Mutual Image-Based Authentication Framework with JPEG2000 in Wireless Environment

Ginesu, Giaime; Giusto, Daniele D.; Onali, Tatiana

doi:10.1155/wcn/2006/73685

Cited by 9 publications

(4 citation statements)

References 13 publications

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“…Ginesu et al [ 31 ] presented a novel mutual image-based authentication framework. It is a challenge-response scheme that uses a visual password and image scrambling.…”

Section: Classification Of Active Image Forgery Detectionmentioning

confidence: 99%

Comprehensive analyses of image forgery detection methods from traditional to deep learning approaches: an evaluation

Sharma

Kumar²,

Sharma³

2022

Multimed Tools Appl

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The digital image proves critical evidence in the fields like forensic investigation, criminal investigation, intelligence systems, medical imaging, insurance claims, and journalism to name a few. Images are an authentic source of information on the internet and social media. But, using easily available software or editing tools such as Photoshop, Corel Paint Shop, PhotoScape, PhotoPlus, GIMP, Pixelmator, etc. images can be altered or utilized maliciously for personal benefits. Various active, passive and other new deep learning technology like GAN approaches have made photo-realistic images difficult to distinguish from real images. Digital image tamper detection now focuses on determining the authenticity and consistency of digital photos. The major research problems use generic solutions and strategies, such as standardized data sets, benchmarks, evaluation criteria and generalized approaches.This paper overviews the evaluation of various image tamper detection methods. A brief discussion of image datasets and a comparative study of image criminological (forensic) methods are included in this paper. Furthermore, recently developed deep learning techniques along with their limitations have also been addressed. This study aims to comprehensively analyze image forgery detection methods using conventional and advanced deep learning approaches.

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“…Ginesu et al [ 31 ] presented a novel mutual image-based authentication framework. It is a challenge-response scheme that uses a visual password and image scrambling.…”

Section: Classification Of Active Image Forgery Detectionmentioning

confidence: 99%

Comprehensive analyses of image forgery detection methods from traditional to deep learning approaches: an evaluation

Sharma

Kumar²,

Sharma³

2022

Multimed Tools Appl

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“…Image based mutual authentication [12] has become now more reliable, when the scrambling technique applied [7].Users will me users should keep the click points to enter into the system, because the image get scrambled and it will be rearranged according to the scrambling algorithm discussed above. User have the provision to select his favorite areas according to his interest.…”

Section: Implementation Aspectsmentioning

confidence: 99%

Persuasive Cued Click Based Graphical Password with Scrambling For Knowledge Based Authentication Technique with Image Scrambling.

2013

IOSR-JCE

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“…Recently, a number of good solutions have been proposed for authenticating the image data stream in the presence of random packet loss. For example: 1.A novel mutual image-based authentication framework [13] has been presented. It consists in a challenge-response scheme based on visual password and image scrambling.…”

Section: Literature Review and Present State Of Artmentioning

confidence: 99%

“…Further, wavelet transforms can generally be computed in linear time, thus allowing for fast algorithms. Most conventional wavelet-based image authentication schemes reported in the literature have three shortcomings [13][14][15]:…”

Section: Decompose the Image Using Secrete Parameterized Wavelet Filtermentioning

confidence: 99%

Digital Signature Scheme for Image

Doke¹,

Patil²

2012

IJCA

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Image authentication techniques have recently gained great attention due to its importance for a large number of multimedia applications. Digital images are increasingly transmitted over non-secure channels such as the Internet. Therefore, military, medical and quality control images must be protected against attempts to manipulate them; such manipulations could tamper the decisions based on these images. To protect the authenticity of multimedia images, several approaches have been proposed. These approaches include conventional cryptography, fragile and semi-fragile watermarking and digital signatures that are based on the image content. The aim of this paper is to present emerging technique for image authentication. It also introduces the new concept of image content authentication and discusses the most important requirements for an effective image authentication system design. Methods which are described provide strict or selective authentication, tamper detection, localization and reconstruction capabilities and robustness against different desired image processing operations. [1]

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Mutual Image-Based Authentication Framework with JPEG2000 in Wireless Environment

Cited by 9 publications

References 13 publications

Comprehensive analyses of image forgery detection methods from traditional to deep learning approaches: an evaluation

Comprehensive analyses of image forgery detection methods from traditional to deep learning approaches: an evaluation

Persuasive Cued Click Based Graphical Password with Scrambling For Knowledge Based Authentication Technique with Image Scrambling.

Digital Signature Scheme for Image

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