Text image secret sharing with hiding based on color feature

The Secret Sharing is a scheme for sharing data into n pieces using (k, n) threshold method. Secret Sharing becomes an efficient method to ensure secure data transmission. Some visual cryptography techniques don’t guarantee security transmission because the secret information can be retrieved if the hackers obtain the number of shares. This study present a secret sharing method with hiding based on YCbCr color space. The proposed method is based on hiding the secret text file or image into a number of the cover image. The proposed method passes through three main steps: the first is to convert the secret text file or image and all cover images from RGB to YCbCr, the second step is to convert each color band to binary vector, then divide this band in the secret image into four-part, each part is appended with a binary vector of each cover image in variable locations, the third step is converting the color space from YCbCr to RGB color space and the generated shares, hidden with covers, are ready for transmission over the network. Even if the hackers get a piece of data or even all, they cannot retrieve the whole picture because they do not know where to hide the information. The results of the proposed scheme guarantee sending and receiving data of any length. The proposed method provides more security and reliability when compared with others. It hides an image of size (234x192) pixels with four covers. The MSE result is 3.12 and PSNR is 43.74. The proposed method shows good results, where the correlation between secret and retrieved images is strong ranging from (0.96 to 0.99). In the proposed method the reconstructed image quality is good, where original and reconstructed images Entropy are 7.224, 7.374 respectively

Data Service Outsourcing and Privacy Protection in Mobile Internet

Mobile Internet data have the characteristics of large scale, variety of patterns, and complex association. On the one hand, it needs efficient data processing model to provide support for data services, and on the other hand, it needs certain computing resources to provide data security services. Due to the limited resources of mobile terminals, it is impossible to complete large-scale data computation and storage. However, outsourcing to third parties may cause some risks in user privacy protection. This monography focuses on key technologies of data service outsourcing and privacy protection, including the existing methods of data analysis and processing, the fine-grained data access control through effective user privacy protection mechanism, and the data sharing in the mobile Internet

Privacy-preserving efficient searchable encryption

Data storage and computation outsourcing to third-party managed data centers, in environments such as Cloud Computing, is increasingly being adopted by individuals, organizations, and governments. However, as cloud-based outsourcing models expand to society-critical data and services, the lack of effective and independent control over security and privacy conditions in such settings presents significant challenges. An interesting solution to these issues is to perform computations on encrypted data, directly in the outsourcing servers. Such an approach benefits from not requiring major data transfers and decryptions, increasing performance and scalability of operations. Searching operations, an important application case when cloud-backed repositories increase in number and size, are good examples where security, efficiency, and precision are relevant requisites. Yet existing proposals for searching encrypted data are still limited from multiple perspectives, including usability, query expressiveness, and client-side performance and scalability. This thesis focuses on the design and evaluation of mechanisms for searching encrypted data with improved efficiency, scalability, and usability. There are two particular concerns addressed in the thesis: on one hand, the thesis aims at supporting multiple media formats, especially text, images, and multimodal data (i.e. data with multiple media formats simultaneously); on the other hand the thesis addresses client-side overhead, and how it can be minimized in order to support client applications executing in both high-performance desktop devices and resource-constrained mobile devices. From the research performed to address these issues, three core contributions were developed and are presented in the thesis: (i) CloudCryptoSearch, a middleware system for storing and searching text documents with privacy guarantees, while supporting multiple modes of deployment (user device, local proxy, or computational cloud) and exploring different tradeoffs between security, usability, and performance; (ii) a novel framework for efficiently searching encrypted images based on IES-CBIR, an Image Encryption Scheme with Content-Based Image Retrieval properties that we also propose and evaluate; (iii) MIE, a Multimodal Indexable Encryption distributed middleware that allows storing, sharing, and searching encrypted multimodal data while minimizing client-side overhead and supporting both desktop and mobile devices