Secure Auditing Scheme with Content-Based Image Retrieval using Human Interaction (RF) in Cloud Computing Environment

Computer Science Engineering

“A picture is worth of thousands of words”! Image processing is used for image retrieval system for browsing, searching and retrieving images from a large database of digital images. There are two types of image search, Image Meta Search and Content-Based Image Retrieval (CBIR). CBIR is the mainframe of image retrieval system. To understand query semantics and users expectations so as to communicate faithful results in terms of accuracy, Relevance Feedback is incorporated into CBIR System. This system allows users to progressively refine the search results, to access iteratively the results as “relevant/irrelevant” or even giving him/her the opportunity to specify a degree of relevance, the system creates a new query that better captures the user’s needs, hence raising the opportunity to get more relevant image results. In the watermark-based protocol, a unique watermark is directly embedded into the encrypted images by the cloud server before images are sent to the query user. Hence, when an illegal image copy is found, the unlawful query user who distributes the image can be traced by the watermark extraction. Feature vectors get protected by the secure hashing algorithm, auditing and alert generation are used at image users side for verification purpose. TPA (Third Party Auditor) is used to detect fraud or malicious activities performed in a cloud environment.

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