Enhancing Data Protection in Dynamic Consent Management Systems: Formalizing Privacy and Security Definitions with Differential Privacy, Decentralization, and Zero-Knowledge Proofs

The General Data Protection Regulation (GDPR), enacted in the European Union in 2018, has significantly transformed the landscape of personal data management and protection. This article provides an overview of GDPR's impact, focusing on its applicability, fundamental principles and influence on data management practices, particularly within the European Society of Thoracic Surgeons (ESTS) database. GDPR's reach extends to all entities collecting and processing personal data of European Union residents, regardless of their location. It encompasses various data types, emphasizing meticulous handling and protection of identifiable information. Special categories of data, such as health and sensitive attributes, require even more stringent protection. The regulation sets legal, fair and transparent data processing principles, emphasizing accuracy, purpose limitation and data minimization. It also stresses accountability, leading to the appointment of Data Protection Officers and significant penalties for non-compliance. The ESTS database, designed to enhance thoracic surgical research and care, collects data on European procedures. It follows GDPR principles by pseudonymizing data, ensuring secure data transmission and providing clear instructions for data submission. The database contributes to research, policymaking and practice improvement in thoracic surgery by offering a comprehensive dataset for analysis. Here, we aim to shed light on the complexities of GDPR implementation and emphasize the need for comprehensive data management strategies to ensure compliance and enhance privacy protection with the contribution to the ESTS database. GDPR compliance comes with challenges, including potential human dignity and privacy rights violations. Data breaches can result in unauthorized disclosures, and non-compliance can lead to substantial fines and reputational damage. The implementation of GDPR encourages organizations to prioritize ethical data practices, security measures and transparent data handling. In conclusion, GDPR has revolutionized personal data protection by emphasizing accountability, transparency and individual rights. It has impacted organizations globally, promoting responsible data management practices. Adhering to GDPR ensures privacy protection, trust-building and overall enhancement of data management in today's data-driven environment.

In this paper, we construct a P2P dynamic trust management system based on the concept of trust network that covers aggregation computation of trust degree, the selection of trust chains and the assessment of overall trust. In particular, we optimized the searching algorithm of trust chains and the calculation of recommendation trust. The results of simulation show that the system can ameliorate the current research with respect to the overhead of computation and the lack of reliability. The constructed dynamic trust management system can provide network nodes with trust value effectively, objectively and dynamically, which can ensure the security and the stability of information systems.

This article addresses one of the key challenges in modern intelligent systems engineering: the practical implementation of the Privacy-by-Design principle, enshrined in the General Data Protection Regulation (GDPR), within artificial intelligence architectures. Existing approaches, such as federated learning, differential privacy, and homomorphic encryption, while effective tools, create a rigid trade-off between the level of personal data protection, model utility (accuracy), and computational efficiency when applied statically. Such a unified “one-size-fits-all” approach is inefficient, as it leads to either excessive protection of non-sensitive data, which unjustifiably degrades performance, or insufficient protection for the most vulnerable categories of information. The objective of this research is to develop a conceptual framework for a novel artificial intelligence architecture that resolves this issue through dynamic, risk-oriented management of privacy mechanisms. The result of this study is a proposed adaptive hybrid architecture. The scientific novelty of this work lies in shifting from a static model of applying Privacy-Enhancing Technologies (PETs) to a flexible, multi-layered system. This system classifies data and model components in real-time based on their sensitivity level and associated risks. Depending on the risk level, the architecture dynamically applies an optimal set of protection tools: from basic federated learning with light differential privacy guarantees for low-risk data to the application of homomorphic encryption for the most critical computations. At the core of the architecture is an optimization model that aims to maximize model utility while minimizing computational costs, ensuring compliance with predefined privacy thresholds for each data category as required by GDPR. This approach enables the creation of more efficient, secure, and productive intelligent systems that meet modern regulatory demands.

On May 25th, 2018, the EU General Data Protection Regulation (GDPR) came into force. Recognised as a comprehensive regulation for improving privacy and data protection, a substantial impact on data processing disciplines such as Serious Games (SG) research was expected.By conducting a scoping review, this paper explores the effects of GDPR on reporting of ethics approval, informed consent, ethics guidelines and data protection in SG studies. Five scientific databases were searched for research between 2016 and 2020 addressing Serious Games, Exergames and Applied Games. A total of 2146 full-text studies split into equal collections before and after GDPR were included. Lexicometric and keyword-in-context analysis were conducted and comparatively evaluated regarding ethics reporting and trends.Results unexpectedly show that GDPR so far hardly left a mark. While a slight increase of 12% in general ethics reporting can be observed, less than 6% of the studies after GDPR coming-into-force report on data protection. Ethics procedures remained consistent with most researchers reporting the approval from their home university committee and stating the Declaration of Helsinki as followed guidelines. Overall, the verifiable impact of GDPR was found negligibly small, with only 0.5% of studies referring to the regulation in the two years after introduction. Conclusively, further research is suggested to focus on integrating ethics and data protection guided on GDPR from an early conceptual stage to the reporting of the findings.

A dynamic memory management system has to take care of the allocation and deallocation of memory blocks in a software system. Real-time embedded systems add some more constraints to the design and the implementation of dynamic memory management systems if compared with the PC world. An increasing number of features are added to embedded mobile devices, however, resources like dynamic memory are limited. In addition, in real-time systems, real-time deadlines must be respected and allocations and deallocations must be done in due time. In this paper we present a case study on evaluating dynamic memory management in embedded real-time systems. We have used a scenario-based approach and used a simulation environment to evaluate the performance of different dynamic memory management systems. Our contribution is to present a practical approach, the tools and the rationales to evaluate dynamic memory management in embedded real-time systems.

EU General Data Protection Regulation: Changes and implications for personal data collecting companies

Aiming at the problem that the currently used dynamic management system based on Hadoop and B/S architecture is affected by the slow data mining rate, resulting in low efficiency of data dynamic management, a design of enterprise economic dynamic management system based on Spark technology is proposed. Deploy the physical architecture of the Spark-based economic dynamic management system, and build a data warehouse in this architecture to facilitate users to quickly view data in real time. The B/S (browser/server) model is adopted to design data collection modules, business service modules and performance modules to meet the needs of big data analysis and decision-making. When using Spark technology to dynamically adjust the difference data in the database, the rule base needs to be updated in time to convert the automatic conversion system to a detection system. Use the optimization algorithm of Spark Join operator to optimize the entire connection operation, filter out the project data without specific categories in the bank flow data, reduce the data entering the shuffle stage, and design a dynamic management process. It can be seen from the test results that the system has a maximum management efficiency of 92% in a safe environment. In a non-interference environment, the highest management efficiency is 0.95, which has an efficient management effect.KeywordsSpark technologyEnterprise economyDynamic managementData warehouseSpark Join operator

Purpose This article aims to examine the tension between freedom of expression and personal data protection, focusing on criminal conviction and offence data under the General Data Protection Regulation (GDPR). It analyses how legal frameworks, particularly Article 85 of the GDPR, attempt to reconcile public access to information with individual data privacy rights harmoniously. Design/methodology/approach Using a legal doctrinal approach primarily, this study examines GDPR provisions, especially Article 85, alongside relevant case law. The principle of proportionality serves as a key analytical tool to assess the necessity and justification of legal restrictions on data processing. Findings The research underscores the delicate balance between freedom of expression and data protection concerning criminal records. Article 85 plays a crucial role in establishing journalistic exemptions while ensuring data privacy. The principle of proportionality is vital in preventing disproportionate restrictions, requiring case-by-case evaluations. The study highlights the evolving nature of privacy-publicity conflicts, with the right to be forgotten serving as a safeguard against undue harm from outdated or minor convictions. Research limitations/implications This study has limitations, including its reliance on case-specific analyses, which overlook the broader impacts of the evolving digital media landscape, particularly social media and user-generated content. The focus on European legal frameworks (e.g. GDPR) restricts generalisability to non-EU jurisdictions with differing standards. Additionally, the analysis emphasises journalistic exemptions, neglecting other forms of expression – such as academic, artistic and literary – that also require balancing against personal data protection rights. Practical implications The research provides practical guidance for balancing data protection and freedom of expression, particularly under GDPR Article 85. It underscores the need for case-by-case assessments, ensuring proportionality and necessity when handling criminal conviction data. Policymakers and legal practitioners can use these insights to refine journalistic exemptions and prevent data misuse, especially in digital media contexts. Organisations, including media platforms, are encouraged to adopt responsible data-handling practices to safeguard privacy while enabling public interest reporting. Finally, the findings stress the importance of dynamic frameworks that adapt to evolving societal and technological contexts, supporting fair outcomes for both data protection and expression rights. Social implications This research highlights the delicate balance between individual data protection rights and freedom of expression, particularly regarding criminal conviction data. Its implications extend to societal concerns over data privacy, the potential misuse of personal information and the long-term impact on individuals, especially those with minor or outdated offences. As digital media evolves, these issues become more pressing, with the rise of social media and user-generated content complicating the legal landscape. Ensuring that privacy is upheld without stifling public access to essential information is crucial for maintaining both rights and societal transparency in an increasingly interconnected world. Originality/value This study enriches the debate on data protection and freedom of expression in crime-related data processing. By addressing journalistic exemptions and the evolving media landscape, it provides a nuanced perspective on safeguarding privacy while maintaining transparency in an era of digital accessibility.

Compensation for Breach of the General Data Protection Regulation

PurposeTo explain the authors’ position that the use of blockchain technology is not incompatible with European Union privacy laws and in particular the EU General Data Protection Regulation (GDPR).Design/methodology/approachExplains the basics of blockchain technology and the GDPR, several reasons why some scholars consider BC not to be compatible with the GDPR, and why the authors believe that the GDPR will be able to regulate the use of blockchain technology.FindingsThe current perception is that blockchain is not compatible with EU privacy laws. The authors disagree that this is the case and explain why none of the issues identified by legal scholars and stakeholders are likely to pose issues for blockchain technology. Their conclusion is that EU privacy laws are well able to regulate also this new technology. This does however not mean that blockchain will thus be suitable for all use and deployment cases.Originality/valuePractical guidance and explanation of complex issues by lawyers with extensive experience and expertise in dealing with data protection, cybersecurity, privacy, intellectual property and related issues.

In this paper we present a Dynamic Energy Management System elaborated to share available electrical energy, provided by a battery less hybrid source (PV-Wind), between motor-pumps used in desalination process.This Dynamic Energy Management System is combined to Power Field Oriented Control to maintain DC bus voltage stability and to control electrical power of motor-pumps used for water pumping and/or reverse osmosis desalination.Simulation and practical results are demonstrated and discussed to evaluate the power sharing performances and "Water-Energy" cooperative control effectiveness.

In order to avoid the safety problems of the public building structure in the dense passenger flow environment, the structural health monitoring system is combined with the Building Information Modeling (BIM) method. This paper proposed a dynamic building information management system based on Structural Health Monitoring (SHM) information to ensure the security of its passenger flow information for a crowded exhibition hall. The continuous development of BIM (building information modeling) technology has greatly promoted the development of the construction industry. We can achieve real-time updating and visualization of sensor monitoring data and effectively manage different types of monitoring information as well as improve the controllability and safety of building structure monitoring by introducing BIM technology into structural health monitoring. A static building information model (BIM) was established to generate dynamic passenger flow information through video data learning, and provide a basis for structural health monitoring system for structural safety analysis and emergency response functions under dense passenger flow conditions. A dynamic building information management system suitable for structural health monitoring was built to display the dynamic network of traffic capacity in real time, so that the building information model is dynamic and predictable. The establishment for the combination mechanism of BIM and SHM system improved the data information circulation of BIM system. It could carry out dynamic health monitoring management and early warning control of building structures, realize information sharing in the process of health monitoring, and effectively improve the safety and operational efficiency of public building structures.

Data Protection in Nigeria: A Review of the Nigerian Data Protection Regulation 2019 and the Need for Nigeria to Sign the African Convention on Data Protection

Differential privacy is a precise mathematical constraint meant to ensure privacy of individual pieces of information in a database even while queries are being answered about the aggregate. Intuitively, one must come to terms with what differential privacy does and does not guarantee. For example, the definition prevents a strong adversary who knows all but one entry in the database from further inferring about the last one. This strong adversary assumption can be overlooked, resulting in misinterpretation of the privacy guarantee of differential privacy. Herein we give an equivalent definition of privacy using mutual information that makes plain some of the subtleties of differential privacy. The mutual-information differential privacy is in fact sandwiched between $\epsilon$-differential privacy and $(\epsilon,\delta)$-differential privacy in terms of its strength. In contrast to previous works using unconditional mutual information, differential privacy is fundamentally related to conditional mutual information, accompanied by a maximization over the database distribution. The conceptual advantage of using mutual information, aside from yielding a simpler and more intuitive definition of differential privacy, is that its properties are well understood. Several properties of differential privacy are easily verified for the mutual information alternative, such as composition theorems.

Currently, South Korea s data protection law can be characterized as a rigid protection system focused on criminal punishment based on prior consent of data subject. It is known as the world s most powerful and strict regulatory legislation. Compared to the European Union s General Data Protection Regulation(GDPR), Korea s data protection law is considered one of the strictest privacy regulations in the world. Many say that the current protection model in Korea has lost its balance of protection and utilization. It requires prior consent of the data subject in order to collect, use, and provide personal data on the premise that personal data must be protected like a private secret. And it imposes excessive administrative fines and criminal penalties for violations. This article was written with the aim of providing clues as to how Korea s data protection law should find a reasonable balance between protection and use in the future. Fortunately, the Personal Data Protection Act, which was revised in February 2020, can be positively evaluated as a legislative attempt to find a reasonable balance between protection and utilization. Similar to the European Union s GDPR, the revised law permits the change of purpose to the extent reasonably related to the purpose of collection. And it introduced the concept of pseudonymized data to increase the possibility of using pseudonymized data, and integrated the enforcement system into the Personal Data Protection Committee to secure the expertise and independence of the data protection agency. This can be assessed as a step closer to global standards. Nevertheless, Korea s data protection law still has a rigid protection model from the perspective of global standards. This article presents three urgent legislative tasks to be improved. First, as in the European Union s GDPR, the six grounds of lawfulness for collection, use, and provision of personal data must be acknowledged, and in principle, the same grounds must be applied in the field of information and communications networks. Second, the requirements for the exercise of the right to the protection of personal data, reasons for defense, and exceptions must be prepared in a reasonable manner. Third, excessive criminal punishment should be reorganized. Like Germany or the UK, criminal sanctions should be imposed only for serious violations of the law, or, as in Japan, criminal sanctions should be imposed for violations of corrective orders of the Personal Data Protection Committee.