Research On Self-adaptive Access Control Technologies For Encrypted Medical Data In Cloud Computing

With the rapid popularization of cloud computing,Internet of Things and other new-generation information technologies,more and more medical data are encrypted before stored in the cloud.It not only provides users with efficient and convenient medical services,but also greatly improves the informatization level of the medical industry.However,medical data often contains users’ private information.It is an urgent problem to realize efficient management and safe sharing of users’ medical data.In order to realize the efficient sharing of encrypted medical data,the access control technologies for medical data based on attributebased encryption has attracted widespread attention from academia and industry.It realizes the secure sharing of medical data by setting fine-grained access policy,thus ensuring the confidentiality and availability of medical data.Although the existing access control technologies based on attribute-based encryption can realize the secure sharing of encrypted data,the existing methods can only ensure the availability of data under normal circumstances.When the data owner encounters an emergency(such as a medical emergency),the user cannot provide timely and effective medical assistance due to the inability to decrypt the medical data,bringing serious consequences to the data owner.In order to solve this problem,some scholars proposed the self-adaptive access control technologies.The data owner additionally sets an emergency decryption key and sends it to a trusted emergency contact person.The emergency contact person helps decrypt when an emergency occurs.However,the scheme has the following shortcomings: 1.The emergency contact person needs to be kept online at all times;2.The two cloud model brings extra computation and communication overhead.In view of the above problems,this thesis conducts in-depth research on the self-adaptive access control technologies for medical data,and the main work is as follows:· Based on fuzzy identity-based encryption and convergent encryption,this thesis proposes an efficient self-adaptive access control scheme for medical data.The scheme uses the user’s biometric information(such as fingerprint)as the decryption key in emergency situations,effectively avoiding the single point of failure.Furthermore,the proposed scheme supports cross-user secure deduplication and reduces the storage overhead on the server side.The results of security and efficiency analysis show that the proposed scheme can realize the efficient decryption for medical data in the emergency and ensure the confidentiality of medical data.The research result has been published by International Academic Journal: International Journal of Computational Science and Engineering.· Based on the idea of attribute version number and re-encryption technology,this thesis proposes a dynamic self-adaptive access control scheme for medical data.The scheme selects a different number for each attribute to identify the part of the ciphertext that is affected by the attribute.When the attribute revocation occurs,the client only needs a small amount of computation to update the affected part of the ciphertext,which reduces the computing burden of the client.The results of security and efficiency analysis show that the proposed scheme can dynamically manage the users’ access permission and ensure the confidentiality of medical data.