5 research outputs found

    Content Authentication and Forge Detection using Perceptual Hash for Image Database

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    Popularity of digital technology is very high. Number of digital images are being created and stored every day. This introduces a problem for managing image databases and security of images. One cannot determine if an image already exists in a database without exhaustively searching through all the entries. Further complication arises from the fact that two images appearing identical to the human eye may have distinct digital representations, making it difficult to compare a pair of images. Also the security of database server is questionable. The proposed framework provides the content authentication and forges detection of image. This can be done by generating perceptual image hash using SIFT algorithm, Perceptual image hash also known as perceptual image signature. It has been proposed as a primitive method to solve problems of image content authentication. The perceptual image hash is generated by using the perceptual features that are in accordance with human’s visual characteristics. It allows tampering of images to permissible extent e.g. improving slight brightness or contrast in image. A perceptual image hash is expected to be able to survive unintentional distortion and reject malicious tampering within an acceptable extend .Therefore it provides a more efficient approach to analyzing changes of image perceptual content and make sure database server is authenticated or not

    A Short Survey on Perceptual Hash Function

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    The authentication of digital image has become more important as these images can be easily manipulated by using image processing tools leading to various problems such as copyright infringement and hostile tampering to the image contents. It is almost impossible to distinguish subjectively which images are original and which have been manipulated. There are several cryptographic hash functions that map the input data to short binary strings but these traditional cryptographic hash functions is not suitable for image authentication as they are very sensitive to every single bit of input data. When using a cryptographic hash function, the change of even one bit of the original data results in a radically different value. A modified image should be detected as authentic by the hash function and at the same time must be robust against incidental and legitimate modifications on multimedia data. The main aim of this paper is to present a survey of perceptual hash functions for image authentication.Keywords: Hash function, image authentication*Cite as: Arambam Neelima, Kh. Manglem Singh, “A Short Survey on Perceptual Hash Function†ADBU-J.Engg Tech, 1(2014) 0011405(8pp

    Modified CSLBP

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    Image hashing is an efficient way to handle digital data authentication problem. Image hashing represents quality summarization of image features in compact manner. In this paper, the modified center symmetric local binary pattern (CSLBP) image hashing algorithm is proposed. Unlike CSLBP 16 bin histogram, Modified CSLBP generates 8 bin histogram without compromise on quality to generate compact hash. It has been found that, uniform quantization on a histogram with more bin results in more precision loss. To overcome quantization loss, modified CSLBP generates the two histogram of a four bin. Uniform quantization on a 4 bin histogram results in less precision loss than a 16 bin histogram. The first generated histogram represents the nearest neighbours and second one is for the diagonal neighbours. To enhance quality in terms of discrimination power, different weight factor are used during histogram generation. For the nearest and the diagonal neighbours, two local weight factors are used. One is the Standard Deviation (SD) and other is the Laplacian of Gaussian (LoG). Standard deviation represents a spread of data which captures local variation from mean. LoG is a second order derivative edge detection operator which detects edges well in presence of noise. The proposed algorithm is resilient to the various kinds of attacks. The proposed method is tested on database having malicious and non-malicious images using benchmark like NHD and ROC which confirms theoretical analysis. The experimental results shows good performance of the proposed method for various attacks despite the short hash length

    A Review of Hashing based Image Copy Detection Techniques

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    Images are considered to be natural carriers of information, and a large number of images are created, exchanged and are made available online. Apart from creating new images, the availability of number of duplicate copies of images is a critical problem. Hashing based image copy detection techniques are a promising alternative to address this problem. In this approach, a hash is constructed by using a set of unique features extracted from the image for identification. This article provides a comprehensive review of the state-of-the-art image hashing techniques. The reviewed techniques are categorized by the mechanism used and compared across a set of functional & performance parameters. The article finally highlights the current issues faced by such systems and possible future directions to motivate further research work

    Reflective-Physically Unclonable Function based System for Anti-Counterfeiting

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    Physically unclonable functions (PUF) are physical security mechanisms, which utilize inherent randomness in processes used to instantiate physical objects. In this dissertation, an extensive overview of the state of the art in implementations, accompanying definitions and their analysis is provided. The concept of the reflective-PUF is presented as a product security solution. The viability of the concept, its evaluation and the requirements of such a system is explored
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