2023. 4th Issue

Volume XV, Number 4

Table of contents 

Full issue   



Pal Varga
Key trends in applied ICT technologies for 2024

We arrived at a many-ways turbulent era at the end of 2023. Focusing on the science and technology, the evolution of Generative AI (GenAI) is at the forefront of the changes. Previously a subject of theoretical discourse, GenAI is now real and practical. This shift is not just about technological advancement but has become strategically important in various areas, from science to education and business to company operations. Enterprises are expected to implement GenAI in real-world applications, moving from a heavy emphasis on training and infrastructure costs to a more nuanced consideration of inference and operational expenses.




Eszter Udvary
Integration of QKD Channels to Classical High-speed Optical Communication Networks 

Integrating Quantum Key Distribution service with classical high-speed optical data transmission using a dense wavelength division multiplexing technique in a fiber is a cost-effective solution to improve the network's security. In this multichannel system, several noise sources degrade the quality of the quantum channel. The dominant degradation effect is determined by modeling in different cases. Optical filtering cannot decrease spontaneous Raman Scattering caused by the classical optical channels. So this nonlinear optical effect is investigated in detail with different system parameter setups. The optimal channel allocation and the required bandgap between the classical and quantum channels are determined.

DOI: 10.36244/ICJ.2023.4.1


Ammar Al-Adhami, Yasir Al-Adhami, and Taha A. Elwi
A 3D Antenna Array based Solar Cell Integration for Modern MIMO Systems

In this work, a design of a 3D array antenna based solar panel integration for self-powered applications in modern wireless communication network. Such array configuration is proposed for Multi Input Multi Output (MIMO) applications. The proposed antenna array is structured as a cubical geometry integrated to a solar panel. Such integration is employed to achieve a selfpowered node. The proposed antenna is designed to perform an excellent size reduction at sub-6GHz frequency bands when designed with the aid of the metamaterial (MTM) structures. The antenna performance is enhanced by Moore fractal geometry based on electromagnetic band gap (EBG) defects in the ground plane. The proposed antenna is found to provide a moderate gain at 3.6GHz, 3.9GHz, and 4.9GHz. The antenna array shows low coupling effects, below -20dB, due the array configuration in a cubical shape arrangement. The proposed work is extended to evaluate effectively the bit error rate (BER) and channel capacity (CC), when the proposed antenna system is located in real world communication environments. Therefore, QPSK modulation scheme is considered to suite the applications of 5G systems. The amount of the harvested solar energy is considered the limit to manage the total signal to noise ratio (SNR) in that is applied to the proposed communication scheme. This work is considered for practical aspect issues that is related with amount for the generated power from such integration with solar panel and the total generated SNR. Finally, the comparison between measured and simulated data reveals an excellent agreement between them.

DOI: 10.36244/ICJ.2023.4.2


Beatrix Koltai, András Gazdag, and Gergely Ács  
Improving CAN anomaly detection with correlation-based signal clustering 

Communication on the Controller Area Network (CAN) in vehicles is notably lacking in security measures, rendering it susceptible to remote attacks. These cyberattacks can potentially compromise safety-critical vehicle subsystems, and therefore endanger passengers and others around them. Identifying these intrusions could be done by monitoring the CAN traffic and detecting abnormalities in sensor measurements. To achieve this, we propose integrating time-series forecasting and signal correlation analysis to improve the detection accuracy of an onboard intrusion detection system (IDS). We predict sets of correlated signals collectively and report anomaly if their combined prediction error surpasses a predefined threshold. We show that this integrated approach enables the identification of a broader spectrum of attacks and significantly outperforms existing state-of-the-art solutions.

DOI: 10.36244/ICJ.2023.4.3


Péter Orosz, Balázs Nagy, Pál Varga
Detection strategies for post-pandemic DDoS profiles 
The global pandemic lockdowns fostered the digital transition of companies worldwide since most of their employees worked from home using public or private cloud services. Accordingly, these services became the primary targets of the latest generation DDoS threats. While some features of current DDoS attack profiles appeared before the pandemic period, they became significant and reached their current complexity in the recent period. Besides applying novel methods and tools, the attacks’ frequency, extent, and complexity also increased significantly. The combination of various attack vectors opened the way for multi-vector attacks incorporating a unique blend of L3-L7 attacking profiles. Unifying the hit-and-run method and the multi-vector approach contributed to the remarkable rise in success rate. The current paper has two focal points. First, it discusses the profiles of the latest DDoS attacks discovered in real data center infrastructures. To demonstrate and emphasize the changes in attack profile, we reference attack samples recently collected in various data center networks. Second, it provides a comprehensive survey of the state-of-the-art detection methods related to recent attacks. The paper especially focuses on the accuracy and speed of these, mostly networking-related detection approaches. Furthermore, we define features and quantitative and qualitative requirements to support detection methods handling the latest threat profiles.

DOI: 10.36244/ICJ.2023.4.4