propose to use ECkNN, a recent hubness-aware regression technique together with dynamic time warping for person identification. We collected time-series data describing the dynamics of typing and used it to evaluate our approach. Experimental results show that hubness-aware techniques outperform state-of-the-art time-series classifiers.

The article contains a survey of methods of the mobile development with the FMX Application platform, which allows to build multi-platform solutions for the efficient Human-Computer Interaction. The test projects illustrate some important conclusions regarding the design and testing of mobile applications for iOS and Android operating systems. They demonstrate navigation controls designed in the skeumorphic and flat manner with some comparisons based on interviews with users in several age ranges. Test apps provide also touch gestures, sensor integration and connections to remote internet data sources. Some additional considerations about the localization and internationalization of the mobile applications built with the FMX platform were also presented. The proposed implementation of the software engineering methods for the mobile application development provides new insights, valuable for software developers dealing with the new FMX platform on iOS and Android.

The paper presents the result of an evaluation of the performance of different message broker system configurations, which lead to the construction of the specific architecture guidelines for such systems. The examples are provided for an exemplary middleware messaging server software - RabbitMQ, set in high availability - enabling and redundant configurations. Rabbit MQ is a message queuing system realizing the middleware for distributed systems that implements the Advanced Message Queuing Protocol. The scalability and high availability design issues are discussed and the possible cluster topologies and their impact is presented. Since HA and performance scalability requirements are in conflict, scenarios for using clustered RabbitMQ nodes and mirrored queues are interesting and have to be considered with specific workloads and requirements in mind. The results of performance measurements for some topologies are also reported in this article.

Evaluating the image quality is a very important problem in image and video processing. Numerous methods have been proposed over the past years to automatically evaluate the quality of images in agreement with human quality judgments. The purpose of this work is to present subjective and objective quality assessment methods and their classification. Eleven widely used and recommended by International Telecommunication Union (ITU) subjective methods are compared and described. Thirteen objective method is briefly presented (including MSE, MD, PCC, EPSNR, SSIM, MS-SSIM, FSIM, MAD, VSNR, VQM, NQM, DM, and 3D-GSM). Furthermore the list of widely used subjective quality data set is provided.

This paper presents novel approach to the Huffman’s asynchronous sequential circuit two valued Boolean switching system design. The algorithm is implemented as software using distributed, service oriented application model with means of the web service component design. It considers method implementation challenges, both towards Moore and Mealy structures with particular respect to the estimation of the Huffman’s minimization algorithm computational complexity. The paper provides implementation details, theoretical model estimation and experimental results that acknowledge the theoretical approach in practice. This paper also examine the multistep design process implementation and its problems inherent in web service based environment both for development and educational purposes.

The paper features a comprehensive approach to risk management worked out during the ValueSec project (EU 7th Framework Programme). The motivation for research was presented, along with the course of the research, achieved project results and validation results. The methodology of risk management and a supporting tool were developed as a result of the project. They help decision makers to make complex strategic decisions about security measures. These complex decision-related problems were the reason to launch the research. The elaborated methodology is based on three pillars: assessment of the considered security measure ability to reduce risk, costs and benefits analysis with respect to the security measure application, and analysis of legal, social, cultural, and other restrictions that might impair or even destroy the efficiency of the functioning measures. In the project these restrictions are called qualitative criteria. The main added value of the ValueSec project is the elaboration of a special software module to analyse impacts of qualitative criteria on the considered measure. Based on the methodology, a ValueSec Toolset prototype was developed. The prototype was then validated in the following application domains: mass event, railway transport security, airport and air transport security, protection against flood, and protection of smart grids against cyber-attacks.