USIM AUDIO JOURNAL

The rise of quantum computing presents a critical threat to classical public-key cryptographic systems, necessitating a global shift toward post-quantum cryptography (PQC). While algorithmic standardisation has seen substantial progress since the National Institute of Standards and Technology (NIST) initiated its call for PQC proposals in 2017, the integration of these algorithms into certificate-based infrastructures remains fragmented and underexplored. This gap creates uncertainty for secure communication, particularly in transitioning legacy systems into quantum-resilient environments. This systematic literature review (SLR) focuses on PQC certificate architectures studied between 2017 and 2025, encompassing the evolution of the field since NIST's formal standardisation efforts began. The review employs the PRISMA 2020 methodology to identify and analyse six distinct post-quantum certificate models: Pure PQC, Hybrid, Composite, Chameleon, Parallel, and Wrapped. Each model is evaluated across several criteria, including structure, backwards compatibility, tooling support, standardisation status, and production readiness, drawing evidence from scholarly publications, draft standards, and open-source implementations. Findings highlight the Hybrid certificate as the most viable short-term solution due to its high interoperability and maturity in deployment. Composite and Parallel architectures offer enhanced security assurances that are suitable for critical infrastructure, although they come with increased implementation complexity. Pure PQC certificates, while future-proof, are still limited to constrained or greenfield environments. Chameleon and Wrapped models are identified as emerging alternatives for blockchain and legacy scenarios, respectively, with limited but growing support. This review enlightens the design and deployment of quantum-safe public key infrastructures by outlining the trade-offs and maturity levels of each architecture. It also emphasises the need for continued development in standardisation and toolchain support to facilitate scalable and secure PQC adoption.

Security Operations Centres (SOCs) form the operational core of cyber defence strategies across the world. They are tasked with ensuring continuous monitoring, triage, detection, and response to ever-evolving threats. However, conventional performance metrics used to evaluate SOC efficacy—such as Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), and false positive rates—primarily assess system throughput while overlooking the psychosocial realities of the human analysts who underpin these metrics. This paper presents the findings of a quantitative workforce study conducted among 175 Malaysian SOC professionals across internal, hybrid, and managed security service provider (MSSP) environments. Using a Likert-based adaptation of the NIOSH Worker Well-Being Questionnaire (WellBQ), the study investigates stress, burnout, alert fatigue, task autonomy, psychological safety, tooling efficacy, and career development perceptions. Findings reveal that 73.1% of respondents experience emotional tiredness at least “Sometimes,” while 78.9% agree that more automation would improve their well-being. Notably, 68.0% reported having opportunities to grow and develop their careers within their SOC environments. These insights highlight the need for a paradigm shift in SOC performance measurement—one that integrates human-centric indicators alongside traditional technical KPIs. The paper concludes with empirically grounded recommendations for embedding well-being frameworks into operational security management to ensure sustainable, high-performing cybersecurity teams.

Audio steganography hides secret messages inside audio files, enabling covert communication without drawing attention. Audio steganography methods aim to achieve high imperceptibility, robust performance, and high payload capacity. While traditional techniques like Least Significant Bit (LSB) coding offer good imperceptibility, they are highly vulnerable to statistical steganalysis and signal manipulation. Existing hybrid methods suffer from maintaining quality across diverse audio and inadequate robustness mechanisms, struggling to balance imperceptibility, payload capacity, and robustness. This paper proposes a novel hybrid approach that combines Conditional Generative Adversarial Networks (CGANs) with LSB coding to address these limitations. The CGAN is trained with the LibriSpeech dataset to generate audio patterns that simulate spontaneous speech for use as adaptive covers. The model was implemented using PyTorch, with performance evaluated based on Signal-to-Noise Ratio (SNR), Perceptual Evaluation of Speech Quality (PESQ), Bit Error Rate (BER), and robustness to audio transformations. Experimental results showed a PESQ value of 4.05 and a mean SNR of 33.1 dB, representing excellent audio quality given the substantial payload capacity of 1.27 kbps. The method achieved a BER value of 2.23% and 87% robustness to compression, filtering, and resampling operations. The effectiveness of the CGAN-LSB hybrid method for enhancing capacity, imperceptibility, and robustness is achieved through the CGAN's ability to generate statistically natural audio covers, while adaptive LSB integration preserves data integrity during signal processing operations, making it highly suitable for secure audio communication and audio watermarking applications. While the generated covers exhibit distributional properties similar to genuine audio, direct validation against specific steganalysis detectors remains an important direction for future empirical evaluation.

Maple syrup urine disease (MSUD) is an autosomal recessive genetic disease and an inherited autosomal recessive trait. It is characterised by a deficiency of an enzyme complex, resulting in an excess of branched-chain amino acids (BCAAs), which are toxic to the nervous system. Our four cases generally presented with lethargy and poor feeding weeks after birth. They were all treated for sepsis until the laboratory results showed high levels of BCAAs, which indicated MSUD. Genetic analysis showed that the four cases were homozygous for the DBT gene mutation c.1196C>G (p.S399C), a possible founder mutation. All of our cases were managed accordingly, with regular monitoring of the BCAA levels. Dietary support, with infant formulas free of BCAAs, was provided to all four cases with regular follow-up at the paediatric genetic clinic. All cases had spastic diplegic and developmental delays

Pyogenic granuloma (PG) is a rapidly growing benign lesion of the skin and mucous membrane. Its etiology is still unclear. It is suggested to have arisen either due to trauma or hormonal influences. Pyogenic granuloma is regularly found in the oral cavity. Even though it is rare, it does occur in the nasal cavity and a few cases of pyogenic granuloma have been reported among the paediatric population. We present a case of a 6-year-old boy, who presented with unilateral nasal blockage and recurrent epistaxis. The child has a history of allergic rhinitis and frequent nasal picking. Clinical examination revealed a small broad based reddish mass at the anterior part of the right inferior turbinate. The histopathological examination from complete excisional biopsy was consistent with pyogenic granuloma. Although pyogenic granuloma is relatively rare, we should raise suspicion in young patients who complain of progressive unilateral nasal blockage and recurrent epistaxis, with or without a history of trauma. Thorough clinical examination is adequate in small lesion thus sparing the need for radiological investigation for bigger and extensive lesions. Complete excision is the ultimate treatment to avoid recurrence.

Blockchain technology has emerged as a transformative tool in higher education, offering secure, transparent, and tamper-proof systems for credential verification, academic record management, and institutional data governance. Despite its potential, adoption remains limited due to technical, financial, and organizational barriers, alongside a lack of validated measurement tools to assess readiness and integration. This pilot study aims to validate an instrument grounded in the Knowledge Integration Model of Blockchain Technology for Higher Learning Institutions using the Rasch Measurement Model. A 50 item survey was administered to 31 purposively sampled stakeholders, including academics, researchers, and postgraduate students with blockchain related experience. Data analysis using WINSTEPS 3.92.1 assessed reliability, item-person fit, unidimensionality, and targeting through Wright Map analysis. The results showed satisfactory reliability (person = 0.82; item = 0.77). Four items (B5, B6, D8, C7) exceeded the acceptable outfit MNSQ threshold (>1.5) and were revised to enhance instrument quality. However, several items showed misfit and require refinement, and the Wright Map indicated a need for more challenging items to better target high ability respondents. Unidimensionality testing revealed a dominant construct with minor secondary dimensions, suggesting further refinement for conceptual clarity. These findings provide preliminary evidence the instrument’s potential for large scale application, providing a foundation for assessing blockchain knowledge integration and guiding policy and strategic implementation in higher education.

The 2023 Malaysian Budget increased the maximum compensable unused leave for public employees from 160 to 180 days, significantly raising future liabilities for public sector employers. Under the Malaysian Private Entities Reporting Standard (MPERS), universities must recognise these benefits, which are payable upon retirement or death, as actuarial liabilities. Existing tools, such as the Jabatan Perkhidmatan Awam (JPA) calculator, offer limited accuracy as they do not account for mortality risk or interest rate fluctuations. This study introduces an enhanced actuarial reserve model that incorporates both uncertainties. The model considers two payment casesw which are upon retirement and upon death, using survival probabilities, interest discounting, and assurance factors to determine the expected present value of future cash awards. To evaluate model performance, a simulation study using a non-parametric bootstrap is conducted on 5,000 simulated employee records. Bootstrap resampling is repeated at increasing levels to measure bias and consistency. Results show that both bias and variance decrease as bootstrap iterations increase, indicating model stability and accuracy. This improved model offers a more realistic and reliable method for estimating future cash awards, ensuring better financial planning, policy compliance, and reserve adequacy for higher education institutions.

Recent years have witnessed a rise in the frequency and intensity of natural disasters, disproportionately affecting vulnerable communities, as reported by the United Nations Office for Disaster Risk Reduction (UNDRR, 2022). Public preparedness, particularly among youth and rural populations, remains limited due to the absence of accessible and engaging educational tools. Conventional approaches often lack interactivity, reducing knowledge retention and behavioural change. To address these gaps, this study developed DisasterPrep, a user-centred mobile edutainment solution designed to enhance disaster awareness and preparedness. The research pursued three objectives: (i) to identify knowledge gaps among target users, (ii) to design a gamified mobile application tailored to their needs, and (iii) to evaluate its effectiveness in improving preparedness and resilience. A mixed-methods approach was adopted, including surveys, focus groups, and co-design workshops, followed by prototype testing with 30 participants in Malaysia. Quantitative data were collected through a structured survey measuring User Interface (UI) and User Experience (UX) using a 5-point Likert scale, with descriptive statistics computed for usability and engagement. Results revealed strong usability, with UI mean scores ranging from 4.04 to 4.60 and UX outcomes between 4.20 and 4.56. Tutorials, navigation flow, and progress tracking emerged as the most valued features, while simulation realism and quiz integration revealed more variable responses. Findings confirm alignment with Malaysia’s MySTIE strategic goals and contributions to SDG 3 (Good Health) and SDG 4 (Quality Education). This research demonstrates that gamified, user-centred mobile tools can significantly enhance disaster preparedness education, offering a scalable, inclusive model to strengthen community resilience. The novelty lies in integrating edutainment with structured evaluation, establishing a replicable framework for disaster education that bridges gaps in interactivity, engagement, and scalability.

Symmetric cryptography, particularly the Advanced Encryption Standard (AES), is widely used for secure data transmission due to its computational efficiency and strong encryption structure. However, limited internal randomness in AES makes it susceptible to advanced cryptanalytic attacks. To address this limitation, this research proposes an enhanced encryption approach that integrates Genetic Algorithm (GA) techniques into the AES framework to enhance randomness. The GA employs variable-length chromosomes and entropy-based fitness evaluation to evolve dynamic binary outputs through selection, crossover, and mutation operations. These evolved outputs are used to introduce controlled randomness into the encryption process, resulting in unpredictable and robust ciphertext. The expected outcome includes improved increased randomness, and stronger resistance to differential and linear attacks. In conclusion, the proposed GA-AES enhanced model offers a mechanism to strengthen symmetric encryption by introducing evolutionary randomness, making it more secure for modern data protection needs.

The security of data during communication is an ever-growing challenge, as outdated algorithms face increasing vulnerability. Audio steganography offers a promising alternative by embedding data within audio signals in a manner that is imperceptible to human listeners. Recent advancements in cover selection as well as cover generation techniques have improved the quality and suitability of audio for embedding, yet the parameters influencing imperceptibility remain underexplored. This research aims to identify and evaluate key audio parameters which are energy, the total and value distribution of silent samples. These parameters can be assessed prior to the embedding process which offer a potential advantage over existing metrics, typically require post-embedding analysis to accurately assess imperceptibility. The methodology of this research consists of five main stages: parameter identification, dataset preparation, parameter extraction, embedding, and evaluation. Signal-to-Noise Ratio (SNR) was employed as the primary metric to assess perceptual transparency, with 20% data capacity embedded in each audio of total 220 audio. The first experiment revealed a positive correlation as high as r = 0.706 between energy and SNR, indicating that higher-energy audio benefit from auditory masking, resulting in improved imperceptibility. The second experiment showed a negative correlation, r = –0.787 between total silent sample and SNR, confirming that embedding in silent sample increases the risk of perceptible artifacts. Silent sample that has higher value exhibited superior SNR values compared to those with extremely lower value. These findings highlight the importance of pre-embedding analysis in identifying suitable samples for embedding. By identifying and evaluating these influential parameters, this research contributes to the development of intelligent cover generation strategies that enhance the transparency of audio steganography systems. The insights presented offer a foundation for future design, optimization, and real-world application of robust data-hiding techniques.