(1.School of Computer Science,，Beijing Institute of Technology，Beijing 100081,，China,； 2.Yangtze Delta Region Academy of Beijing Institute of Technology，Jiaxing 314019,，China,； 3.China Institute of Marine Technology and Economy，Beijing 100081,，China,； 4.School of Cyberspace Science and Technology，Beijing Institute of Technology,，Beijing 100081,，China)
Abstract： Deep learning-based target detection technology is being widely used in the field of medical detections. For training a large number of medical images, we can construct an effective classification model to effectively predict the disease situation of patients and provide a powerful auxiliary medical means of decision-making. In order to improve the prediction accuracy, massive training data are the premise to construct an effective learning model. However, medical data involve patients′ privacy and are directly related to diagnoses. Sharing medical data needs to guarantee privacy, accuracy and tamper-proof. Existing centralized medical storage schemes face many security issues, e.g., privacy disclosure. This paper proposes a blockchain-based artificial intelligence detection model for medical data that uses a target detection technology to assist physicians during the diagnosis process. In our model, blockchain technology supports realizing the decentralized and un-tampered aggregation of training parameters. Encryption and signature technology are used to protect privacy and smart Contract is implemented to evaluate the accuracy of server diagnosis. The proposed model will contribute to solving the issues in medical data barriers and privacy disclosure.
Key words : deep learning；blockchain,；secure data sharing,；artificial intelligence detection
