Abstract-Nowadays, Multimedia security [1] is a major issue. Images, video, audio, text files are losing their credibility day by day as they can be distorted or manipulated by using several tools. Ensuring the authenticity [2] and integrity of digital media is a major issue. The manipulation made by forgery tools are so smoothly done that we don't even suspect that forgery may be involved in digital content. Multimedia data is facing several issues related to illegal distribution, duplication and manipulation of information conveyed by them. The digital watermarking [3] technique plays an important role in protecting digital content. In this paper, On the basis of their operating principles different watermarking techniques are categorized [4]. Attacks, applications and requirements [5] related to watermarking techniques are also discussed. Different watermarking techniques proposed by researchers for protecting copyrights of digital media are presented which are based on spatial and frequency domain. Frequency domain are getting much more attention due to use of wavelets which have high degree of resemblance to human visual system. In digital watermarking, secret information is embedded with original data for maintaining ownership rights of the digital content. Spatial domain watermarking techniques work over pixel characteristics and frequency domain watermarks concerned about different transformations that can be used with digital content. Imperceptibility, robustness, security, complexity and capacity are some requirements of the digital watermarking which completely depends on the algorithm used for watermarking.

Copy‐move image forgery is one of the most popular image tampering technique which can be performed for vicious purposes. In this forgery technique, selected region is copied and pasted at different locations on the same image to produce a manipulated image. Such forgery is denigratory as it can alter the image content by hiding or appending visual information. In this study, the authors propose a novel keypoint‐based technique to detect forged images sustaining composite attacks consisting of various combinations of geometrical and post‐processing operations. In the authors' method, AKAZE and FAST techniques are used to extract keypoints from the image. Non‐maximal value suppression with automatic contrast thresholding is performed during FAST keypoint extraction. SIFT and DAISY descriptors are computed corresponding to extracted keypoints. PCA is applied over SIFT and DAISY descriptors to discard lower components which are sensitive to distortions occurred in images. They apply a correlation‐based nearest neighbour search technique to detect similarity among keypoint descriptors. HDBSCAN algorithm is applied to obtain matched keypoint clusters. Further, RANSAC algorithm is utilised for removal of keypoint outliers. In comparison to state‐of‐the‐art techniques, their approach achieve high F‐measure (%) and low FPR (%) for image‐level as well as pixel‐level copy‐move forgery detection.

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Copy-move forgery is being used at various fields to hide significant information or to append additional information in image. Image forgery results in false interpretations. In this forgery, one section of image is copied and then it is pasted over the same image at different location. Although, various techniques are suggested by researchers but finding forged section of varying size and located at different locations on image is complicated. To resolve such problems we introduce a new hybrid approach for finding copy-move forgery based on Discrete Wavelet Transform with Local Binary Pattern. At First, image is moldered into three color components. Discrete Wavelet Transform is applied over the image which results in four sub bands. Approximation sub image contains low frequency components having maximum information. LL subimage is divided in overlapping blocks. Local Binary Pattern is calculated for blocks to generate descriptors to match similar blocks. Shift vectors are computed to find group of block pairs with similar shifting. It is observed by our experimental results that proposed method can efficiently detect manipulated images having different forgery size with high detection accuracy and low false positive rate as comparison to other state-of-the-art.

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