Currently, there are several challenges that cloud-based healthcare systems around the world are facing. The most important issue is to ensure security and privacy, or in other words, to ensure the confidentiality, integrity, and availability of the data. Although the main provisions for data security and privacy were present in the former legal framework for the protection of personal data, the General Data Protection Regulation (GDPR) introduces new concepts and new requirements. In this paper, we present the main changes and the key challenges of the GDPR and, at the same time, we present how a cloud-based security policy could be modified in order to be compliant with the GDPR, as well as how cloud environments can assist developers to build secure and GDPR compliant cloud-based healthcare systems. The major concept of this paper is dual-purpose; primarily, to facilitate cloud providers in comprehending the framework of the new GDPR and secondly, to identify security measures and security policy rules, for the protection of sensitive data in a cloud-based healthcare system, following our risk-based security policy methodology that assesses the associated security risks and takes into account different requirements from patients, hospitals, and various other professional and organizational actors.

The General Data Protection Regulation (GDPR) harmonizes personal data protection laws across the European Union, affecting all sectors including the healthcare industry. For processing operations that pose a high risk for data subjects, a Data Protection Impact Assessment (DPIA) is mandatory from May 2018. Taking into account the criticality of the process and the importance of its results, for the protection of the patients’ health data, as well as the complexity involved and the lack of past experience in applying such methodologies in healthcare environments, this paper presents the main steps of a DPIA study and provides guidelines on how to carry them out effectively. To this respect, the Privacy Impact Assessment, Commission Nationale de l’Informatique et des Libertés (PIA-CNIL) methodology has been employed, which is also compliant with the privacy impact assessment tasks described in ISO/IEC 29134:2017. The work presented in this paper focuses on the first two steps of the DPIA methodology and more specifically on the identification of the Purposes of Processing and of the data categories involved in each of them, as well as on the evaluation of the organization’s GDPR compliance level and of the gaps (Gap Analysis) that must be filled-in. The main contribution of this work is the identification of the main organizational and legal requirements that must be fulfilled by the health care organization. This research sets the legal grounds for data processing, according to the GDPR and is highly relevant to any processing of personal data, as it helps to structure the process, as well as be aware of data protection issues and the relevant legislation.

Introduction: Advances in Information Technology are transforming healthcare systems, with a focus on improving accessibility, efficiency, resilience, and service quality. Wearable devices such as smartwatches and mental health trackers enable continuous biometric data collection, offering significant potential to enhance chronic disorder treatment and overall healthcare quality. However, these technologies introduce critical security and privacy risks, as they handle sensitive patient data.Methods: To address these challenges, this paper proposes a security-by-design cloud-based architecture that leverages wearable body sensors for continuous patient monitoring and mental disorder prediction. The system integrates an Elasticsearch-powered backend to manage biometric data securely. A dedicated framework was developed to ensure confidentiality, integrity, and availability (CIA) of patient data through secure communication protocols and privacy-preserving mechanisms.Results: The proposed architecture successfully enables secure real-time biometric monitoring and data processing from wearable devices. The system is designed to operate 24/7, ensuring robust performance in continuously tracking both mental and physiological health indicators. The inclusion of Elasticsearch provides scalable and efficient data indexing and retrieval, supporting timely healthcare decisions.Discussion: This work addresses key security and privacy challenges inherent in continuous biometric data collection. By incorporating a security-by-design approach, the proposed framework enhances trustworthiness in healthcare monitoring technologies. The solution demonstrates the feasibility of balancing real-time health monitoring needs with stringent data protection requirements.

Currently, there are several challenges that Cloud-based health-care Systems, around the world, are facing. The most important issue is to ensure security and privacy or in other words to ensure the confidentiality, integrity and availability of the data. Although the main provisions for data security and privacy were present in the former legal framework for the protection of personal data, the General Data Protection Regulation (GDPR) introduces new concepts and new requirements. In this paper, we present the main changes and the key challenges of the General Data Protection Regulation, and also at the same time we present how the Cloud-based Security Policy methodology proposed in [1] could be modified in order to be compliant with the GDPR and how Cloud environments can assist developers to build secure and GDPR compliant Cloud-based health Systems. The major concept of this paper is, primarily, to facilitate Cloud Providers in comprehending the framework of the new General Data Protection Regulation and secondly, to identify security measures and security policy rules for the protection of sensitive data in a Cloud-based Health System, following our risk-based Security Policy Methodology that assesses the associated security risks and takes into account different requirements from patients, hospitals, and various other professional and organizational actors.