Blockchain Empowered Arbitrable Data Auditing Scheme for Network Storage as a Service

Xu, Yang; Ren, Ju; Zhang, Yan; Zhang, Cheng; Shen, Bo; Zhang, Yaoxue

doi:10.1109/tsc.2019.2953033

Cited by 170 publications

(113 citation statements)

References 22 publications

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“…(3) Third, how to further fuse different privacy protection solutions [28][29][30][31] for better performances is still an open problem that calls for future study.…”

Section: Further Discussionmentioning

confidence: 99%

Multi-Source Medical Data Integration and Mining for Healthcare Services

et al. 2020

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With the advent of Internet of Health (IoH) age, traditional medical or healthy services are gradually migrating to the Web or Internet and have been producing a considerable amount of medical data associated with patients, doctors, medicine, medical infrastructure and so on. Effective fusion and analyses of these IoH data are of positive significances for the scientific disaster diagnosis and medical care services. However, IoH data are often distributed across different departments and contain partial user privacy. Therefore, it is often a challenging task to effectively integrate or mine the sensitive IoH data, during which user privacy is not disclosed. To overcome the above difficulty, we put forward a novel multi-source medical data integration and mining solution for better healthcare services, named PDFM (Privacy-free Data Fusion and Mining). Through PDFM, we can search for similar medical records in a time-efficient and privacy-preserving manner, so as to offer patients with better medical and health services. A group of experiments are enacted and implemented to demonstrate the feasibility of the proposal in this work.

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“…(3) Third, how to further fuse different privacy protection solutions [28][29][30][31] for better performances is still an open problem that calls for future study.…”

Section: Further Discussionmentioning

confidence: 99%

Multi-Source Medical Data Integration and Mining for Healthcare Services

et al. 2020

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“…A majority of researchers can just work on a certain modal data. However, we believe that the advances in Internet of Things and privacy techniques 48-51 will make more and more multimodal datasets become available in the near future. Even though a whole multimodal TCM diagnostic architecture is not completely implemented for now, this work would be a first step towards applying multimodal DNN architecture to TCM diagnosis.…”

Section: Discussionmentioning

confidence: 99%

A multimodal deep architecture for traditional Chinese medicine diagnosis

Dai

Wang

Dai

et al. 2020

Concurrency and Computation

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Traditional Chinese medicine (TCM) is found on a long‐term medical practice in China. Rare human brains can fully grasp the deep TCM knowledge derived from a tremendous amount of experience. In this big data era, a big electronic brain might be competent via deep learning techniques. For this prospect, the electronic brain needs to process various heterogeneous data, such as images, texts, audio signals, and other sensory data. It used to be a challenge to analyze the heterogeneous data by the computer‐aided system until the advances of the powerful deep learning tools. We propose a multimodal deep learning framework to mimic a TCM practitioner to diagnose a patient on the basis of multimodal perceptions of see, listen, smell, ask, and touch. The framework learns common representations from various high‐dimensional sensory data, and fuse the information for final classification. We propose to use conceptual alignment deep neural networks to embed prior knowledge and obtain interpretable latent representations. We implement a multimodal deep architecture to process tongue image and description text data for TCM diagnosis. Experiments illustrate that the multimodal deep architecture can extract effective features from heterogeneous data, produce interpretable representations, and finally achieve a higher accuracy than either corresponding unimodal architectures.

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“…The sports impact on people health and wellbeing, so the sports play a key role in people's daily behavior activities [31][32][33]. Thus, the government needs to reasonably allocate the public sports resources to increase the degree of the people's sport participation.…”

Section: Discussionmentioning

confidence: 99%

Fuzzy Keywords-Driven Public Sports Resource Allocation Strategies Retrieval With Privacy-Preservation

Sang

Zhang

et al. 2020

IEEE Access

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Currently, the government proposes various public sports resource allocation strategies to promote the construction of public sports in the local. Thus, searching for the document database becomes an economic and efficient way for government officials to understand the contents of various public sports resource allocation strategies. As the government officials lack background knowledge of public sports resource allocation, the government officials are hard to retrieve appropriate documents. What's more, the document database is generally unwilling to share all text document information with the government official as some documents contain sensitive data information. Considering the above drawbacks, we put forward a fuzzy keywords-driven public sports resource allocation strategies retrieval approach based on the Simhash (named PSRASk+S) in the paper. The retrieval approach can accurately recommend appropriate documents to the government officials, by using the text description mining of documents and the fuzzy keywords search technology. Furthermore, the retrieval process is not revealing the sensitive data information of the irrelevant public sports resource allocation strategy document to the government officials, so the retrieval process can achieve local information protection mechanism. Finally, a case study explains the feasibility and effectiveness of our retrieval approach step by step.

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Blockchain Empowered Arbitrable Data Auditing Scheme for Network Storage as a Service

Cited by 170 publications

References 22 publications

Multi-Source Medical Data Integration and Mining for Healthcare Services

Multi-Source Medical Data Integration and Mining for Healthcare Services

A multimodal deep architecture for traditional Chinese medicine diagnosis

Fuzzy Keywords-Driven Public Sports Resource Allocation Strategies Retrieval With Privacy-Preservation

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