Nowadays, there is the tendency to outsource data to cloud storage servers for data sharing purposes. In fact, this makes access control for the outsourced data a challenging issue. Ciphertext-policy attribute-based e...Nowadays, there is the tendency to outsource data to cloud storage servers for data sharing purposes. In fact, this makes access control for the outsourced data a challenging issue. Ciphertext-policy attribute-based encryption（CP-ABE） is a promising cryptographic solution for this challenge. It gives the data owner（DO） direct control on access policy and enforces the access policy cryptographically. However,the practical application of CP-ABE in the data sharing service also has its own inherent challenge with regard to attribute revocation. To address this challenge, we proposed an attribute-revocable CP-ABE scheme by taking advantages of the over-encryption mechanism and CP-ABE scheme and by considering the semitrusted cloud service provider（CSP） that participates in decryption processes to issue decryption tokens for authorized users. We further presented the security and performance analysis in order to assess the effectiveness of the scheme. As compared with the existing attributerevocable CP-ABE schemes, our attribute-revocable scheme is reasonably efficient and more secure to enable attribute-based access control over the outsourced data in the cloud data sharing service.展开更多
Lubricant diagnosis serves as a crucial accordance for condition-based maintenance(CBM)involving oil changing and wear examination of critical parts in equipment.However,the accuracy of traditional end-to-end diagnosi...Lubricant diagnosis serves as a crucial accordance for condition-based maintenance(CBM)involving oil changing and wear examination of critical parts in equipment.However,the accuracy of traditional end-to-end diagnosis models is often limited by the inconsistency and random fluctuations in multiple monitoring indicators.To address this,an attribute-driven adaptive diagnosis method is developed,involving three attributes:physicochemical,contamination,and wear.Correspondingly,a fuzzy fault tree(termed FFT)-based model is constructed containing the logic correlations from monitoring indicators to attributes and to lubricant failures.In particular,inference rules are integrated to mitigate conflicts arising from the reverse degradation of multiple indicators.With this model,the lubricant conditions can be accurately assessed through rule-based reasoning.Furthermore,to enhance its intelligence,the model is dynamically optimized with lubricant analysis knowledge and monitoring data.For verification,the developed model is tested with lubricant samples from both the fatigue experiment and actual aero-engines.Fatigue experiments reveal that the proposed model can improve the lubricant diagnosis accuracy from 73.4%to 92.6%compared with the existing methods.While for the engine lubricant test,a high accuracy of 90%was achieved.展开更多
P-集合(packet sets)是把动态特性引入到有限普通集合X内,改进有限普通集合X得到的一个动态模型;在一定的条件下,P-集合被还原成有限普通集合X。P-集合由内P-集合XF珚(internal packet set XF珚)与外P-集合XF(outerpacket set XF)构成...P-集合(packet sets)是把动态特性引入到有限普通集合X内,改进有限普通集合X得到的一个动态模型;在一定的条件下,P-集合被还原成有限普通集合X。P-集合由内P-集合XF珚(internal packet set XF珚)与外P-集合XF(outerpacket set XF)构成的集合对;或者,(XF珚,XF)是P-集合。P-推理(packet reasoning)由内P-推理(internal packet rea-soning)与外P-推理(outer packet reasoning)共同构成。利用内P-集合与内P-推理,给出了内P-信息恢复概念与内P-信息恢复特征、内P-信息恢复的内P-推理生成与它的属性潜藏、内P-信息恢复的信息元补充定理、内P-信息恢复的依赖性定理,以及内P-推理信息恢复的属性潜藏定理与属性潜藏发现定理。利用这些理论结果,给出内P-推理信息恢复在信息系统中的应用。展开更多
基金supported by the Major International(Regional)Joint Research Project of China National Science Foundation under Grant No.61520106007National High Technology Research and Development Program of China(863)under Grant No.2015AA016007
文摘Nowadays, there is the tendency to outsource data to cloud storage servers for data sharing purposes. In fact, this makes access control for the outsourced data a challenging issue. Ciphertext-policy attribute-based encryption（CP-ABE） is a promising cryptographic solution for this challenge. It gives the data owner（DO） direct control on access policy and enforces the access policy cryptographically. However,the practical application of CP-ABE in the data sharing service also has its own inherent challenge with regard to attribute revocation. To address this challenge, we proposed an attribute-revocable CP-ABE scheme by taking advantages of the over-encryption mechanism and CP-ABE scheme and by considering the semitrusted cloud service provider（CSP） that participates in decryption processes to issue decryption tokens for authorized users. We further presented the security and performance analysis in order to assess the effectiveness of the scheme. As compared with the existing attributerevocable CP-ABE schemes, our attribute-revocable scheme is reasonably efficient and more secure to enable attribute-based access control over the outsourced data in the cloud data sharing service.
基金supported in part by the National Natural Science Foundation of China(Nos.52275126 and 52105159)the Science and Technology Planning Project of Shaanxi Province,China(No.2024GX-YBXM-292).
文摘Lubricant diagnosis serves as a crucial accordance for condition-based maintenance(CBM)involving oil changing and wear examination of critical parts in equipment.However,the accuracy of traditional end-to-end diagnosis models is often limited by the inconsistency and random fluctuations in multiple monitoring indicators.To address this,an attribute-driven adaptive diagnosis method is developed,involving three attributes:physicochemical,contamination,and wear.Correspondingly,a fuzzy fault tree(termed FFT)-based model is constructed containing the logic correlations from monitoring indicators to attributes and to lubricant failures.In particular,inference rules are integrated to mitigate conflicts arising from the reverse degradation of multiple indicators.With this model,the lubricant conditions can be accurately assessed through rule-based reasoning.Furthermore,to enhance its intelligence,the model is dynamically optimized with lubricant analysis knowledge and monitoring data.For verification,the developed model is tested with lubricant samples from both the fatigue experiment and actual aero-engines.Fatigue experiments reveal that the proposed model can improve the lubricant diagnosis accuracy from 73.4%to 92.6%compared with the existing methods.While for the engine lubricant test,a high accuracy of 90%was achieved.
