HILBERT-LSB-C as Authentication System for Color Medical Images Syifak Izhar Hisham Faculty of Computer Science and Software Eng. Universiti Malaysia Pahang Gambang, Malaysia penawar85@gmail.com Jasni Mohamad Zain Faculty of Computer Science and Software Eng. Universiti Malaysia Pahang Gambang, Malaysia jasni@ump.edu.my Nurul Wahidah Arshad Faculty of Electrical and Electronics Eng. Universiti Malaysia Pahang Pekan, Malaysia wahidah@ump.edu.my Liew Siau-Chuin Faculty of Computer Science and Software Eng. Universiti Malaysia Pahang Gambang, Malaysia liewsc@ump.edu.my Abstract—This paper proposes a new numbering method for a fragile watermarking algorithm aimed at improving color medical image watermarking. The proposed method uses Hilbert pattern numbering before watermarking operations such as parity bits check and comparison between average intensities as the authentication data. The authentication data embedded in the same host image are utilized to localize any tamper using block- wise approach. The method is very effective since it only requires a secret key and public, chaotic mixing algorithm to recover the attacked image. We use the Hilbert mapping approach, which is more compatible with medical image modalities, which is not only specifically to the square shape of image but applicable to all kinds and modalities of the image. We propose the algorithm to match the criterion of having 3 planes in a color image. The peak-signal-noise-ratio value of the proposed scheme is very good, achieving up to 56 decibelf. Keywords—authentication; Hilbert; localization; security; recovery I. INTRODUCTION Authentication method is seen as very important in medical images. A study of [1] has reported that the evaluation method for medical image watermarking techniques should be more stringent than regular image watermarking. One of the reasons is the medical images are available in different sizes and modalities such as CT, MRI, and X-ray. A watermarking scheme for medical image should invisibly embed data in the image without changing its size or format. The watermarking scheme should also compatible to all modalities of medical images. Among the criterion that is focused in medical image watermarking is the importance of not changing the meaning of even one pixel to ensure no misdiagnosis happens. A watermarking method is considered good if it survives after being attacked by various kinds of noise. Medical images usually degrade when transmission because of Gaussian noise. Therefore, when developing a new watermarking method, the requirement is to be robust against Gaussian noise and speckle noise. Another requirement of a quality watermarking method is to solve the problem of vector quantization (VQ) counterfeiting attack and collage attack. One popular way is by breaking block-wise independence as proposed by [2]. Chang (2007) [3] claims that modification to some blocks would be done effortlessly if malicious attackers know the block-mapping sequence in advance, which in this case, when we use the typical raster pattern. Hung (2013) [4] also states that a unique scan pattern is known as a secure method of encryption for having great compression before embedding, which can be further investigated in this research whether it is also good in watermarking or not. The block numbering process is seen as critical as it also decides the location of the embedded watermark data when mapping. With the probability of getting the tamper attack in the middle of medical image is high, a unique numbering system is seen as helpful to protect the region of interest in the middle [5]. However, as we aim to develop schemes that is compatible with all types of modalities, we cannot say that the region of interest (ROI) is definitely only in the middle. As an example, a scanned femur in MRI will has the ROI as from top to the bottom of the image as that part of a body is long. Lin et. al [2] proposed the idea of embedding the recovery data of original block into another block in cover block. This is to separate the block independency, which can optimize the security of original data. The method is very efficient and time saving since it only uses two simple operations for authentication, which are parity bits check and average intensities comparison. The embedding space is three least- significant-bits (LSBs) in every bit of pixels. The detection process is based on a hierarchical structure which three times of checking are done. Based on the approach in [6] which using unique and random mapping using two-dimensional transformation, [2] used public chaotic mixing algorithm to recover tampered images. 2015 4th International Conference on Software Engineering and Computer Systems (ICSECS), Kuantan, Pahang, Malaysia. August 19-21, 2015 15 978-1-4673-6722-6/15/$31.00 ©2015 IEEE