scholarly journals A Secure and Robust Image Hashing Scheme Using Gaussian Pyramids

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1132 ◽  
Author(s):  
Iram Bashir ◽  
Fawad Ahmed ◽  
Jawad Ahmad ◽  
Wadii Boulila ◽  
Nouf Alharbi
Keyword(s):  
False Negative ◽  
Hash Functions ◽  
Feature Space ◽  
Image Hashing ◽  
Gaussian Pyramid ◽  
Image Hash ◽  
Perceptual Hash ◽  
Robust Image ◽  
Robust Image Hashing ◽  
Cryptographic Hash Functions

Image hash is an alternative to cryptographic hash functions for checking integrity of digital images. Compared to cryptographic hash functions, an image hash or a Perceptual Hash Function (PHF) is resilient to content preserving distortions and sensitive to malicious tampering. In this paper, a robust and secure image hashing technique using a Gaussian pyramid is proposed. A Gaussian pyramid decomposes an image into different resolution levels which can be utilized to obtain robust and compact hash features. These stable features have been utilized in the proposed work to construct a secure and robust image hash. The proposed scheme uses Laplacian of Gaussian (LOG) and disk filters to filter the low-resolution Gaussian decomposed image. The filtered images are then subtracted and their difference is used as a hash. To make the hash secure, a key is introduced before feature extraction, thus making the entire feature space random. The proposed hashing scheme has been evaluated through a number of experiments involving cases of non-malicious distortions and malicious tampering. Experimental results reveal that the proposed hashing scheme is robust against non-malicious distortions and is sensitive to detect minute malicious tampering. Moreover, False Positive Probability (FPP) and False Negative Probability (FNP) results demonstrate the effectiveness of the proposed scheme when compared to state-of-the-art image hashing algorithms proposed in the literature.

scholarly journals A Practical Blockchain Framework using Image Hashing for Image Authentication

2020 ◽  
Author(s):  
Manoranjan Paul ◽  
Cameron C White ◽  
Subrata Chakraborty
Keyword(s):  
New Technology ◽  
Hash Functions ◽  
Image Authentication ◽  
Image Hashing ◽  
Original Image ◽  
Multiple Image ◽  
System A ◽  
Image Hash ◽  
Authentication System ◽  
Cryptographic Hash Functions

Abstract Blockchain is a relatively new technology that can be seen as a decentralised database. Blockchain systems heavily rely on cryptographic hash functions to store their data, which makes it difficult to tamper with any data stored in the system. A topic that was researched along with blockchain is image authentication. Image authentication focuses on investigating and maintaining the integrity of images. As a blockchain system can be useful for maintaining data integrity, image authentication has the potential to be enhanced by blockchain. There are many techniques that can be used to authenticate images; the technique investigated by this work is image hashing. Image hashing is a technique used to calculate how similar two different images are. This is done by converting the images into hashes and then comparing them using a distance formula. To investigate the topic, an experiment involving a simulated blockchain was created. The blockchain acted as a database for images. This blockchain was made up of devices which contained their own unique image hashing algorithms. The blockchain was tested by creating modified copies of the images contained in the database, and then submitting them to the blockchain to see if it will return the original image. Through this experiment it was discovered that it is plausible to create an image authentication system using blockchain and image hashing. However, the design proposed by this work requires refinement, as it appears to struggle in some situations. This work shows that blockchain can be a suitable approach for authenticating images, particularly via image hashing. Other observations include that using multiple image hash algorithms at the same time can increase performance in some cases, as well as that each type of test done to the blockchain has its own unique pattern to its data.

scholarly journals Robust image hashing with compressed sensing and ordinal measures

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Zhenjun Tang ◽  
Hanyun Zhang ◽  
Shenglian Lu ◽  
Heng Yao ◽  
Xianquan Zhang
Keyword(s):  
Compressed Sensing ◽  
Image Hashing ◽  
Robust Image ◽  
Robust Image Hashing

Robust image hashing with embedding vector variance of LLE

2015 ◽  
Vol 43 ◽  
pp. 17-27 ◽  
Author(s):  
Zhenjun Tang ◽  
Linlin Ruan ◽  
Chuan Qin ◽  
Xianquan Zhang ◽  
Chunqiang Yu
Keyword(s):  
Image Hashing ◽  
Robust Image ◽  
Robust Image Hashing

scholarly journals A Novel Approach for Robust Perceptual Image Hashing

2021 ◽  
Vol 14 (3) ◽  
pp. 38
Author(s):  
Azhar Hadmi ◽  
Awatif Rouijel
Keyword(s):  
Side Information ◽  
Main Idea ◽  
Jpeg Compression ◽  
Image Hashing ◽  
Novel Approach ◽  
Perceptual Hash ◽  
Short Signature ◽  
Robust Image ◽  
Tampered Image ◽  
The Stability

Perceptual image hashing system generates a short signature called perceptual hash attached to an image before transmission and acts as side information for analyzing the trustworthiness of the received image. In this paper, we propose a novel approach to improve robustness for perceptual image hashing scheme for generating a perceptual hash that should be resistant to content-preserving manipulations, such as JPEG compression and Additive white Gaussian noise (AWGN) also should differentiate the maliciously tampered image and its original version. Our algorithm first constructs a robust image, derived from the original input by analyzing the stability of the extracted features and improving their robustness. From the robust image, which does perceptually resemble the original input, we further extract the final robust features. Next, robust features are suitably quantized allowing the generation of the final perceptual hash using the cryptographic hash function SHA1. The main idea of this paper is to transform the original image into a more robust one that allows the extraction of robust features. Generation of the robust image turns out be quite important since it introduces further robustness to the perceptual image hashing system. The paper can be seen as an attempt to propose a general methodology for more robust perceptual image hashing. The experimental results presented in this paper reveal that the proposed scheme offers good robustness against JPEG compression and Additive white Gaussian noise.

Robust Image Hashing Based Efficient Authentication for Smart Industrial Environment

2019 ◽  
Vol 15 (12) ◽  
pp. 6541-6550 ◽  
Author(s):  
Muhammad Sajjad ◽  
Ijaz Ul Haq ◽  
Jaime Lloret ◽  
Weiping Ding ◽  
Khan Muhammad
Keyword(s):  
Image Hashing ◽  
Industrial Environment ◽  
Robust Image ◽  
Robust Image Hashing

Robust Hash for Detecting and Localizing Image Tampering

2010 ◽  
Vol 439-440 ◽  
pp. 1018-1023
Author(s):  
De Long Cui ◽  
Yong Fu Liu ◽  
Jing Long Zuo
Keyword(s):  
Fourier Transform ◽  
Fractional Fourier Transform ◽  
Image Hashing ◽  
Post Processing ◽  
Feature Extracting ◽  
Image Tampering ◽  
Secret Keys ◽  
Robust Image ◽  
Hashing Algorithm ◽  
Robust Image Hashing

In order to improve the sensitive to illegal manipulations of image hashing, a novel robust image hashing algorithm based on fractional Fourier transform (FRFT) for detecting and localizing image tampering is proposed in this paper. The framework of generating an image hashing includes three steps: preprocessing, feature extracting and post processing. The robust hashing sequence is obtained by FRFT coefficients of image blocks. The security of proposed algorithm is totally depended on the orders of FRFT which are saved as secret keys. Experimental results show that the proposed scheme is robust against perceptually acceptable modifications to the image such as JPEG compression, mid-filtering, and rotation, more importantly the tampered place can be identified accurately.

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