INTERNET OF THINGS IN SPORTS: SECURITY OF SENSOR NETWORKS FOR HEALTH MONITORING

Abstract

The article addresses the problem of ensuring the security of sensor networks used for athlete health monitoring within Internet of Things (IoT) ecosystems. It is demonstrated that the digitalisation of sports and the widespread adoption of wearable sensing devices connected to mobile gateways and cloud platforms create a new class of risks related to the confidentiality, integrity, and availability of biometric data. Based on an analysis of international standards and recommendations, including NIST SP 800-213/213A, ENISA guidelines, and ISO/IEC 27001, as well as contemporary research on sports IoT technologies, eHealth, BLE security, and authentication in IoT-enabled healthcare, a conceptual multi-layer security model for sports IoT systems is developed. The proposed approach distinguishes sensor, gateway, server, and application layers, each characterised by its functional role, typical threats, and specific mitigation mechanisms that take into account device resource constraints and real-time operational requirements. At the sensor layer, the study substantiates the use of energy-efficient cryptographic algorithms, BLE LE Secure Connections mode, secure boot, signed OTA firmware updates, and hardware security modules such as Secure Elements for protected key storage. At the gateway layer, the use of MQTT and HTTPS over TLS 1.3, mutual authentication (mTLS), as well as the implementation of edge analytics and on-device AI, is examined to reduce the volume of raw data transmitted and to enhance privacy. The server layer is described as a domain of scalable analytics and identity management, where data-at-rest encryption, centralised key management, short-lived and rotation-enabled JWT tokens, and key revocation mechanisms are applied. At the application layer, a role-based access model for physicians, coaches, analysts, and administrative personnel is proposed, along with multi-factor authentication, protected audit logging, and controlled firmware updates via Signed OTA. Particular attention is given to the confidentiality of geolocation data, the use of pseudonymisation and coordinate coarsening, as well as ethical and legal aspects of processing athletes’ biometric information. The results show that the proposed model can serve as a methodological foundation for designing, auditing, and standardising digital solutions in both professional and recreational sports, including the development of internal security policies in clubs and sports federations. The integration of technical, organisational, and regulatory measures, complemented by mechanisms for validating the reliability of AI-generated decisions and limiting the autonomy of algorithmic outputs, is identified as a prerequisite for building a robust, trustworthy, and resilient health monitoring ecosystem in sports based on the Internet of Things.