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Jamming Signal Cancellation by Channel Inversion Power Control for Preserving Covert Communications, Journal of Telecommunications and Information Technology, 2023, nr 2
Full text linkUninformed jammers are used to facilitate covert communications between a transmitter and an intended receiver under the surveillance of a warden. In reality, the signals the uniformed jammer emits to make the warden’s decision uncertain have inadvertently interfered with the detection of the intended receiver. In this paper, we apply truncated channel inversion power control (TCIPC) to both the transmitter and the uninformed jammer. The TCIPC scheme used on the uninformed jammer may help the intended receiver remove jamming signals using the successive interference cancellation (SIC) technique. Under the assumption that the warden knows the channel coefficient between two intended transceivers and achieves the optimal detection power threshold, we form the optimization problem to maximize the effective transmission rate (ETR) under covertness and decoding constraints. With the aim of enhancing covertness-related performance, we achieve the optimal power control parameters and determine system parameter-related constraints required for the existence of these solutions. According to the simulations, the use of the TCIPC scheme on the uninformed jammer significantly improves covertness-related performance in comparison to that of random power control (RPC) and constant power control (CPC) schemes. In addition, simulation results show that, for the TCIPC scheme: 1) the maximum ETR tends to converge as the transmitter’s or the uninformed jammer’s maximum transmit power increases, and 2) there exists an optimal value of the transmitter’s predetermined transmission rate to achieve the optimal performance
Energy Consumption in Wireless Systems Equipped with RES, UAVs, and IRSs, Journal of Telecommunications and Information Technology, 2023, nr 2
Full text linkThis paper investigates energy budget characteristics of mobile base stations (BSs) having the form of unmanned aerial vehicles (UAVs) equipped with radio frequency (RF) transceivers, intelligent reconfigurable surfaces (IRSs), and renewable energy sources (RES). The results obtained highlight the benefits and challenges related to using the aforementioned mobile BS, from the energy-related point of view. The specific cases researched involved two types of UAV devices, i.e. multirotor and fixed-wing (airplane-like) aircraft
Coverage Improvements for Sub-Terahertz Systems Under Shadowing Conditions, Journal of Telecommunications and Information Technology, 2023, nr 3
Full text linkRadio propagation in the millimeter wave and sub-terahertz domain is heavily affected by shadowing conditions. The communication link is blocked without any additional technical means being used. Coverage improvements can be provided by using reflectors, RIS arrays, and repeaters to direct radio waves around corners or obstacles. These concepts show different performance and complexity levels affecting their network deployment. This paper investigates the achievable radio range or the received power to compare specific deployment concepts under realistic propagation conditions. Overall, the repeater solution provides either the largest radio range or the lowest necessary total transmit power compared to reflectors or RIS arrays and, thereby, is the most sustainable approach. A RIS array requires an additional centralized signal processing capacity for calculating optimized RIS settings and results in the highest level of network deployment complexity
Improved Association Rule Mining-Based Data Sanitization for Privacy Preservation Model in Cloud, Journal of Telecommunications and Information Technology, 2023, nr 1
Full text linkData security in cloud services is achieved by imposing a broad range of privacy settings and restrictions. However, the different security techniques used fail to eliminate the hazard of serious data leakage, information loss and other vulnerabilities. Therefore, better security policy requirements are necessary to ensure acceptable data protection levels in the cloud. The two procedures presented in this paper are intended to build a new cloud data security method. Here, sensitive data stored in big datasets is protected from abuse via the data sanitization procedure relying on an improved apriori approach to clean the data. The main objective in this case is to generate a key using an optimization technique known as Corona-integrated Archimedes Optimization with Tent Map Estimation (CIAO-TME). Such a technique deals with both restoration and sanitization of data. The problem of optimizing the data preservation ratio (IPR), the hiding ratio (HR), and the degree of modification (DOM) is formulated and researched as well
Adaptive Rider Feedback Artificial Tree Optimization-Based Deep Neuro-Fuzzy Network for Classification of Sentiment Grade, Journal of Telecommunications and Information Technology, 2023, nr 1
Full text linkSentiment analysis is an efficient technique for expressing users’ opinions (neutral, negative or positive) regarding specific services or products. One of the important benefits of analyzing sentiment is in appraising the comments that users provide or service providers or services. In this work, a solution known as adaptive rider feedback artificial tree optimization-based deep neuro-fuzzy network (RFATO-based DNFN) is implemented for efficient sentiment grade classification. Here, the input is pre-processed by employing the process of stemming and stop word removal. Then, important factors, e.g. SentiWordNet-based features, such as the mean value, variance, as well as kurtosis, spam word-based features, term frequency-inverse document frequency (TF-IDF) features and emoticon-based features, are extracted. In addition, angular similarity and the decision tree model are employed for grouping the reviewed data into specific sets. Next, the deep neuro-fuzzy network (DNFN) classifier is used to classify the sentiment grade. The proposed adaptive rider feedback artificial tree optimization (A-RFATO) approach is utilized for the training of DNFN. The A-RFATO technique is a combination of the feedback artificial tree (FAT) approach and the rider optimization algorithm (ROA) with an adaptive concept. The effectiveness of the proposed A-RFATO-based DNFN model is evaluated based on such metrics as sensitivity, accuracy, specificity, and precision. The sentiment grade classification method developed achieves better sensitivity, accuracy, specificity, and precision rates when compared with existing approaches based on Large Movie Review Dataset, Datafiniti Product Database, and Amazon reviews
Implementation of a Malicious Traffic Filter Using Snort and Wireshark as a Proof of Concept to Enhance Mobile Network Security, Journal of Telecommunications and Information Technology, 2022, nr 1
Full text linkIn the 1970s, roaming interconnections for cellular networks were designed for a few trusted parties. Hence, security was not a major concern. Today, the SS7 (Signaling System no. 7) solution that is several decades old is still used for many roaming interconnections. SS7 has been proven vulnerable to serious threats due to deregulation, expansion, and convergence with IP-based Long Term Evolution (LTE) networks. The limitations of the SS7 network that it is unable to check the subscriber’s authentic location, verify their identity and filter illegitimate messages, makes the system vulnerable to attacks. Adversaries taking advantage of these shortcomings can inflict threats such as interception of calls and text messages, subscriber tracking and denial of service attacks. Although LTE and Diameter signaling protocols promise enhanced security keeping up with the latest attack vectors, their inherent flaws related to roaming interconnections are still there and continue to make the networks vulnerable. Hence, a highly secure signaling network is required to protect the operators and the subscribers from a diverse range of security attacks. SS7 network protocol layers, such as signaling connection control part (SCCP), transaction capabilities application part (TCAP), and global system for mobile Communications – mobile application part (GSM MAP), manage connectivity between networks and subscribers. An analysis of the parameters of these layers may provide a clear insight into any anomalies present. Unfortunately, these parameters are not validated and verified at the network’s edge. The major contribution of this research is a methodology for detecting anomalies by checking malformed parameters and intra-layer parameter discrepancies at the abovementioned protocol layers. This paper provides an insight into the severity of SS7 network security vulnerabilities. Furthermore, it provides a proof of concept for the analysis of SS7 network traffic using the Wireshark packet capture tool and the Snort intrusion detection system (IDS) capable of detecting malicious traffic patterns
Using of Golden Code Orthogonal Super-Symbol in Media-Based Modulation for Single-Input Multiple-Output Schemes, Journal of Telecommunications and Information Technology, 2022, nr 2
Full text linkThe media-based modulation (MBM) scheme is capable of providing high throughput, increasing spectrum efficiency, and enhancing bit error rate (BER) performance of communication systems. In this paper, an MBM employing radio frequency (RF) mirrors and golden code is investigated in a single-input multiple-output (GC-SIMO) application. The aim is to reduce complexity of the system, maximize linear relationships between RF mirrors and improve spectral efficiency of MBM to in order to obtain a high data rate with the use of less hardware. Orthogonal pairs of the super-symbol in the GC scheme’s encoder are employed, transmitted via different RF mirrors at different time slots in order to achieve the full data rate and high diversity. In the results having BER of 10−5 , the GC-SIMO, MBM exhibits better performance than GD-SIMO, with the gain of approximately 7 dB and 6.5 dB SNR for 4 b/s/Hz and 6 b/s/Hz, respectively. The derived theoretical average error probability of the proposed scheme is validated with the use of the Monte Carlo simulatio
Speeding Up Minimum Distance Randomness Tests, Journal of Telecommunications and Information Technology, 2022, nr 2
Full text linkRandomness testing is one of the essential and easiest tools for the evaluation of the features and quality of cryptographic primitives. The faster we can test, the greater volumes of data can be checked and evaluated and, hence, more detailed analyses may be conducted. This paper presents a method that significantly reduces the number of distances calculated in the minimum distance, Bickel-Breiman, and m nearest points tests. By introducing a probabilistic approach with an arbitrarily low probability of failure, the number of calculated distances proportional to the number of required distances and independent of the number of points was achieved. In the well-known Diehard’s minimum distance and 3D spheres tests, the quantity of computations achieved is reduced by the factors of 394 and 771, respectively
Design Low Complexity SCMA Codebook Using Arnold’s Cat Map, Journal of Telecommunications and Information Technology, 2022, nr 4
Full text linkIn 5G wireless communications, sparse code multiple access (SCMA) – a multi-dimensional codebook based on a specific category of the non-orthogonal multiple access (NOMA) technique - enables many users to share non-orthogonal resource components with a low level of detection complexity. The multi-dimensional SCMA (MD-SCMA) codebook design presented in this study is based on the constellation rotation and interleaving method. Initially, a subset of the lattice Z 2 is used to form the mother constellation’s initial dimension. The first dimension is then rotated to produce other dimensions. Additionally, interleaving is employed for even dimensions to enhance fading channel performance. Arnold’s chaotic cat map is proposed as the interleaving method to reduce computational complexity. Performance of the SCMA codebook based on interleaving is evaluated by comparing it with selected codebooks for SCMA multiplexing. The metrics used for performance evaluation purposes include bit error rate (BER), peak to average power ratio (PAPR), and minimum Euclidean distance (MED), as well as complexity. The results demonstrate that the suggested codebook with chaotic interleaving offers performance that is equivalent to that of the conventional codebook based on interleaving. It is characterized by lower MED and higher BER compared to computer-generated and 16-star QAM codebook design approaches, but its complexity is lower than that of the conventional codebook based on interleaving
High-level and Low-level Feature Set for Image Caption Generation with Optimized Convolutional Neural Network, Journal of Telecommunications and Information Technology, 2022, nr 4
Full text linkAutomatic creation of image descriptions, i.e. captioning of images, is an important topic in artificial intelligence (AI) that bridges the gap between computer vision (CV) and natural language processing (NLP). Currently, neural networks are becoming increasingly popular in captioning images and researchers are looking for more efficient models for CV and sequence-sequence systems. This study focuses on a new image caption generation model that is divided into two stages. Initially, low-level features, such as contrast, sharpness, color and their high-level counterparts, such as motion and facial impact score, are extracted. Then, an optimized convolutional neural network (CNN) is harnessed to generate the captions from images. To enhance the accuracy of the process, the weights of CNN are optimally tuned via spider monkey optimization with sine chaotic map evaluation (SMO-SCME). The development of the proposed method is evaluated with a diversity of metrics