ABSTRACT
COVID-19 is currently a major global public health challenge. In the battle against the outbreak of COVID-19, how to manage and share the COVID-19 Electric Medical Records (CEMRs) safely and effectively in the world, prevent malicious users from tampering with CEMRs, and protect the privacy of patients are very worthy of attention. In particular, the semi-trusted medical cloud platform has become the primary means of hospital medical data management and information services. Security and privacy issues in the medical cloud platform are more prominent and should be addressed with priority. To address these issues, on the basis of ciphertext policy attribute-based encryption, we propose a blockchain-empowered security and privacy protection scheme with traceable and direct revocation for COVID-19 medical records. In this scheme, we perform the blockchain for uniform identity authentication and all public keys, revocation lists, etc are stored on a blockchain. The system manager server is responsible for generating the system parameters and publishes the private keys for the COVID-19 medical practitioners and users. The cloud service provider (CSP) stores the CEMRs and generates the intermediate decryption parameters using policy matching. The user can calculate the decryption key if the user has private keys and intermediate decrypt parameters. Only when attributes are satisfied access policy and the user's identity is out of the revocation list, the user can get the intermediate parameters by CSP. The malicious users may track according to the tracking list and can be directly revoked. The security analysis demonstrates that the proposed scheme is indicated to be safe under the Decision Bilinear Diffie-Hellman (DBDH) assumption and can resist many attacks. The simulation experiment demonstrates that the communication and storage overhead is less than other schemes in the public-private key generation, CEMRs encryption, and decryption stages. Besides, we also verify that the proposed scheme works well in the blockchain in terms of both throughput and delay.
ABSTRACT
AlGaN-based deep-ultraviolet light-emitting diodes (DUV LEDs) are widely used in sterilization, sensing, water purification, medical treatment, non-line of sight (NLOS) communication and many other fields. Especially it has been reported that the global novel coronavirus (COVID-19) can be effectively inactivated by the DUV light with a wavelength below 280 nm (UVC) within a few seconds, which has also attracted great attention. However, the external quantum efficiency (EQE) of UVC LED is still at a low level, generally not more than 10%. As an important component of EQE, internal quantum efficiency (IQE) plays a crucial role in realizing high-performance DUV-LED. In order to improve the IQE of AlGaN-based DUV-LED, this work adopts an electron blocking layer (EBL) structure based on InAlGaN/AlGaN superlattice. The results show that the superlattice EBL structure can effectively improve the IQE compared with the traditional single-layer and double-layer EBL structure for the DUV-LED. On this basis, the optimization method based on JAYA intelligent algorithm for LED structure design is proposed in this work. Using the proposed design method, the InAlGaN/AlGaN superlattice EBL structure is further optimized to maximize the LED' s IQE. It is demonstrated that the optimized superlattice EBL structure is beneficial to not only the suppression of electron leakage but also the improvement of hole injection, leading to the increase of carrier recombination in the active region. As a result, the IQE of the DUV-LED at 200 mA injection current is 41.2% higher than that of the single-layer EBL structure. In addition, the optimized structure reduces IQE at high current from 25% to 4%. The optimization method based on intelligent algorithm can break through the limitation of the current LED structure design and provide a new method to improve the efficiency of AlGaN-based DUV-LED. © 2023 Chinese Physical Society.