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An important application of data sharing in cloud environment is the storage and retrieval of Patient Health Records (PHR) that maintain the patient's personal and diagnosis information. These records should be maintained with privacy and security for safe retrieval. The privacy mechanism protects the sensitive attributes. The security schemes are used to protect the data from public access. The data are allowed to be accessed only by authorized individuals. Each party is assigned with access permission for a set of attributes. Data owners update the patient data into third party cloud data centers. The attribute based encryption (ABE) scheme is used to secure these patient records. Multiple owners are allowed to access the same data values. The Multi Authority Attribute Based Encryption (MA-ABE) scheme is used to provide multiple authority based access control mechanism due to its vast access. The MA-ABE model is not tuned to provide identity based access mechanism. Distributed storage model is not supported in the MA-ABE model.The proposed system is designed to provide identity based encryption facility. The attribute based encryption scheme is enhanced to handle distributed attribute based encryption process. Data update and key management operations are tuned for multi user access environment.

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Visual saliency models mimic the human visual system to gaze towards fixed pixel positions and capture the most conspicuous regions in the scene. They have proved their efficacy in several computer vision applications. This paper provides a comprehensive review of the recent advances in eye fixation prediction and salient object detection, harnessing deep learning. It also provides an overview on multi-modal saliency prediction that considers audio in dynamic scenes. The underlying network structure and loss function for each model are explored to realise how saliency models work. The survey also investigates the inclusion of specific low-level priors in deep learning-based saliency models. The public datasets and evaluation metrics are succinctly introduced. The paper also makes a discussion on the key issues in saliency modeling along with some open problems and growing research directions in the field.