相关论文: ModelChain: Decentralized Privacy-Preserving Healt…
Privacy preservation is a big concern for various sectors. To protect individual user data, one emerging technology is differential privacy. However, it still has limitations for datasets with frequent queries, such as the fast accumulation…
As blockchain technology rapidly evolves, the demand for enhanced efficiency, security, and scalability grows.Transformer models, as powerful deep learning architectures,have shown unprecedented potential in addressing various blockchain…
COVID-19 is a severe global epidemic in human history. Even though there are particular medications and vaccines to curb the epidemic, tracing and isolating the infection source is the best option to slow the virus spread and reduce…
In modern healthcare systems, being able to share electronic health records is crucial for providing quality care and for enabling a larger spectrum of health services. Health data sharing is dependent on obtaining individual consent which,…
The use of collaborative and decentralized machine learning techniques such as federated learning have the potential to enable the development and deployment of clinical risk predictions models in low-resource settings without requiring…
With the increasing importance of data sharing for collaboration and innovation, it is becoming more important to ensure that data is managed and shared in a secure and trustworthy manner. Data governance is a common approach to managing…
Academic examination systems worldwide continue to rely on centralised, opaque record-keeping that is often vulnerable to credential forgery, result tampering, examiner bias, and the absence of transparent re-evaluation pathways. Existing…
The digital transformation of the medical sector requires solutions that are convenient and efficient for all stakeholders while protecting patients' sensitive data. One example that has already attracted design-oriented research are…
Health management has become a primary problem as new kinds of diseases and complex symptoms are introduced to a rapidly growing modern society. Building a better and smarter healthcare infrastructure is one of the ultimate goals of a smart…
Human genomic data carry unique information about an individual and offer unprecedented opportunities for healthcare. The clinical interpretations derived from large genomic datasets can greatly improve healthcare and pave the way for…
Financial fraud cases are on the rise even with the current technological advancements. Due to the lack of inter-organization synergy and because of privacy concerns, authentic financial transaction data is rarely available. On the other…
With the widespread attention and application of artificial intelligence (AI) and blockchain technologies, privacy protection techniques arising from their integration are of notable significance. In addition to protecting privacy of…
Motivated by the explosive computing capabilities at end user equipments, as well as the growing privacy concerns over sharing sensitive raw data, a new machine learning paradigm, named federated learning (FL) has emerged. By training…
Federated Learning (FL) has gained widespread popularity in recent years due to the fast booming of advanced machine learning and artificial intelligence along with emerging security and privacy threats. FL enables efficient model…
Secure storage and sharing of patients' medical data over the Internet are part of the challenges for emerging healthcare systems. The use of blockchain technology in medical Internet of things systems can be considered a safe and novel…
There has been an intense concern for security alternatives because of the recent rise of cyber attacks, mainly targeting critical systems such as industry, medical, or energy ecosystem. Though the latest industry infrastructures largely…
Centralized social networks have experienced a transformative impact on our digital era communication, connection, and information-sharing information. However, it has also raised significant concerns regarding users' privacy and individual…
The paper proposes a Blockchain (BC) system to prevent counterfeiting in health insurance sector. The results show the system strength in terms of achieving data integrity and privacy of data. Moreover, the results show that the consensus…
As global industries transition towards Industry 5.0 predictive maintenance PM remains crucial for cost effective operations resilience and minimizing downtime in increasingly smart manufacturing environments In this chapter we explore how…
This paper proposes a distributed deep learning framework for privacy-preserving medical data training. In order to avoid patients' data leakage in medical platforms, the hidden layers in the deep learning framework are separated and where…