Pre-paid Voice Services Based on openBTS Platform

Import 03/11/2016Táto diplomová práca nadväzuje na moju bakalársku prácu s názvom OpenBTS a její integrace do telekomunikační sítě. V práci sa detailne venujem konfigurácii tohto projektu a možnosti prepojenia medzi viacerými Asterisk systémami. Využitím rôznych nástrojov je v diplomovej práci implementovaný vlastný účtovací systém, na základe ktorého môžem z OpenBTS vytvoriť nízkonákladového mobilného operátora.This diploma thesis knots on my bachelor thesis titled OpenBTS and its Integration into Telecommunication Network. This work gives detailed explanation of the project configuration and describes connectivity options with multiple Asterisk systems. As the title implies, this diploma thesis presents implementation of its own billing system, which in collaboration with OpenBTS system can be operated as a low-cost mobile operator.440 - Katedra telekomunikační technikyvýborn

OpenBTS and its Integration into Telecommunication Network

Import 05/08/2014Táto bakalárska práca zoznámi čitateľov so softwarom OpenBTS, prostredníctvom ktorého je spolu s pobočkovou ústredňou Asterisk a softwarovo riadeného vysielača USRP možné vytvoriť si svoju vlastnú GSM sieť. Ďalej detailne popisuje inštaláciu a konfiguráciu jednotlivých komponentov potrebných pre korektnú funkčnosť, ktorá bude overovaná uskutočňovaním telefónnych hovorov a zasielaním sms správ medzi jednotlivými mobilnými zariadeniami v sieti. Ako už z názvu vyplýva, práca sa bude zaoberať možnosťou rozšírenia siete OpenBTS, respektíve jeho pobočkovej ústredne Asterisk, pripojením SIP a IAX trunk providera.This bachelor thesis will familiarize readers with creating their own GSM network, which can be operated with OpenBTS software, Asterisk PBX and universal software radio peripheral USRP. Further it describes the detail installation and configuration of individual components required for correct functionality, which will be verified by making phone calls and sending text messages between two mobile devices in this GSM network. As the title implies, this thesis will deal with the possibility of linking OpenBTS or more precisely its PBX Asterisk with other provider components, specifically SIP and IAX trunk.440 - Katedra telekomunikační technikyvýborn

Traffic Management by Admission Control in IMS Networks

The paper deals with traffic management in IP multimedia subsystem (IMS) networks. The aim of this article is ensuring quality of service (QoS) in IMS network. Admission control (AC) is used to manage incoming traffic and to prevent the network congestion. The main function of AC is to maximize the utilization of network resources and to ensure the level of QoS. AC was applied on constant bit rate (CBR) and variable bit rate (VBR) traffic. Three methods were chosen for VBR traffic and they were compared. The last part of the article deals with simulations CBR and VBR traffic before and after application of AC

Multi-modal rigid image registration and segmentation using multi-stage forward path regenerative genetic algorithm

Medical image diagnosis and delineation of lesions in the human brain require information to combine from different imaging sensors. Image registration is considered to be an essential pre-processing technique of aligning images of different modalities. The brain is a naturally bilateral symmetrical organ, where the left half lobe resembles the right half lobe around the symmetrical axis. The identified symmetry axis in one MRI image can identify symmetry axes in multi-modal registered MRI images instantly. MRI sensors may induce different levels of noise and Intensity Non-Uniformity (INU) in images. These image degradations may cause difficulty in finding true transformation parameters for an optimization technique. We will be investigating the new variant of evolution strategy of genetic algorithm as an optimization technique that performs well even for the high level of noise and INU, compared to Nesterov, Limited-memory Broyden-Fletcher-Goldfarb-Shanno algorithm (LBFGS), Simulated Annealing (SA), and Single-Stage Genetic Algorithm (SSGA). The proposed new multi-modal image registration technique based on a genetic algorithm with increasing precision levels and decreasing search spaces in successive stages is called the Multi-Stage Forward Path Regenerative Genetic Algorithm (MFRGA). Our proposed algorithm is better in terms of overall registration error as compared to the standard genetic algorithm. MFRGA results in a mean registration error of 0.492 in case of the same level of noise (1-9)% and INU (0-40)% in both reference and template image, and 0.317 in case of a noise-free template and reference with noise levels (1-9)% and INU (0-40)%. Accurate registration results in good segmentation, and we apply registration transformations to segment normal brain structures for evaluating registration accuracy. The brain segmentation via registration with our proposed algorithm is better even in cases of high levels of noise and INU as compared to GA and LBFGS. The mean dice similarity coefficient of brain structures CSF, GM, and WM is 0.701, 0.792, and 0.913, respectively.Web of Science148art. no. 150

Augmenting speech quality estimation in software-defined networking using machine learning algorithms

With the increased number of Software-Defined Networking (SDN) installations, the data centers of large service providers are becoming more and more agile in terms of network performance efficiency and flexibility. While SDN is an active and obvious trend in a modern data center design, the implications and possibilities it carries for effective and efficient network management are not yet fully explored and utilized. With most of the modern Internet traffic consisting of multimedia services and media-rich content sharing, the quality of multimedia communications is at the center of attention of many companies and research groups. Since SDN-enabled switches have an inherent feature of monitoring the flow statistics in terms of packets and bytes transmitted/lost, these devices can be utilized to monitor the essential statistics of the multimedia communications, allowing the provider to act in case of network failing to deliver the required service quality. The internal packet processing in the SDN switch enables the SDN controller to fetch the statistical information of the particular packet flow using the PacketIn and Multipart messages. This information, if preprocessed properly, can be used to estimate higher layer interpretation of the link quality and thus allowing to relate the provided quality of service (QoS) to the quality of user experience (QoE). This article discusses the experimental setup that can be used to estimate the quality of speech communication based on the information provided by the SDN controller. To achieve higher accuracy of the result, latency characteristics are added based on the exploiting of the dummy packet injection into the packet stream and/or RTCP packet analysis. The results of the experiment show that this innovative approach calculates the statistics of each individual RTP stream, and thus, we obtain a method for dynamic measurement of speech quality, where when quality decreases, it is possible to respond quickly by changing routing at the network level for each individual call. To improve the quality of call measurements, a Convolutional Neural Network (CNN) was also implemented. This model is based on two standard approaches to measuring the speech quality: PESQ and E-model. However, unlike PESQ/POLQA, the CNN-based model can take delay into account, and unlike the E-model, the resulting accuracy is much higher.Web of Science2110art. no. 347

Efficient detection of spam over internet telephony by machine learning algorithms

Recent trends show a growing interest in VoIP services and indicate that guaranteeing security in VoIP services and preventing hacker communities from attacking telecommunication solutions is a challenging task. Spam over Internet Telephony (SPIT) is a type of attack which is a significant detriment to the user's experience. A number of techniques have been produced to detect SPIT calls. We reviewed these techniques and have proposed a new approach for quick, efficient and highly accurate detection of SPIT calls using neural networks and novel call parameters. The performance of this system was compared to other state-of-art machine learning algorithms on a real-world dataset, which has been published online and is publicly available. The results of the study demonstrated that new parameters may help improve the effectiveness and accuracy of applied machine learning algorithms. The study explored the entire process of designing a SPIT detection algorithm, including data collection and processing, defining suitable parameters, and final evaluation of machine learning models.Web of Science1013342613341

Inovativní přístup k detekci spamu přes internetovou telefonii použitím metod umělé inteligence

The dissertation thesis deals with the need to provide a new approach to a protection from Spam over Internet Telephony. It is not an entirely trivial matter to ensure the security of the VoIP services and attacks on telecommunication solutions, built on VoIP technology, grow with an increasing number of active users in last two decades. Spam over Internet Telephony (SPIT) is one of the attacks going to have a significant impact on the user experience. Various techniques have been presented to detect SPIT calls so far, however, nobody has devoted his/her research to the application of modern artificial intelligence algorithms on SPIT detection. It is my motivation to propose an innovative detection mechanism which is the primary goal of my dissertation thesis. Due to nonexistence of active open-source projects dedicated to VoIP attacks, which I could use for creation of the suitable dataset, I had to develop my own tool. No project dispose of sophisticated SPIT detection, and many scientific research papers work with synthetic data, which behave according to the defined models. By processing a wide range of data from various sources, using different statistical and data mining tools, I focused my research on the behavioral characteristics of individual users in the telecommunications chain. I was able to determine the decisive factors for the design and innovative concept of a classification system that is able to distinguish between a regular user and a SPIT attacker. Among other things, this dissertation brings a new approach to the emulation SIP relations based on Markov chains, as well as the design of a new open-source honeypot with the advanced features.Dizertačná práca sa zaoberá potrebou poskytnúť nový prístup k ochrane pred spamom cez internetovú telefóniu. Zabezpečiť bezpečnosť VoIP služieb nie je úplne triviálna záležitosť a útoky na telekomunikačné riešenia postavené na technológii VoIP v posledných dvoch desaťročiach narastajú s rastúcim počtom aktívnych používateľov. Spam over Internet Telephony (SPIT) je jedným z útokov, ktorý bude mať významný vplyv na používateľskú skúsenosť. Doteraz boli prezentované rôzne techniky na detekciu SPIT hovorov, avšak nikto doposiaľ nevenoval svoj výskum aplikácii moderných algoritmov umelej inteligencie na ich detekciu. Mojou motiváciou je navrhnúť inovatívny detekčný mechanizmus, čo je primárnym cieľom mojej dizertačnej práce. Vzhľadom na neexistenciu aktívnych open-source projektov venovaných VoIP útokom, ktoré by som mohol použiť na vytvorenie vhodného datasetu, som si musel vyvinúť vlastný nástroj. Žiadny projekt nedisponuje sofistikovanou detekciou SPIT útokov a mnohé vedeckovýskumné práce pracujú so syntetickými dátami, ktoré sa správajú podľa definovaných modelov. Spracovaním širokého spektra údajov z rôznych zdrojov, s využitím rôznych štatistických a data miningových nástrojov som zameral svoj výskum na charakteristiky správania jednotlivých používateľov v telekomunikačnom reťazci. Podarilo sa mi určiť rozhodujúce faktory pre návrh inovatívneho klasifikačného systému, ktorý je schopný rozlíšiť medzi bežným používateľom a SPIT útočníkom. Táto dizertačná práca okrem iného prináša nový prístup v emulácii SIP relácii založeným na Markovových reťazcoch, ako aj návrh nového open-source honeypotu disponujúceho pokročilými funkciami.440 - Katedra telekomunikační technikyvyhově