Telecom, Volume 4, Issue 4 (December 2023) – 9 articles

Software-defined networking (SDN) is an innovative technology that has the potential to enhance the scalability, flexibility, and security of telecommunications networks. The emergence and development of SDNs have introduced new opportunities and challenges in the telecommunications industry. One of the major challenges encountered by SDNs is the timing side-channel attacks. These attacks exploit timing information to expose sensitive data, including flow tables, routes, controller types, and ports, which pose a significant threat to communication networks. Existing techniques for mitigating timing side-channel attacks primarily focus on limiting them via network architectural changes. This significantly increases the overhead of SDNs and makes it difficult to identify the origin of the attack. To secure resilient integration of SDN in telecommunications networks, it is necessary to conduct comprehensive research that not only identifies the attack activity, but also formulates an adequate response. In this paper, we propose a detection and response solution for timing side-channel attacks in SDN. We used a machine learning-based approach to detect the probing activity and identify the source. To address the identified timing side-channel attack queries, we propose a response mechanism. This entails devising a feedback-oriented response to counter the identified source, such as blocking or diverting it, while minimising any adverse effects on legitimate network traffic. This methodology is characterised by an automated data-driven approach that enables prompt and effective responses. The architecture of this security solution ensures that it has a minimal impact on network traffic and resource usage as it is designed to be used in conjunction with SDN. The overall design findings show that our detection approach is 94% precise in identifying timing side-channel attacks in SDN when compared with traditional mitigation strategies. Additionally, the response mechanism employed by this approach yielded highly customised and precise responses, resulting in an impressive accuracy score of 97.6%. Full article

The exponential growth of the fifth-generation (5G) network gives businesses and universities a chance to turn their attention to the next-generation network. It is widely acknowledged that many IoT devices require more than 5G to send various types of data in real-time. In addition to 5G, several research centres are currently concentrating on 6G, which is expected to produce networks with great quality of service (QoS) and energy efficiency. Future application requirements will necessitate a significant upgrade in mobile network architecture. 6G technologies offer larger networks with lower latency and faster data transmission than 5G networks. This review presents a comprehensive overview of 6G networks which includes the novel architectural changes within 6G networks, recent research insights from diverse institutions, applications within the realm of 6G networks, and the key features associated with them. We also explored various technologies of 6G networks encompassing terahertz, visible light connectivity, blockchain, and symbiotic broadcasting, all of which contribute to the establishment of robust and socially integrated network structures. In this survey, we have focused on 6G network slices and discussed a detailed exploration of security and privacy concerns regarding the potential 6G technologies at the levels of physical infrastructure, connecting protocols, and service provisions, alongside an evaluation of current security strategies. Full article

The application of drones, also known as unmanned aerial vehicles deployed as unmanned aerial base stations (UABSs), has received extensive interest for public safety communications (PSC) to fill the coverage gaps and establish ubiquitous connectivity. In this article, we design a PSC LTE-Advanced air–ground-based HetNet (AG-HetNet) that is a scenario representation of a geographical area during and after a disaster. As part of the AG-HetNet infrastructure, we have UABSs and ground user equipment (GUE) flocking together in clusters at safe places or evacuation shelters. AG-HetNet uses cell range expansion (CRE), intercell interference coordination (ICIC), and 3D beamforming techniques to ensure ubiquitous connectivity. Through system-level simulations and using a brute-force technique, we evaluate the performance of the AG-HetNet in terms of fifth-percentile spectral efficiency (5pSE) and coverage probability. We compare system-wide 5pSE and coverage probability when UABSs are deployed on a hexagonal grid and for different clustering distributions of GUEs. The results show that reduced power subframes (FeICIC) defined in 3GPP Release-11 can provide practical gains in 5pSE and coverage probability than the 3GPP Release-10 with almost blank subframes (eICIC). Full article

Humankind has entered a new era wherein a main characteristic is the convergence of various technologies providing services and exerting a major impact upon all aspects of human activity, be it social interactions with the natural environment. Fixed networks are about to play a major role in this convergence, since they form, along with mobile networks, the backbone that provides access to a broad gamut of services, accessible from any point of the globe. It is for this reason that we introduce a forward-looking approach for fixed networks, particularly focused on Fixed 6th Generation (F6G) networks. First, we adopt a novel classification scheme for the main F6G services, comprising six categories. This classification is based on the key service requirements, namely latency, capacity, and connectivity. F6G networks differ from those of previous generations (F1G–F5G) in that they concurrently support multiple key requirements. We then propose concrete steps towards transforming the main elements of fixed networks, such as optical transceivers, optical switches, etc., such that they satisfy the new F6G service requirements. Our study categorizes the main networking paradigm of optical switching into two categories, namely ultra-fast and ultra-high capacity switching, tailored to different service categories. With regard to the transceiver physical layer, we propose (a) the use of all-optical processing to mitigate performance barriers of analog-to-digital and digital-to-analog converters (ADC/DAC) and (b) the exploitation of optical multi-band transmission, space division-multiplexing, and the adoption of more efficient modulation formats. Full article

Malware in today’s business world has become a powerful tool used by cyber attackers. It has become more advanced, spreading quickly and causing significant harm. Modern malware is particularly dangerous because it can go undetected, making it difficult to investigate and stop in real time. For businesses, it is vital to ensure that the computer systems are free from malware. To effectively address this problem, the most responsive solution is to operate in real time at the system’s edge. Although machine learning and deep learning have given promising performance for malware detection, the significant challenge is the required processing power and resources for implementation at the system’s edge. Therefore, it is important to prioritize a lightweight approach at the system’s edge. Equally important, the robustness of the model against the concept drift at the system’s edge is crucial to detecting the evolved zero-day malware attacks. Application programming interface (API) calls emerge as the most promising candidate to provide such a solution. However, it is quite challenging to create API call features to achieve a lightweight implementation, high malware detection rate, robustness, and fast execution. This study seeks to investigate and analyze the reuse rate of API calls in both malware and goodware, shedding light on the limitations of API call dictionaries for each class using different datasets. By leveraging these dictionaries, a statistical classifier (STC) is introduced to detect malware samples. Furthermore, the study delves into the investigation of model drift in the STC model, employing entirely distinct datasets for training and testing purposes. The results show the outstanding performance of the STC model in accurately detecting malware, achieving a recall value of one, and exhibiting robustness against model drift. Furthermore, the proposed STC model shows comparable performance to deep learning algorithms, which makes it a strong competitor for performing real-time inference on edge devices. Full article

We have studied the interference caused by amplitude and phase distortions induced by rain in ultra-wideband communication systems designed for using amplitude modulation in GeoSurf future satellite constellations. The results concern radio links simulated with the synthetic storm technique at Spino d’Adda (Italy), Madrid (Spain) and Tampa (Florida), which are sites located in different climatic regions. The conclusions are (a) the three sites, although in different climatic zones, are practically indistinguishable; (b) the channel signal-to-noise ratio can be increased or decreased by interference with equal probability. Channel theoretical capacity loss, even in the worst case, is very limited and rain, therefore, does not cause significant linear distortions in ultra-wideband channels at millimeter waves; therefore, these channels could be used at millimeter waves. Full article

In the realm of military communications, the advent of new technologies like 5G and the future 6G networks holds promise. However, incorporating these technologies into tactical environments presents unique security challenges. This article delves into an analysis of these challenges by examining practical use cases for military communications, where emerging technologies can be applied. Our focus lies on identifying and presenting a range of emerging technologies associated with 5G and 6G, including the Internet of things (IoT), tactile internet, network virtualization and softwarization, artificial intelligence, network slicing, digital twins, neuromorphic processors, joint sensing and communications, and blockchain. We specifically explore their applicability in tactical environments by proposing where they can be potential use cases. Additionally, we provide an overview of legacy tactical radios so that they can be researched to address the challenges posed by these technologies. Full article

This article describes the process of implementing a transportable radar MSSR-S for Peruvian civil aviation (ACP) to minimize the operational impact in emergencies that affects air traffic without causing structural damage and restore data from the radar in a short time. In recent years, ACP has shown constant falls in the radars, causing radar data to be lost for long periods of time and putting air safety at risk due to the lack of maintenance and overlapping radar coverage of more than three radars. The deployment of the transportable radar in Mode S of Monopulse Secondary Surveillance (MSSR-S) has allowed for work that involves the prolonged stoppage of the radar to be carried out and provided coverage to eight more radars during maintenance and modernization, covering the areas without coverage in the Peruvian air space (EAP). For the implementation, this was divided into three SPRINTs using the SCRUM methodology; the first sprint refers to the equipment and radar coverage study, the second the implementation and service test phase, and the third the operational analysis phase with the eight modernized radars. As a result of the implementation and integration with the other ACP radar systems, they were able to operate together, providing highly reliable radar data, performing a continuous analysis of radar performance through the PASS software, complying with the thresholds established by ICAO and EuroControl, and guaranteeing that the systems operate under perfect conditions and with full coverage at all time. Full article

In recent decades, wireless sensor networks (WSNs) have become a popular ambient sensing and model-based solution for various applications. WSNs are now achievable due to the developments of micro electro mechanical and semiconductors logic circuits with rising computational power and wireless communication technology. The most difficult issues concerning WSNs are related to their energy consumption. Since communication typically requires a significant amount of energy, there are some techniques/ways to reduce energy consumption during the operation of the sensor’s communication systems. The topology control technique is one such effective method for reducing WSNs’ energy usage. A cluster head (CH) is usually selected using a topology control technique known as clustering to control the entire network. A single factor is inadequate for CH selection. Additionally, with the traditional clustering method, each round exhibits a new batch of head nodes. As a result, when using conventional techniques, nodes decay faster and require more energy. Furthermore, the inceptive energy of nodes, the range between sensor nodes and base stations, the size of data packets, voltage and transmission energy measurements, and other factors linked to sensor nodes are also completely unexpected due to irregular or hazardous natural circumstances. Here, unpredictability represented by Triangular Fuzzy Numbers (TFNs). The associated parameters of nodes were converted into crisp ones via the defuzzification of fuzzy numbers. The fuzzy number has been defuzzified using the well-known signed distance approach. Here, we have employed a multi-criteria decision-making (MCDM) approach to choosing the CHs depending on a bunch of characteristics of each node (i) residual energy, (ii) the number of neighbors, (iii) distance from the sink, (iv) average distance of cluster node, (v) distance ratio, and (vi) reliability. This study used the entropy-weighted Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) approach to select the CH in WSNs. For experiments, we have used the NSG2.1 simulator, and based on six characteristics comprising residual energy, number of neighbor nodes, distance from the sink or base station (BS), average distance of cluster nodes, distance ratio, and reliability, optimal CHs have been selected. Finally, experimental results have been presented and compared graphically with the existing literature. A statistical hypothesis test has also been conducted to verify the results that have been provided. Full article