ACTA TECHNICA NAPOCENSIS ELECTRONICS AND TELECOMMUNICATIONS

URI permanent pentru această colecțiehttps://oasis.utcluj.app/handle/123456789/447

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A NUMERICAL MODEL FOR I/Q MODULATION/DEMODULATION FOR AN FPGA-ENABLED SDR PLATFORM
(Terebes Romulus, 2023-06-21) Bianca L.M. BOTA; Rareș BUTA; Botond S. KIREI; Calin A. FĂRCAȘ; Sorin A. HINTEA
This paper presents a numerical model for I/Q modulation/demodulation implemented in Matlab. This numerical model serves as a starting point for the HDL/FPGA implementation of a baseband processor for a previously developed SDR platform. The numerical model verification is carried out by performing 4, 8, 64, and 256-point QAM transmission over an additive White Gaussian Noise Channel and by comparing numerical and theoretical bit error rates. A partial HDL implementation of the baseband processor is given: the baseband processor generates a 1MHz tone signal that is mixed by the RF fronted, generating a double sideband modulated signal.
AN ANALYSIS OF THE PERFORMANCE OF DIFFERENT DPSK MODULATION DATA FORMATS USING CROSS-POLARIZATION MODULATION BASED 80 Gb/s ALL-OPTICAL WAVELENGTH CONVERSION IN A SINGLE WIDEBAND SOA
(Terebes Romulus, 2024-06-07) SAROJINI R; SIVANANTHA Raja; SELVENDRAN S
At key optical network nodes the efficient deployment of WDM/DWDM technologies can be made possible by wavelength conversion. In this research, Cross-Polarization Modulation (XpolM) based All-Optical Wavelength Conversion (AOWC) using wide band Semiconductor Optical Amplifier (SOA) is obtained. The effectiveness of various optical differential phase modulations on wavelength conversion is analysed. NRZ-DPSK/DPSK, 33%RZ-DPSK, 50%RZ-DPSK and 67%RZ-DPSK/CSRZ-DPSK are investigated here. The data rate is 80 Gb/s and the conversion bandwidth is 1.04 nm. The analysis is extended for Linear, Lorentzian and No-approximation material gain simulation models. The NRZ-DPSK performs better in terms of maximum coupled intensity and ellipticity. CSRZ-displays a power spectral gain of up to 12 dB and shows narrower spectral width.
CHATBOT DESIGNED FOR INTERNATIONAL STUDENTS
(Terebes Romulus, 2024-05-20) BULZESCU Carla-Mihaela; GRAMA Lacrimioara
The main purpose of this paper is to present a chatbot developed for international students. It provides guidance on a range of challenges, including safety, culture shock, housing, language, and academic notes. For this purpose, a dataset of 72 question-and-answer intents was developed from scratch, designed to assist students. The training phase uses the dataset to create the neural network model. The chatbot makes use of established rules and techniques for natural language processing to predict the appropriate responses to user’s demand. Two Python-based versions of the chatbot are developed: one with a user interface, designed using a Flask server connected to a front-end section, and one with a compiler-based method that can handle speech input and output. Both versions achieved high accuracy during the training phase, suggesting good forecasting for the purpose upon which the chatbot was designed.
DDoS ATTACK DETECTION USING SUPERVISED MACHINE LEARNING ALGORITHMS OVER THE CIDDOS2019 DATASET
(Terebes Romulus, 2023-06-22) ZINCA Daniel; DOBROTA Virgil
Distributed Denial-of-Service (DDoS) attacks are one of the most common types of cyber-attacks that can cause severe damage to networks and systems. Traditional methods to detect them rely on signature-based Intrusion Detection Systems (IDS), which are limited by the need of prior knowledge of specific patterns and by the usual ineffectiveness against zero-day attacks. However machine learning (ML) algorithms have the potential to support the detection of new and unknown attacks. This article compares the DDoS detection performance of three Machine Learning techniques: Gaussian Naïve Bayes, Logistic Regression and Random Forest, based on validation metrics such as precision, recall and F1 score. The system was trained using three datasets extracted from CICDDoS2019 database. The results proved the detection of attacks at Layer 4 (TCP SYN/ UDP flood), and at reflective Layer 7 (MSSQL, NetBIOS). The Random Forests and Logistic Regression methods achieved a precision between 93.7% and 99.4 % over these three datasets.
DESIGN AND IMPLEMENTATION OF A FULL-DUPLEX GROUND STATION FOR THE QO-100 SATELLITE SYSTEM BASED ON SDR AND RASPBERRY PI
(Romulus Terebes, 2024) Nicolae CRIȘAN
Abstract: This paper proposes an approach based on the Adalm-Pluto SDR and Raspberry PI to design a ground station for geostationary satellite communications. The system is designed from modules to be versatile, agile, and scalable. In this case, the usage of modules is mandatory due to the complexity of the communications system, which simultaneously operates two radio channels at 2.4 GHz for uplink and 10 GHz for downlink. Such a combination with SDR (Software Defined Radio) and classic down and up converters benefits from using a Raspberry PI 4 with a powerful processor running under Linux. The proposed system allows the usage of GNU Radio with its powerful graphical interface written in Python. User interface UI has been undertaken by the Raspberry PI’s most versatile display with a touch screen of 7 inches. Another topic the paper addresses is using the helical antenna in front of the Horn antenna at the same focus point established by the dish reflector. The ground station proposed here has been successfully tested to transmit short radio packages containing data about temperature, atmospheric conditions, and voice.
INTEGRATION OF THE SURICATA INTRUSION DETECTION SYSTEM AND OF THE WAZUH SECURITY INFORMATION AND EVENT MANAGEMENT FOR REAL-TIME DENIAL-OF-SERVICE AND DATA TAMPERING DETECTION AND ALERTING
(Terebes Romulus, 2024) Gheorghe-Romeo ANDREICA; IVANCIU Iustin-Alexandru; ZINCA Daniel; DOBROTA Virgil
This paper addresses one of the cybersecurity challenges posed by the rapid growth of IoT and intelligent transport systems. It aims to develop a security monitoring and alerting system for GPS devices in these systems, integrating the Suricata Intrusion Detection System (IDS) mechanism and the Wazuh Security Information and Event Management (SIEM). The solution is focused on detecting, alerting and real-time monitoring for Denial-of-Service (DoS) and Data Tampering attacks, ensuring robust protection against emerging cyber threats in IoT GPS tracking systems
INTRODUCTION TO CYCLIC CODES AND ILLUSTRATION OF THEIR IMPLEMENTATION THROUGH LINEAR FEEDBACK SHIFT REGISTERS WITHIN A PROGRESSIVE WEB APPLICATION
(Romulus Terebes, 2024-06-02) SOFIA Ioana Lavinia
This paper provides an introductory overview of cyclic codes of Hamming type and showcases their effectiveness in detecting and correcting errors in digital communications. Thus, a Progressive Web Application has been developed through React.js and p5.js JavaScript libraries to simulate the coding operations using Linear Feedback Shift Registers. This GUI serves an educational purpose, being used in Information Transmission Theory laboratories so that students could easier comprehend this particular coding scheme. The results obtained highlight the efficiency of developed software application in the e-learning process of cyclic code of Hamming type and its adeptness in error detection and correction within digital communications.
KUBERNETES CONFIGURATION FILES CREATED WITH A PYTHON QUART WEB INTERFACE FOR REAL LIFE SCENARIOS OF KUBERNETES DEPLOYMENTS
(Terebes Romulus, 2024-11-29) DUMITRE Ioan-Alexandru; RUGINA Szabolcs-Gavril; LENGYEL Laszlo-Csongor; RUS Andrei-Bogdan; DOBROTA Virgil
This paper presents the development of a web interface using Python Quart to simplify the creation and management of Kubernetes manifest files. The interface allows users to create, update, delete, and manage Kubernetes resources through an intuitive platform. Developed using Test-Driven Development (TDD) principles, the application minimizes errors and improves reliability by ensuring that each component is rigorously tested before deployment. By leveraging Quart’s asynchronous capabilities, it handles multiple requests efficiently, enhancing scalability and performance. Performance tests with Locust and real-time monitoring with Prometheus show the system's ability to manage multiple users and highlight areas for improvement in request latency.
MOBILE APPLICATION FOR BLE INDOOR POSITIONING
(Technical University of Cluj-Napoca, 2023-12-12) MĂLUȚAN Raul; BRISC Bianca
Distance estimation in indoor localization is mainly solved by Received Signal Strength Indicator (RSSI). In our approach, the RSSI is determined empirically, and it’s used to estimate the distance between the user and beacons in a mobile app solution. Trilateration and Kalman filter help obtain better accuracy. The paper proposes a classical solution for indoor localization, but with features like blueprint implementation, Google Maps integration, and manual beacon positioning.
SECURE ACCESS WITH TELTONIKA GPS TRACKING DEVICES FOR INTELLIGENT TRANSPORTATION SYSTEMS
(Terebes Romulus, 2023-03-27) ANDREICA Gheorghe-Romeo; STANGU Ciprian; IVANCIU Iustin-Alexandru; ZINCA Daniel; DOBROTA Virgil
GPS tracking devices are widely used in industries like logistics, transportation, and security. However, they are susceptible to cyber-attacks, including Man-in-the-Middle (MITM). This study focuses on Teltonika GPS tracking devices and examines the impact of MITM attacks on their operation. We propose implementing encryption protocols and other measures to enhance the security and resilience of Teltonika GPS tracking devices.
SECURITY ISSUES IN INTERNET OF THINGS BOTNETS: A HIGH INTERACTION HONEYPOT APPROACH
(Technical University of Cluj-Napoca, 2023-12-11) LAZAR Alexandru; BLAGA Tudor-Mihai; ZINCA Daniel; DOBROTA Virgil
For a better awareness of the tactics employed by the malicious entities in Internet of Things, a system called Honeypot tricks the attackers into exploiting its “sweet” fake resources. While implementing nine types of devices only six of those were attacked. Despite this, the honeypot managed to capture attacks destined for three devices that were not implemented. Overall, several real-world attacks were captured and analyzed providing different indicators of compromise. No new threats were identified but the server only ran for a short period of time and with limited resources. This approach looks like a promising avenue for creating attacker profiles and collecting data on botnet behavior.
SPATIAL-SPECTRAL CLASSIFICATION OF HYPERSPECTRAL DATA WITH CONTROLLED DATA SEPARATION
(Terebes Romulus, 2023-06-22) MICLEA Andreia Valentina; ABRUDAN Mihaela
Exploring spatial-spectral data frequently involves classifying hyperspectral images using convolutional neural networks. Due to the high complexity of the data and the scarcity of available training samples, hyperspectral image classification presents significant difficulties. In the context of supervised classification, we find that traditional experimental designs are frequently misused in the spectral-spatial processing context, resulting in unfair or biased performance evaluation, particularly when training and testing samples are selected at random from the same dataset. Under these circumstances, the dependence caused by the overlap between training and testing samples may be artificially increased, in breach of the data independence assumption upheld by supervised learning theory. In order to prevent an unbiased classification result, we present in this paper a controlled strategy designed to minimize the overlap between the samples present in the training and the testing data sets. The proposed controlled sampling strategy ensures a more trustworthy generalization of the CNN model by minimizing the issues present in the random sampling approach, such as the inability to determine whether or not an increase in classification accuracy is due to the spatial information incorporated into a classifier or to an increase in the overlap between training and testing data sets. Experiments performed with a wavelet CNN on different HSIs, namely Indian Pines, Pavia University, and Salinas, ensure the generalization of the data under the assumption that the training and data sets are independent from one another, based on a controlled strategy. Considering the high dimension of the HSI image, as a pre-processing step, the evaluation of the proposed framework is done by PCA and FA methods.
UHF-RFID ANTENNA FOR SEMI-ACTIVE ASSISTED TAGS
(Technical University of Cluj-Napoca – Romania, 2023-12-09) CRIȘAN Nicolae
This paper proposes a new concept of using RFID tag antennas more actively in the identification process. This innovative concept is based on antenna native properties that allow RF harvesting for DC biasing, either from the reader or from other proximity RF sources at the same time. Nevertheless, for now, RFID identification tags without a self-DC power supply have become more popular and are referred to as passive. Eventually, both RF and light harvesting processes could be addressed as a foreseeable solution for identification range extension. Soon this trend will lead to the cheapest (printable) RFID tags at competitive prices closely shifted to those of the already mass-produced barcode tags, mainly in use today. The proposed semi-passive tag antenna is working by replacing the IMPINJ-MONZA chip with the EM4325 chip which can be DC supplied by a PV panel. This tag can work as RF energy harvester and can be DC biased as well, being the most capable for the proposed concept. The antenna is printed on paper using a metal powder ink printer and the tag is interrogated using a UHF-RFID reader. The harvesting for tag DC biasing is extended through a very small solar panel, which acts also as a substrate for the RFID antenna. Thus, the extended concept of the semi-active tag could increase the coverage and the sensing range of the reader significantly. This happens especially in daylight or when other nearby RF sources are available, otherwise, the tag will work as an ordinary one. This approach will allow the antenna to be shrunk even further near the Chu-Harrington limit.