Attribute-Based Encryption (ABE) must provide an efficient revocation mechanism since a user’s private key can be compromised or expired over time. The existing revocable ABE schemes have the drawbacks of heavy computational costs on key updates and encryption operations, which make the entities for performing these operations a possible bottleneck in practice applications. In this paper, we propose an efficient Ciphertext-Policy Attribute-Based Online/Offline Encryption with user Revocation (R-CP-ABOOE). We integrate the subset difference method with ciphertext-policy ABE to significantly improve key-update efficiency on the side of the trusted party from O(rlog⁡(N/r)) to O(r), where N is the number of users and r is the number of revoked users. To reduce the encryption burden for mobile devices, we use the online/offline technology to shift the majority of encryption work to the offline phase, and then mobile devices only need to execute a few simple computations to create a ciphertext. In addition, we exploit a novel trick to prove its selective security under the q-type assumption. Performance analysis shows that our scheme greatly improves the key-update efficiency for the trusted party and the encryption efficiency for mobile devices.

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Due to the shortcoming of linear normalization for sensitivity in electrical tomography system, nonlinear formulas are derived about electrical resistance tomography (ERT) , capacitance tomography (ECT) and electromagnetic tomography (EMT). Those formulas are deduced according to the characteristics of analytical solution and system structure. The role of normalization in data processing is introduced. Logarithmic normalization formula is summarized for ERT. In ECT, parallel model and serial model are introduced, and nonlinear formulas are described depending on real distribution in object field. Mainly, special normalization formula is deduced.

Electromagnetic tomography technology is a new process tomography technology. The aim of this study is to develop a new image reconstruction algorithm suitable to electromagnetic tomography and verify its convergence. The advantages and development of electromagnetic tomography technology and image reconstruction algorithms are introduced briefly. Based on conjugate gradient algorithm, modified conjugate gradient algorithm for Electromagnetic Tomography (EMT) is proposed. Convergence of the modified conjugate gradient algorithm is analyzed. In the light of the lab electromagnetic tomography system, modified conjugate gradient algorithm for reconstructing images is verified. By evaluation of image error and the relevance, regularization algorithm, Landweber algorithm, conjugate gradient algorithm and modified conjugate gradient algorithm are compared. It can draw the conclusion that for different flow patterns, modified conjugate gradient algorithm is superior to other algorithms in the 8 coils electromagnetic tomography lab system.