On Secure Image Hashing by Higher-Order Statistics | IEEE Conference Publication | IEEE Xplore

On Secure Image Hashing by Higher-Order Statistics


Abstract:

Due to the fact that the same multimedia content can have different digital representations, content-based hashing is important for multimedia identification and authenti...Show More

Abstract:

Due to the fact that the same multimedia content can have different digital representations, content-based hashing is important for multimedia identification and authentication. In this paper we discuss some issues on image hashing by higher-order statistics. We show by experiments that fourth-order cumulants can be used for image hashing and they have better overall performance than fourth-order-moments which are used in an existing algorithm. We further extend the algorithm to a more secure version by incorporating a secret key. It is achieved by choosing different statistic patterns from image blocks according to a secure pseudo-random number generator. Simulation shows satisfactory results.
Date of Conference: 24-27 November 2007
Date Added to IEEE Xplore: 22 December 2008
ISBN Information:
Conference Location: Dubai, United Arab Emirates

1. INTRODUCTION

The success of digital technologies such as JPEG, MPEG, MP3, and the Internet has brought the world into a multimedia era, in which an enormous amount of multimedia data is being produced and manipulated every second. Consequently, two challenging issues have arisen: 1) it is difficult to identify multimedia content in a large database; 2) it is difficult to authenticate multimedia content due to the advance of editing software. These two issues both suffer from the fact, that the same multimedia content may have different digital representations. On one hand, the same content can be represented by various file formats, qualities, etc.; on the other hand, it might undergo signal processing such as smoothing, denoising, etc. – they all result in almost the same content but the underlying binary files can be quite different. In order to cope with this problem, content-based hashing, also known as perceptual or robust hashing, was proposed as a promising solution.

References

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