Smith–Magenis syndrome (SMS) is a rare, underdiagnosed condition due to limited public awareness of genetic testing and a lengthy diagnostic process. Voice analysis can be a noninvasive tool for monitoring and detecting SMS. In this paper, the cepstral peak prominence and mel-frequency cepstral coefficients are used as disease monitoring and detection metrics. In addition, an efficient neural network, incorporating synthetic data processes, was used to detect SMS in a cohort of individuals with the disease. Three study cases were conducted with a set of 19 SMS patients and 292 controls. The three study cases employed various oversampling and undersampling techniques, including SMOTE, random oversampling, NearMiss, random undersampling, and 16 additional methods, resulting in balanced accuracies ranging from 69% to 92%. This is the first study using a neural network model to focus on a rare genetic syndrome using phonation analysis data. By using synthetic data (oversampling and undersampling) and a CNN, it was possible to detect SMS with high levels of accuracy. Voice analysis and deep learning techniques have proven to be a useful and noninvasive method. This is a finding that may help in the complex identification of this syndrome as well as other rare diseases.

Homomorphic encryption has seen limited application in real-world settings due to its high computational costs, which often impede practical use in latency-sensitive scenarios. Addressing this challenge, this research work presents an efficient, partially homomorphic encryption framework for privacy-preserving ID creation tailored to biometric applications, such as border control or access to secure restricted facilities. The proposed solution leverages the additive homomorphic properties of Paillier and Elliptic Curve ElGamal encryption schemes to encapsulate biometric data within a secure cryptographic layer, enabling rapid verification while minimizing computation and storage demands. Paillier encryption ensures robust security with maximal accuracy, while Elliptic Curve ElGamal optimizes for minimal ciphertext sizes, both meeting rigorous ISO biometric security standards. Experimental results demonstrate that the framework achieves high accuracy with reduced memory and bandwidth requirements, with encrypted IDs as compact as 4 KiB, making it suitable for scalable deployment. This research work represents a key advancement in homomorphic encryption applications, balancing privacy and efficiency without the usual overhead, and making it feasible for real-time biometric processing. In summary, this framework offers a pioneering solution in secure biometric verification, setting a new standard for privacy-preserving applications, positioning it as a promising model for future secure identification systems.

The production of phonation involves very complex processes, linked to the physical, clinical, and emotional state of the speaker. Thus, in populations with neurological diseases, it is possible to find the imprint in the voice signal left by the deterioration of certain cortical areas or part of the neurocognitive mechanisms that are involved in speech. In previous works, the authors determined the relationship between the pathological characteristics of the voice of the speakers with Smith-Magenis syndrome (SMS) and a lower value in the cepstral peak prominence (CPP) with respect to normative speakers. They also described the presence of subharmonics in their voices. The present study aims to verify whether both characteristics can be used simultaneously to differentiate SMS voices from neurotypical voices. It will also be analyzed if there is variation in the trajectory of the formants coinciding with the subharmonics. To do this, the effect of subharmonics in the voices of 12 SMS individuals was isolated to see if they were responsible for the lower CPP values. An evaluation of the CPP was also carried out in the areas of subharmonic presence, from the peak that reflected the value of f0, rather than using the most prominent peak. This offered us a baseline for the CPP value in the presence of subharmonics. It was checked if changes in the formants occurred synchronously to the appearance of those subharmonics. If so, the muscles that control the position of the jaw and tongue would be affected at the same time as the larynx. The latter was difficult to observe since the samples were very short. A comparison of phonatory performance of a sustained /a/ between a normotypical group and non-normotypical group of children was carried out. These groups were balanced and matched in age and gender. The Spanish Association of Smith-Magenis Syndrome (ASME) provides almost 20% of the population in Spain. The CPP allows differentiating between normative speakers and those with SMS, even when isolating the effect of subharmonics. The CPP is a robust index for determining the degree of dysphonia. It makes it possible to differentiate pathological voices from healthy voices even when subharmonics are present. The presence of subharmonics is a characteristic of voices of SMS individuals and is not present in healthy ones. Both indexes can be used simultaneously to differentiate SMS voices from neurotypical voices.

As the demand for expansive back-end systems in online applications continues to grow, novel frameworks are necessitated to address the escalating operational demands, energy consumption, and associated costs. Traditional Client–Server models, while offering centralized security and reliability, are characterized by their high deployment and maintenance expenses. Conversely, Peer-to-Peer (P2P) models, despite being cost-effective and scalable, are hindered by inherent security and data integrity challenges. Moreover, the lack of a central authority in P2P systems complicates a definitive resolution of scenarios involving stakes, where users cannot withdraw without incurring a tangible loss. In this research work, a hybrid back-end framework is introduced, combining the advantages of both models through the utilization of cryptographic algorithms and Secure Multi-Party Computation (MPC) protocols. The baseline solution is lightweight and fully composable, making it capable of utilizing different more complex slot-in MPC techniques. The proposed framework’s effectiveness is demonstrated through a simplified two-player Spades game, although it is fully generalizable to any application. Evaluations across multiple case studies reveal substantial performance enhancements compared to conventional approaches, particularly post-initialization, highlighting the scheme’s potential as a cost-effective, energy-efficient, and secure solution for modern online applications.