Software Interface for Intelligent Household

Import 04/07/2011Práce se zabývá návrhem vhodného softwaru pro systém ovládání spotřebičů v domácnosti s pouţitím embedded zařízení. Projekt je navrţen tak, aby co nejvíc ulehčil ţivot fyzicky postiţeným lidem. Cílem je návrh a implementace řešení, které by bylo levné, robustní a rozšiřitelné. Tato diplomová práce navazuje na práci Bc. Patrika Dubce, který navrhnul pro dané řešení hardware. V této práci je pak softwarová analýza projektu, návrh prezentační vrstvy a logické vrstvy. Práce je zakončena nasazení a vyhodnocením uţivatelské spokojenosti.The paper describes the design of suitable software for controlling home appliances using embedded devices. The project is designed to make life much easier for physically disabled people. The aim is to design and implement a solution that would be cheap, robust and scalable. This thesis builds on the work of Patrick Bachelor Dubeč, who designed the hardware for the solution. In this thesis, we work with the software project analysis, design of presentation layer and logic layer. The work ends with the deployment and evaluation of user satisfaction.460 - Katedra informatikyvelmi dobř

From Malware Samples to Fractal Images: A New Paradigm for Classification. (Version 2.0, Previous version paper name: Have you ever seen malware?)

To date, a large number of research papers have been written on the classification of malware, its identification, classification into different families and the distinction between malware and goodware. These works have been based on captured malware samples and have attempted to analyse malware and goodware using various techniques, including techniques from the field of artificial intelligence. For example, neural networks have played a significant role in these classification methods. Some of this work also deals with analysing malware using its visualisation. These works usually convert malware samples capturing the structure of malware into image structures, which are then the object of image processing. In this paper, we propose a very unconventional and novel approach to malware visualisation based on dynamic behaviour analysis, with the idea that the images, which are visually very interesting, are then used to classify malware concerning goodware. Our approach opens an extensive topic for future discussion and provides many new directions for research in malware analysis and classification, as discussed in conclusion. The results of the presented experiments are based on a database of 6 589 997 goodware, 827 853 potentially unwanted applications and 4 174 203 malware samples provided by ESET and selected experimental data (images, generating polynomial formulas and software generating images) are available on GitHub for interested readers. Thus, this paper is not a comprehensive compact study that reports the results obtained from comparative experiments but rather attempts to show a new direction in the field of visualisation with possible applications in malware analysis.Comment: This paper is under review; the section describing conversion from malware structure to fractal figure is temporarily erased here to protect our idea. It will be replaced by a full version when accepte

The data extraction using distributed crawler inside multi-agent system

The paper discusses the use of web crawler technology. We created an application based on standard web crawler. Our application is determined for data extraction. Primarily, the application was designed to extract data using keywords from a social network Twitter. First, we created a standard crawler, which went through a predefined list of URLs and gradually download page content of each of the URLs. Page content was then parsed and important text and metadata were stored in a database. Recently, the application was modified in to the form of the multi-agent system. The system was developed in the C# language, which is used to create web applications and sites etc. Obtained data was evaluated graphically. The system was created within Indect project at the VSB-Technical University of Ostrava

X-ware: a proof of concept malware utilizing artificial intelligence

Recent years have witnessed a dramatic growth in utilizing computational intelligence techniques for various domains. Coherently, malicious actors are expected to utilize these techniques against current security solutions. Despite the importance of these new potential threats, there remains a paucity of evidence on leveraging these research literature techniques. This article investigates the possibility of combining artificial neural networks and swarm intelligence to generate a new type of malware. We successfully created a proof of concept malware named X-ware, which we tested against the Windows-based systems. Developing this proof of concept may allow us to identify this potential threat’s characteristics for developing mitigation methods in the future. Furthermore, a method for recording the virus’s behavior and propagation throughout a file system is presented. The proposed virus prototype acts as a swarm system with a neural network-integrated for operations. The virus’s behavioral data is recorded and shown under a complex network format to describe the behavior and communication of the swarm. This paper has demonstrated that malware strengthened with computational intelligence is a credible threat. We envisage that our study can be utilized to assist current and future security researchers to help in implementing more effective countermeasure

An Approach to Customer Behavior Modeling using Markov Decision Process

This paper presents an application of Markov Decision Process method for modeling of selected marketing processes. Based on available realistic data, MDP model is constructed. Customer behavior is represented by a set of states of the model with assigned rewards corresponding to the expected return value. Outcoming arcs then represent actions available to the customer in current state. Favourable outcome rate of available actions is then analyzed, with emphasis on suitability of the model for future predictions of customer behavior

Modelování a simulace diskrétních systémů na paralelních počítačích

The thesis deals with the method of Analytical Programming, which is used for symbolic regression of Workflow Nets. These nets can be used to model various processes, which are demonstrated on several examples. The work will introduce the reader to the theory of Petri nets, Workflow nets, bio-inspired algorithms and the basics of many other methods. In the first part of the thesis, the state of the art is presented. The aims of this thesis are derived from this state of the art. The methods used and the design of the experiment are described below. An important part of the work is the verification of the generated nets quality, therefore a part of the thesis deals with methods for nets analysis. Methods for net analysis were tested on a generated dataset that contained nets of different sizes. The result of the experiment is presented and discussed. The functionality of tool for nets synthesis has been tested in several experiments, three of which are described in this work. These experiments were selected primarily because they demonstrate the solution of real life problems. Generated networks meet the requirements of well-structured networks, while providing a satisfactory solution to the task. At the end of the work, a discussion of the results and a proposal for future continuation of the area are laid out.Dizertační práce se zaměřuje na práci s metodou Analytického programování, která je zde použita pro potřeby symbolické regrese Workflow sítí. Tyto sítě mohou popisovat různorodé procesy, což je v disertační práci demonstrováno ne několika příkladech. Práce seznámí čtenáře se základy Petriho sítí, Workflow sítí, Bio-inspirovaných algoritmů a se základy mnoha dalších metod. V první části práce je rozebrán aktuální stav díla, ze kterého jsou odvozeny cíle práce. Následně jsou popsány použité metody a návrh experimentu. Důležitou součástí práce je vyhodnocení kvality generovaných sítí, a proto se část práce zabývá metodami pro analýzu sítí. Metody pro analýzu sítí byly otestovány na vygenervané datové sadě, která obsahovala sítě různých velikostí. Výsledky jsou publikovány v samostatné kapitole, kde je vyhodnoceny. Funkčnost nástroje pro generování sítí pak byla testována na několika experimentech, z nichž tři jsou popsány i v této práci. Zmíněné experimenty byly vybrány zejména proto, že demonstrují řešení problémů z reálného života. Vygenerované sítě splňují nároky na dobře strukturované sítě a zároveň poskytují dostatečně dobré řešení zadaného úkolu. Na závěr práce probíhá diskuze výsledků a návrh na budoucí pokračování v oblasti.460 - Katedra informatikyvyhově

Ovládání domácnosti mobilním zařízením

Bakalářská práce se zabývá návrhem a tvorbou informačního systému inteligentní domu. Zahrnuje webovou stránku napsanou pomocí programovacího jazyka ASP.NET, mobilní zařízení (J2ME) a server (.NET CF). Data se pak ukládají do databáze, která podporuje SQL. Je zde řešena správa uživatelů, kontakty, přístupová práva, správa služeb, galerie a jednoduchá manipulace s fotografiemi. K znázornění systému je použito UML. Projekt je členěn do několika částí: analýza, návrh, implementace.The Bachelor thesis addresses the problem of designing and creating IS if intelligent house. It consists of a web page implemented using ASP.NET, mobile device (J2ME) and server (.NET CF). Data are stored in diabase, which supports SQL. This project deals with the issues such as the user administration, contacts, rights, service administrativ, gallery and simple photo editor.UML is used to demonstrate the system architecture. The project is divided into several parts: analysis, design, implementation.Prezenční456 - Katedra informatikyvýborn

CREATING DATA OUTPUTS FROM MULTI AGENT TRAFFIC MICRO SIMULATION TO ASSIMILATION WITH REAL TRAFFIC DATA

The intensive development of traffic engineering and technologies that are integrated into vehicles, roads and their surroundings, bring opportunities of real time transport mobility modeling. Based on such model it is then possible to establish a predictive layer that is capable of predicting short and long term traffic flow behavior. It is possible to create the real time model of traffic mobility based on generated data. However, data may have different geographical, temporal or other constraints, or failures. It is therefore appropriate to develop tools that artificially create missing data, which can then be assimilated with real data. This paper presents a mechanism describing strategies of generating artificial data using microsimulations. It describes traffic microsimulation based on our solution of multiagent framework over which a system for generating traffic data is built. The system generates data of a structure corresponding to the data acquired in the real world

Use of the bio-inspired algorithms to find global minimum in force directed layout algorithms

We present bio-inspired approach in a process of finding global minimum of an energetic function that is used in force directed layout algorithms. We have been faced with the issue of displaying large graphs. These graphs arise in the analysis of social networks with the need to view social relationships between entities. In order to find global minimum of an energetic function we employ two bio-inspired algorithms: Differential Evolution and Self- Organizing Migration Algorithm (SOMA). Differential evolution is inspired by crossbreeding of population whereas SOMA is inspired by migration of some species. In this article we will present basics of these algorithms, their results and comparison

Intelligent Malware - Trends and Possibilities

In recent months and years, with more and more computers and computer systems becoming the target of cyberattacks. These attacks are gaining strength and the sophistication of the approach in terms of how to attack. Attackers and Defenders are increasingly using artificial intelligence methods to maximize the success of their actions. For a successful defence, we must be able to anticipate future threats that may come. For these reasons, our research group is engaged in creating experimental software with artificial intelligence to test the possibilities and capabilities of such malware in the event of its deployment. This software has not only malware capabilities but also antimalware and can be used on both sides. This article introduces the reader to the main principles of our design, which can serve as a future platform for cyber defence systems