In this letter, we introduce a novel keys distribution optimization scheme for CP-ABE based access control. This scheme integrates roles, role hierarchies and objects grouping to accelerate keys distribution, meanwhile the CP-ABE encrypting overhead is reduced by adopting deterministic cryptographic function. Experiments show that our scheme obtains noticeable improvement over the original one, especially when the number of objects is much greater than that of users.

After exploring the classic Lambertian reflectance model, we proposed an effective illumination estimation model to extract illumination invariants for face recognition under complex illumination conditions in this paper. The estimated illumination by our method not only meets the actual lighting conditions of facial images, but also conforms to the imaging principle. Experimental results on the combined Yale B database show that the proposed method can extract more robust illumination invariants, which improves face recognition rate.