Compatible 2D-Code Having Tamper Detection System with QR-Code

Takayuki, Ishihara; Niimi, Michiharu

doi:10.1109/iih-msp.2014.129

Cited by 7 publications

(4 citation statements)

References 2 publications

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“…Work that was not done mainly focuses on QR code production and ignores digital detection system solutions and uses encryption without taking 2014 detect signature and wet usability into account. The content modifications for QR codes [18].…”

Section: Literature Reviewmentioning

confidence: 99%

A QR Code Used for Personal Information Based On Multi-Layer Encryption System

Haroon Rashid Hammood Al Dallal,

Wijdan Noaman Marzoog Al Mukhtar

2023

Int. J. Interact. Mob. Technol.

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Protecting and concealing sensitive data in the modern world is challenging. Due to insufficient protection and privacy, it is feasible for critical information to be fabricated. This led to a significant financial loss for someone. The intended recipient must be trusted with sensitive information and be able to independently authenticate the accuracy of the information by independently checking the specifics. There are several driving the rise in QR codes used for information transmission. Due to their enormous capacity for storing information, QR codes are vital for dissemination. However, most currently deployed QR code solutions employ insecure data formats and never employ encryption. Secure QR Code is data protection and data concealing available technology. The Quick Response (QR) code is widely used and accessible without extensive technical training. Now, the user data stored in a QR code is effectively public knowledge and occasionally even illegally used. To address the abovementioned issues, this study's authors propose a novel QR code encryption system. Using the image's mathematical processing method, we may apply the equivalence class principle to the ordered equations of the two-dimensional code, producing the desired cryptographic result. This method exploits the unique visual properties of the QR code. Only a QR code reader can decode the code's useful information, which is too complex for standard reading methods. It will be utilised to address issues in speedy business client data protection Security, commodity anticounterfeiting, and bicycle sharing QR codes.

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Section: Literature Reviewmentioning

confidence: 99%

A QR Code Used for Personal Information Based On Multi-Layer Encryption System

Haroon Rashid Hammood Al Dallal,

Wijdan Noaman Marzoog Al Mukhtar

2023

Int. J. Interact. Mob. Technol.

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“…Reference [14] proposed a QR code tamper detection system that depends on a digital signature. The approach is to hide the digital signature using a special stereographic algorithm.…”

Section: Related Workmentioning

confidence: 99%

Secure Real-Time Computational Intelligence System Against Malicious QR Code Links

Wahsheh

Al-Zahrani

2021

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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Web attackers aim to propagate malicious links using various techniques to deceive users. They attempt to control victims’ devices or obtain their passwords remotely, thereby acquiring access to bank accounts, financial transactions, or private and sensitive information they trade via the Internet. QR codes are accessible, free, easy to use, and can be scanned through several free apps on smartphones. As there is no standard structure or authentication phase in QR code generation, such codes are vulnerable to suspicious online content embedding, i.e., phishing, Cross-Site Scripting (XSS), and malware. Many studies have highlighted the attacks that may be perpetrated using barcodes, and there are some security countermeasures. Several of these solutions are limited to malicious link detection methods or require knowledge of cryptographic techniques. This study’s main objective is to detect malicious URLs embedded in QR codes. A dataset of 90 000 benign and malicious URLs was collected from various resources, and their lexical properties were extracted. Two computational intelligence models, fuzzy logic and multilayer perceptron artificial neural network (MLP-ANN), were applied and compared. An MLP-ANN was identified as the best classifier for detecting malicious URLs, and a proactive, secure, real-time computational intelligence barcode scanner implementation (BarCI ) against malicious QR code links was proposed based on this classifier. The results demonstrate that this approach enables efficient real-time attack detection with 82.9% accuracy

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“…In Ishihara and Niimi (2014), it is proposed a tamper detection system for QR codes based on steganographically embedding a digital signature into the error correcting area. However, the paper appears preliminary as it only considers small sizes for signatures x and the embedding of actual signatures is left as a future work.…”

Section: Related Workmentioning

confidence: 99%