Protecting Sensitive Data in the Information Age: State of the Art and Future Prospects

Stach, Christoph; Gritti, Clémentine; Bräcker, Julia; Behringer, Michael; Mitschang, Bernhard

doi:10.3390/fi14110302

Cited by 9 publications

(5 citation statements)

References 199 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The intersection of artificial intelligence (AI) and machine learning (ML) with healthcare privacy has led to significant advancements in protecting sensitive patient information. Some studies revealed how AI algorithms could be trained to automatically redact sensitive information from healthcare records, thereby reducing the risk of data exposure [21], [22]. ML models could effectively classify data access as either legitimate or suspicious, thus streamlining the audit process [23], [24].…”

Section: B Ai/ml In Enhancing Healthcare Privacymentioning

confidence: 99%

Innovative Applications of Large Language Models for Medical Record Access Audits

陳文意,

黃兆明

2024

Preprint

View full text Add to dashboard Cite

This study explores the application of Mistral 8x7b, a state-of-the-art Large Language Model (LLM) with a mixture of experts architecture, in auditing access to medical records. By conducting a comprehensive evaluation, including both quantitative and qualitative analyses, we demonstrate that Mistral 8x7b significantly outperforms traditional audit methods in detecting unauthorized access, showcasing superior accuracy, precision, recall, and F1 score metrics. Additionally, our findings reveal notable improvements in computational efficiency, indicating the model's potential to enhance the privacy and security of healthcare data systems significantly. The research addresses the broader implications for healthcare privacy, AI ethics, and the responsible integration of AI technologies in sensitive domains. Despite acknowledging certain limitations and the necessity for further validation in real-world settings, this study underscores the transformative potential of advanced AI models like Mistral 8x7b in improving data security protocols and contributing to the safeguarding of patient information in an increasingly digital healthcare landscape.

show abstract

Section: B Ai/ml In Enhancing Healthcare Privacymentioning

confidence: 99%

Innovative Applications of Large Language Models for Medical Record Access Audits

陳文意,

黃兆明

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Finally, PET can be attached to each policy rule. To this end, we evaluated a variety of privacy filters for specific types of data (e.g., location data, health data, or audio data) [222]. These reflect the privacy requirements expressed by data producers.…”

Section: Data Provisioningmentioning

confidence: 99%

Data Is the New Oil–Sort of: A View on Why This Comparison Is Misleading and Its Implications for Modern Data Administration

Stach

2023

Future Internet

Self Cite

View full text Add to dashboard Cite

Currently, data are often referred to as the oil of the 21st century. This comparison is not only used to express that the resource data are just as important for the fourth industrial revolution as oil was for the technological revolution in the late 19th century. There are also further similarities between these two valuable resources in terms of their handling. Both must first be discovered and extracted from their sources. Then, the raw materials must be cleaned, preprocessed, and stored before they can finally be delivered to consumers. Despite these undeniable similarities, however, there are significant differences between oil and data in all of these processing steps, making data a resource that is considerably more challenging to handle. For instance, data sources, as well as the data themselves, are heterogeneous, which means there is no one-size-fits-all data acquisition solution. Furthermore, data can be distorted by the source or by third parties without being noticed, which affects both quality and usability. Unlike oil, there is also no uniform refinement process for data, as data preparation should be tailored to the subsequent consumers and their intended use cases. With regard to storage, it has to be taken into account that data are not consumed when they are processed or delivered to consumers, which means that the data volume that has to be managed is constantly growing. Finally, data may be subject to special constraints in terms of distribution, which may entail individual delivery plans depending on the customer and their intended purposes. Overall, it can be concluded that innovative approaches are needed for handling the resource data that address these inherent challenges. In this paper, we therefore study and discuss the relevant characteristics of data making them such a challenging resource to handle. In order to enable appropriate data provisioning, we introduce a holistic research concept from data source to data sink that respects the processing requirements of data producers as well as the quality requirements of data consumers and, moreover, ensures a trustworthy data administration.

show abstract

“…As more and more personal data are involved, the processing of such data inevitably raises privacy concerns. Therefore, Stach et al [6] investigate which privacy-enhancing technologies (PETs) can be used to systematically conceal certain information patterns contained in the data without compromising the overall data utility. However, in a highly heterogeneous landscape like the IoT, there is no compelling one-size-fits-all solution to this end.…”

Section: Articlesmentioning

confidence: 99%

Special Issue on Security and Privacy in Blockchains and the IoT Volume II

Stach

Gritti

2023

Future Internet

Self Cite

View full text Add to dashboard Cite

show abstract

Protecting Sensitive Data in the Information Age: State of the Art and Future Prospects

Cited by 9 publications

References 199 publications

Innovative Applications of Large Language Models for Medical Record Access Audits

Innovative Applications of Large Language Models for Medical Record Access Audits

Data Is the New Oil–Sort of: A View on Why This Comparison Is Misleading and Its Implications for Modern Data Administration

Special Issue on Security and Privacy in Blockchains and the IoT Volume II

Contact Info

Product

Resources

About