Conference Publications

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A compact, array-ready dual-polarized stacked patch element for C-band UAV SAR
(2026-05) Mafa, Ike M; Winberg, S; Ferreira, Riaan
This paper presents a compact dual-polarized stacked microstrip patch antenna designed for C-band spaceborne and UAV-mounted Synthetic Aperture Radar (SAR) systems operating in the ITU-allocated 5.25–5.57 GHz band (320 MHz). The antenna employs a novel coupling-excited feed architecture in which two orthogonal coaxial probes excite inverted U-shaped slots etched into a driven patch, enabling strong coupling and improved impedance shaping. A parasitic patch—scaled 5% smaller than the driven patch and incorporating matching rounded corners—is placed above the radiator to form a vertically coupled two-resonator system that broadens the impedance bandwidth while preserving planar symmetry suitable for array integration. Electromagnetic simulations performed in Altair FEKO demonstrate a −8 dB impedance bandwidth of 5.32–5.78 GHz (≈480 MHz), fully covering the 320 MHz SAR allocation. The antenna maintains inter-port isolation better than −17 dB across the band, with a peak isolation of −24.3 dB at 5.55 GHz; such isolation levels significantly reduce crosstalk in dual-polarized SAR channels, improving polarimetric accuracy without requiring external decoupling networks. The realized gain remains stable between 3–5.3 dBi, and cross-polarization levels stay below −18 dB in the main beam region. These results confirm that the proposed architecture offers a compact, low-profile, and wideband dualpolarized radiator well suited for next-generation space-borne and UAV SAR front ends.
A comparison of various machine learning algorithms on ISAR image classification of complex targets with varying levels of Gaussian noise
(2025-08) Stewart-Burger, CD; Ludick, DJ; Potgieter, Monique
This paper investigates the ability to classify complex targets using inverse synthetic aperture radar (ISAR) images with varying noise levels. ISAR is an imaging technique used to generate high resolution two-dimensional images of radar targets. ISAR images contain more information about targets than one-dimensional data, such as high- resolution range (HRR) profiles. ISAR images therefore have useful applications in target classification.
A comprehensive analysis of identity theft: Definitions, types, and impacts
(2026-05) Ntshangase, Cynthia S; Steyn, AS
Identity theft is a complex and evolving phenomenon spanning physical, digital, algorithmic, and hybrid domains. This paper presents a systematic literature review following PRISMA guidelines to consolidate definitions, identify major and emerging subtypes, and assess impacts on individuals, organisations, and society. The study proposes a comprehensive definition that unifies fragmented and subtype‑specific descriptions in the literature and explicitly encompasses document‑based, child, offline, familial, criminal, synthetic, biometric, and algorithmic identity theft. We clarify that our bibliometric analysis reflects research attention rather than real‑world incidence and explain the practical implications of this distinction. To enhance applied value, we discuss Africa‑specific identity‑management challenges, including persistent identity document fraud, and the rise of synthetic identities, and outline how the taxonomy supports national ID authorities, policy makers, financial institutions, and fraud‑prevention bodies in South Africa and across the continent. Benefits include improved incident‑response categorisation, more comprehensive compliance checklists, enhanced risk assessments, and clearer cross‑sector communication. The review highlights a research focus bias toward financial theft and calls for further empirical work on underexplored subtypes (e.g., familial, child, algorithmic, deceased). We conclude with future research that triangulates bibliometric signals with incident statistics and operational data to inform resilient identity‑management frameworks.
A comprehensive exploration of digital forensics investigations in embedded systems, ubiquitous computing, fog computing, and edge computing
(2024-08) Nelufule, Nthatheni; Singano, Zothile T; Masango, Mfundo G
The rapid evolution of digital ecosystems, characterized by the intricate interplay of diverse technologies, has necessitated a shift in the digital forensics’ paradigm. Traditional investigative methods are inadequate to perform digital forensic exercises in the new paradigm of dynamic digital ecosystem landscapes. The emergence of complex digital ecosystems encompassing an array of interconnected devices and data repositories poses formidable challenges for conventional digital forensics. There is a dire need to adapt and advance digital forensic methodologies to effectively combat cybercrime because the evolving landscape of digital ecosystems presents a critical juncture for the field of digital forensics. This study proposes a systematic literature review to understand the extent of these challenges and proposes a collaborative and innovative approach to digital forensic investigation within the context of digital ecosystems. The proposed approach emphasizes collaboration across diverse sectors and integration of innovative technologies by combining a spectrum of digital forensic experts, technologists, and legal professionals to produce a massive wealth of collective intelligence.
A computational model for analysis of the dynamic response of a quarter-vehicle suspension system
(2026-09) Sikhakhane, Phakamani L; Joni, Emmanuel L; Mokgotho, Lebone Y; Modungwa, Dithoto M
Off road vehicle suspension performance directly affects ride behaviour, structural loading, and vehicle control under irregular terrain excitation. This paper presents a cross-platform computational framework for analyzing the vertical dynamic response of a quarter-vehicle suspension system using three modeling approaches: a reduced-order MATLAB model and multibody models in Project Chrono and MSC ADAMS. A common suspension definition and terrain input were used to compare sprung mass displacement, unsprung mass displacement, suspension travel, and sprung mass acceleration. MATLAB and Project Chrono show the closest agreement. while MSC ADAMS predicts a smoother, more damped response. The framework provides a practical basis for comparing modelling fidelity in quarter vehicle suspension analysis under off-road excitation.
A decentralized cyber threat information (CTI) sharing platform
(2024-08) Singano, Zothile T; Mthethwa, Sthembile N; Ntshangase, Cynthia S
Embracing the changes in technology and cybersecurity is crucial especially for organisations. As the technology space evolves so does the techniques used by cyber attackers, it gets more sophisticated. For organisations to secure their environment, it is vital to collaborate with other organisations to fight against zero-day-attacks. This can be achieved through sharing cyber threat information. Most organisations are hesitant to share CTI because of trust. Therefore, this paper presents a DLT based CTI sharing platform, which presents a trust-less environment for sharing. The nature of DLT presents opportunities for sharing CTI in a secure and decentralized manner, thus allowing global collaboration.
A hybrid, transparent trust and risk assessment framework for cryptocurrency exchanges
(2026-06) Mawhayi, B; Botha, Johannes G; Leenen, L
Cryptocurrency exchanges act as critical intermediaries within the digital asset ecosystem, yet users currently rely on largely opaque, platform-defined trust scores to assess their reliability and risk. Existing industry frameworks, notably those produced by CoinGecko and CoinMarketCap, provide useful signals related to liquidity and volume integrity but suffer from limited transparency, fixed weighting schemes, and the absence of sentiment-based assessment. This paper presents HTREx (Hybrid Trust and Risk Evaluation framework for exchanges), a semi-automated, modular trust and risk assessment framework for cryptocurrency exchanges that addresses these limitations. The framework integrates five dimensions of exchange integrity: user sentiment, regulatory compliance, technical security, transparency, and incident history. Sentiment is quantified using transformer-based natural language processing applied to user-generated content from mobile application reviews and online forums. Compliance is assessed through structured extraction of regulatory and operational disclosures from Terms of Service documents using large language models. Security, transparency, and incident history are evaluated through a combination of publicly verifiable indicators, third-party assessments, and a recency-weighted incident scoring model. All components are normalised and aggregated into a composite score using user-adjustable weights, enabling personalised risk prioritisation while retaining a defensible default configuration for comparative analysis. The framework is demonstrated using four prominent exchanges—Kraken, Coinbase, Binance, and Uniswap—highlighting clear differences between centralised and decentralised platforms and illustrating how sentiment, compliance, and historical incidents materially influence overall trust assessments. The results suggest that transparent, extensible, and user-configurable scoring models can provide a more interpretable and context-sensitive evaluation of exchange risk than existing monolithic trust scores, with direct relevance for both retail and institutional participants.
A mathematical model of a commercial fuel cell for evaluating efficiency under varying ambient conditions
(2025-09) Ndebele, Bright B; Naidoo, Purusha; Ragimana, Phumudzo; Makhubo, Mamokete
Long-endurance aviation propulsion is currently dominated by carbon-based fuels. However, due to climate change, which is largely attributed to carbon dioxide (CO2) emissions from human activities, aviation contributes approximately 4 %, a more climate friendly fuel is sought. Hydrogen (H2), particularly in proton exchange membrane (PEM) fuel cells, offers a promising carbon-neutral alternative. To assess its viability, a mathematical model of a commercial fuel cell was developed to evaluate efficiency under varying ambient conditions representative of Africa climates and at high-altitude scenarios. The Nernst equation – modified to include terms for activation, polarisation, and Ohmic losses – was used to model an experimentally determined polarisation curve (current against cell voltage curve). When fit to experimental data the modified Nernst equation parameters were found to be: A = 0.0356 V, I0 = 0.0212 Amperes, Rint = 0.0059 Ohms, and Imax = 150 Amperes where A, I0, Rint and Imax are the Tafel slope, limit current, internal resistance, and maximum limit current, respectively. The influence of pressure and temperature were determined by varying the partial pressure of oxygen and temperature in the Nernst equation resulting in an efficiency map (𝜂(𝑃𝑂2,𝑇)). The maps showed that efficiency is high for high ambient pressure and low ambient temperature. However, the influence of ambient pressure and temperature were found to be insignificant compared to the influence of power drawn.
A perspective on the integration of ABB industrial robots into Open AI Gym using vision-based reinforcement learning
(2024-12) Dikole, Realeboga G; Faniso-Mnyaka, Zimbini; Sekopa, Teboho L
Reinforcement learning-based robotic manipulation has risen to prominence recently due to the rise of frameworks such as Open AI Gym. Although there has been much success in reinforcement learning applied to manipulators such as the Kuka iiwa, Franka Emika Panda, UR5 robots, there has been little to no exploration of the application of reinforcement learning on ABB robotic manipulators. This paper presents a perspective on integrating vision-based reinforcement learning and ABB robots with Open AI Gym environments. We focus mainly on the pick-and-place and push environments using proximal policy optimisation due to its simplicity and ease of memory. Our results affirm the possibility of vision-based reinforcement learning with ABBrobots with the best training performance yielding a success rate of close to sixty-five percent.
A qualitative review of zero-knowledge proofs and biometrics in decentralized identity systems
(2025) Baruni, Kedimotse P; Ntshangase, Cynthia S; Ngobeni, Harvest T; Moatshe, Lesego S; Ndhlovu, Nomalisa
This paper presents a qualitative review of the integration of Zero Knowledge Proofs (ZKPs) and biometrics in Decentralized Identity (DID) sys tems. It explores how these technologies address key challenges in digital identity management, including privacy preservation, security enhancement, and regula tory compliance. Using three research questions, the study systematically reviews the recent literature to identify the problems these technologies solve, the sectors where they are applied, and the standards that govern their implementation. The review further reveals that ZKPs-DID is the most widely adopted method, dom inating finance and governance applications, while Bio-DID focuses on healthcare and education under GDPR, and BioZK-DID combines biometrics with ZKPs for enhanced security but with limited regulatory guidance. The find ings reveal that ZKPs enable privacy-preserving verification, while biometrics offer robust user-specific authentication. Integration within DID systems is par ticularly relevant in sectors such as finance, healthcare, governance, and educa tion. However, challenges remain in scalability, interoperability, and regulatory alignment. This paper contributes new insights by proposing technical guidelines, policy recommendations, and future research directions to support the ethical and effective deployment of ZKP-biometric-enabled DID systems.
A review of injury risk curve development to support human factors and ergonomic design under extreme loading conditions
(2026-02) Mokgotho, Lebone Y; Sekhuthe, Karabelo L; Modungwa, Dithoto M
Conducting risk assessments in underbody blast (UBB) scenarios on landmine-protected vehicles is important for evaluating vehicle safety, crew injury risk, and the effectiveness of blast protection systems. Due to the hazardous, costly, and resource-constrained nature of UBB testing, injury risk assessment commonly relies on survival analysis methods to estimate injury probabilities from limited and censored experimental data. This paper presents a structured review of survival analysis methods used to develop lower-limb injury risk criteria under UBB loading conditions. Parametric, non-parametric, and semi-parametric survival models are reviewed and compared with respect to their assumptions, data requirements, and suitability for constrained experimental environments. Emphasis is placed on their application to injury risk curve development for lower extremity injuries. The review highlights methodological strengths, limitations, and practical implications of model selection for engineering decision-making, including risk threshold definition, test evaluation, and validation of protective systems. A limited illustrative dataset is used to demonstrate the application of selected methods. The findings support more consistent and transparent use of survival analysis techniques in injury risk assessment for extreme loading scenarios.
A review of PFCP cyber attacks in 5G standalone for robotic telesurgery services
(2024-10) Makondo, Ntshuxeko; Baloyi, Errol; Kobo, Hlabishi I; Mathonsi, TE
The emergence of fifth-generation technology (5G) has revolutionised telecommunication networks, offering enhanced mobile broadband, ultra-reliable (eMBB), ultra-lowlatency communications (uRLLC), and massive machine-type communication (mMTC) service classes. This breakthrough has garnered significant attention and investment worldwide, driving innovation and growth in the digital era. However, the adoption of cloud-based 5G core (5GC) networks, while offering scalability and deployment flexibility, has posed challenges to meeting stringent latency requirements, particularly for uRLLC services specifically for robotic telesurgery. To address this problem, mobile network operators (MNOs) have turned to edge computing (EC), using the control and user plane separation (CUPS) architecture introduced in the thirdgeneration partnership project (3GPP) release 14 specification. This architecture enables the deployment of the user plane function (UPF) closer to users, reducing latency, and improving quality of service (QoS). However, the deployment of the UPF as a standalone node on the edge of the network exposes the packet forwarding control protocol (PFCP) to cybersecurity attacks, which pose risks to telesurgery services and could even lead to loss of life. In the existing literature, only a few techniques focus on minimising these attacks when the UPF is deployed on the edge of the network far from the 5GC. Therefore, this paper reviews PFCP attacks and explores machine learning (ML) techniques to mitigate these security threats. This paper further provides recommendations and future research directions for mitigating these attacks.
A review of the South African public sector’s capability in combating ransomware
(2024-09) Siphambili, Nokuthaba; Mahlasela, Oyeana N; Baloyi, Errol; Mukondeleli, Elekanyani
Ransomware attacks have emerged as a significant cybersecurity threat, impacting organisations globally, including the South African public sector. This study conducted a narrative review aimed at investigating the South African public sector's capability to address ransomware attacks. The review examined news articles, reports, and literature from databases such as Scopus, Google Scholar, and ScienceDirect. Furthermore, this review explored the evolving landscape of ransomware, including its modus operandi and impacts. The findings revealed that since 2019, ten different South African public sector entities have been targeted by ransomware, with one entity being hit twice. Based of those findings, this study provided recommendations to strengthen the South African public sector's national defences and improve its preparedness for future ransomware attacks.
A strategic path for digital transformation in cyber warfare for African  militaries
(2024-03) Mphahlela, James M; Mtsweni, Jabu S
Digital disruption has changed the battlefield and increased its complexity for the war fighter. The modern battlefield continues to increase this complexity, due to the evolution of components that constitute military capability. The technologies, processes and the users are such components. The modern battlefield relies on advanced technologies tapping on high connectivity, are more lethal, precise, and autonomous. Due to this evolution, areas once thought to be safe from conventional attacks are increasingly becoming vulnerable. This evolution of technology and shorter development curves have also increased the prominence of the cyberspace, as a domain of war. However, many militaries, especially in Africa are still operating legacy systems and struggling with modernizing their systems to take advantage of the digital evolution. This paper, therefore, uses a systematic literature review and benchmarking focusing on selected super cyber power nations’ indices to propose a strategic path for African militaries to drive digital transformation in their operational environments. The roadmap is proposed to stimulate the establishment and enhancement of African militaries’ cyber warfighting capabilities in the digital age. The objectives of this digital transformation path include establishing a digital backbone, where all the sensors, effectors and the deciders are plugged to share information and intelligence.
A Study on bistatic RCS simulations, measurements and calibration
(2018) Potgieter, Monique
Bistatic RCS improves detection, characterisation and identification and enhances target information. Its stealthy targets have a low monostatic return and shaping of larger bistatic scattering.
A survey of digital forensic tools for Android and iOS smart phones
(2024-09) Ntshangase, Cynthia S; Nelufule, Nthatheni; Mulihase, Nkgomeleng D; Mtshali, Mamello L; Mokoena, Chantel JM; Moloi, Palesa MM
Mobile theft has been an increasing problem in South African cities and townships. This is also motivated by the black market for cellphone sales, but it has recently emerged that in many instances, the phone is stolen to harvest the credential and defraud and clean the victims’ bank account. Such cases are hardly reported as the success rate of prosecution is low. This is due to the lack of capacity, investigative tools, and the financial constraints of the investigative authorities. This paper presents a review of modern mobile forensic investigative tools, both open-source and commercialized. The purpose of this survey article is to present an analysis of tools in terms of their strengths and weaknesses and to simplify the work of investigators by bringing all the latest tools into one article.
A survey on the application of blockchain technology for cyber-physical systems
(2024) Nelufule, Norman; Senamela, Pertunia M; Shadung, Lesiba D; Singano, Zothile T; Masemola, Kelebogile B; Mangole, Tshegofatso C
This paper presents a systematic review of the literature on the application of blockchain technology to improve the security of cyber-physical systems. The objective of the article was to identify current challenges, evaluate existing solutions, and propose future research directions. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework was used to ensure that the result of this comprehensive review is not biased. The results and key findings have highlighted that there is a potential usage of the blockchain technology to address security challenges in a cyber-physical systems, including data integrity, authentication, and secure communication. This survey paper concludes by presenting the recommendations for integrating blockchain technology into CPSs to enhance their security and resilience.
A trust framework for peer-to-peer energy markets
(2025) Leotlela, Boitumelo; Ledwaba, L; Coetzee, M
Peer-to-peer energy markets rely on trust to enable secure participation; however existing trust models often address only isolated trust concerns. This fragmented approach leaves significant gaps in ensuring holistic trust across the peer-to-peer energy market and exposes participants to threats in the market. To address this, the paper proposes a trust framework grounded in the Trust over IP (ToIP) model, which integrates technical mechanisms and governance policies to sustain trust in decentralised environments. Using the STRIDE threat model, key threats in the peer-to-peer energy market are identified, while also analysing how existing research mitigates these risks. The corresponding trust and security mechanisms are then mapped to the ToIP architecture, offering a comprehensive approach to trust establishment, that unifies social-behavioural and security dimensions of trust. By leveraging ToIP as a formal foundation for trust establishment in this work, the proposed framework provides a holistic approach to building and maintaining trust in the market, thereby fostering greater user confidence and encouraging broader market participation.
A unified framework for secure and interoperable digital identity in South Africa
(2026-05) Mthethwa, Sthembile N; Ntshangase, Cynthia S; Myaka, Zanele S; Ndhlovu, Nomalisa; Lefophane, Samuel
Digital identity represents a technological advancement facilitating the secure access and management of identities for both individuals and organisations within digital environments. Despite considerable progress in digital identity systems over the past decade, their implementation has been hindered by challenges, including fragmentation, lack of interoperability, and inadequate governance framework. This study analyses global digital identity frameworks to identify best practices and opportunities for accelerating adoption, focusing on key principles such as privacy protection, trust, inclusivity, and cross-border interoperability. Additionally, it outlines the essential requirements for a well-governed digital identity ecosystem and proposes a national digital identity framework consistent with international standards, aimed at enhancing the security, resilience, and global recognition digital identities issued in South African.
A web scraping approach towards cryptocurrency investigations
(2025-06) Mawhayi, B; Botha, Johannes G; Leenen, L
The investigation of cryptocurrency crimes is still in its infancy with no standardised process or methodology to follow. This paper describes research that forms part of a broader project led by the second author (Botha, et al., 2025). The broader project’s aim is to develop a methodology to follow when conducting cryptocurrency crime investigations. One of the steps in the proposed methodology is web scraping. The authors of this paper present a detailed exploration of web scraping techniques within the broader context of the proposed investigation methodology. In this paper, the focus is on developing a well-structured methodology for scraping social media platforms and online forums to gather data related to fraudulent activities; the goal is to find posts that include references to the wallet address of interest. This exploration uses an iterative approach; for every new cryptocurrency wallet address discovered or revealed through on-chain analysis, a parallel path is followed by scraping the Internet. If a mention of the cryptocurrency address should be discovered it is considered to be a key finding, creating a pivot point in the investigation. From a pivot point, further open-source intelligence (OSINT) techniques will be applied, though this aspect falls beyond the scope of this paper. If no relevant information or link is found, the scraping path will not be pursued, and the investigation proceeds with on-chain analysis to identify additional wallet addresses. Additionally, challenges encountered in web scraping, such as handling platform restrictions, ensuring data accuracy, and managing large volumes of data, are addressed. The goal of the proposed methodology is to enhance data extraction and analysis efficiency contributing to the proposed methodology for investigating cryptocurrency scams.

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