2022
DOI: 10.47852/bonviewaia2202289
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Prevention of Shoulder-Surfing Attack Using Shifting Condition with the Digraph Substitution Rules

Abstract: Graphical passwords are implemented as an alternative scheme to replace alphanumeric passwords to help users to memorize their password. However, most of the graphical password systems are vulnerable to shoulder-surfing attack due to the usage of the visual interface. In this research, a method that uses shifting condition with digraph substitution rules is proposed to address shoulder-surfing attack problem. The proposed algorithm uses both password images and decoy images throughout the user authentication p… Show more

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Cited by 19 publications
(7 citation statements)
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“…Traditional image steganalysis mainly relies on prior knowledge for manual operation to achieve the purpose of deciphering encrypted information. 15 The use of deep learning technology has widened in image steganography due to its growing development. Therefore, this study combines with deep learning technology proposed an ISM based on CNN and AM, hoping to promote the development of ISM.…”
Section: Analysis Of Ism For Deep Learning In Computer Communicationmentioning
confidence: 99%
“…Traditional image steganalysis mainly relies on prior knowledge for manual operation to achieve the purpose of deciphering encrypted information. 15 The use of deep learning technology has widened in image steganography due to its growing development. Therefore, this study combines with deep learning technology proposed an ISM based on CNN and AM, hoping to promote the development of ISM.…”
Section: Analysis Of Ism For Deep Learning In Computer Communicationmentioning
confidence: 99%
“…Descriptors containing light and viewpoint invariance have similar matching accuracy to descriptors containing light and viewpoint variation characteristics, while descriptors containing viewpoint invariance and illumination variation characteristics have relatively low matching accuracy. When the pixel judgment threshold is within the range of, 2,5 the matching accuracy of the four combinations increases rapidly. Conversely, when the judgment threshold falls in the range of, 5,10 accuracy tends to stabilize.…”
Section: Performance Analysis Of Local Feature Algorithmmentioning
confidence: 99%
“…l p (x hw ∶ y hw ) is the logarithmic diffusion function. The Loss function in the construction phase of the local feature descriptor is shown in Equation (5).…”
Section: Local Feature Constructionmentioning
confidence: 99%
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