QR codes are widely used in applications such as information sharing,advertising,and digital payments.However,their growing adoption has made them attractive targets for malicious activities,including malware distribu...QR codes are widely used in applications such as information sharing,advertising,and digital payments.However,their growing adoption has made them attractive targets for malicious activities,including malware distribution and phishing attacks.Traditional detection approaches rely on URL analysis or image-based feature extraction,whichmay introduce significant computational overhead and limit real-time applicability,and their performance often depends on the quality of extracted features.Previous studies in malicious detection do not fully focus on QR code securitywhen combining convolutional neural networks(CNNs)with recurrent neural networks(RNNs).This research proposes a deep learning model that integrates AlexNet for feature extraction,principal component analysis(PCA)for dimensionality reduction,and RNNs to detect malicious activity in QR code images.The proposed model achieves both efficiency and accuracy by transforming image data into a compact one-dimensional sequence.Experimental results,including five-fold cross-validation,demonstrate that the model using gated recurrent units(GRU)achieved an accuracy of 99.81%on the first dataset and 99.59%in the second dataset with a computation time of only 7.433 ms per sample.A real-time prototype was also developed to demonstrate deployment feasibility.These results highlight the potential of the proposed approach for practical,real-time QR code threat detection.展开更多
为解决一维条码使用依靠数据库、受到极大限制的问题 ,设计的 QR Code码作为一种矩阵式二维码 ,具有超高速识读、全方位识读 ,能够有效地表示中国汉字、日本汉字等其他二维码所没有的特点。 QR Code用于印刷地图上同一位置的直接输入、...为解决一维条码使用依靠数据库、受到极大限制的问题 ,设计的 QR Code码作为一种矩阵式二维码 ,具有超高速识读、全方位识读 ,能够有效地表示中国汉字、日本汉字等其他二维码所没有的特点。 QR Code用于印刷地图上同一位置的直接输入、检索系统 ,有很强的使用价值。展开更多
With the rise of the Internet of Things(IoT),various devices in life and industry are closely linked.Because of its high payload,stable error correction capability,and convenience in reading and writing,Quick Response...With the rise of the Internet of Things(IoT),various devices in life and industry are closely linked.Because of its high payload,stable error correction capability,and convenience in reading and writing,Quick Response(QR)code has been widely researched in IoT.However,the security of privacy data in IoT is also a very important issue.At the same time,because IoT is developing towards low-power devices in order to be applied to more fields,the technology protecting the security of private needs to have the characteristics of low computational complexity.Visual Secret Sharing(VSS),with its features of safety and low computational cost,can fully meet the requirements of communication security in IoT.Therefore,a VSS scheme with QR code(VSS-QR)was proposed and has been applied to some extent.In VSS-QR,the secret is shared into a series of shares.These shares are usually common QR codes,which cannot cause the attention of the attacker.However,if there is dishonesty among participants,the secret cannot be recovered,which will lead to VSS-QR cannot be widely used due to its inadequate security.In this paper,we propose a visual secret sharing scheme with authentication based on QR code(VSSA-QR).Both the reconstructed secret QR code and shares can be verified whether they are forged by attackers.The above-mentioned operations conveniently are performed on low-power QR scanning devices.Not only does the proposed scheme prevent some dishonest participants or attackers from cheating,but also prevent all participants from conspiring.In addition,the payload is the QR code itself,which is higher than other schemes.Theoretical analysis and experiments prove that the proposed scheme is effective.展开更多
The QR Code is a 2 dimensional matrix code with high error correction capability. It employs RS codes to generate error correction codewords in encoding and recover errors and damages in decoding. This paper presents ...The QR Code is a 2 dimensional matrix code with high error correction capability. It employs RS codes to generate error correction codewords in encoding and recover errors and damages in decoding. This paper presents several QR Code’s virtues, analyzes RS decoding algorithm and gives a software flow chart of decoding the QR Code with RS decoding algorithm.展开更多
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University Jeddah,under grant no.(GPIP:1168-611-2024)The authors acknowledge the DSR for financial and technical support.
文摘QR codes are widely used in applications such as information sharing,advertising,and digital payments.However,their growing adoption has made them attractive targets for malicious activities,including malware distribution and phishing attacks.Traditional detection approaches rely on URL analysis or image-based feature extraction,whichmay introduce significant computational overhead and limit real-time applicability,and their performance often depends on the quality of extracted features.Previous studies in malicious detection do not fully focus on QR code securitywhen combining convolutional neural networks(CNNs)with recurrent neural networks(RNNs).This research proposes a deep learning model that integrates AlexNet for feature extraction,principal component analysis(PCA)for dimensionality reduction,and RNNs to detect malicious activity in QR code images.The proposed model achieves both efficiency and accuracy by transforming image data into a compact one-dimensional sequence.Experimental results,including five-fold cross-validation,demonstrate that the model using gated recurrent units(GRU)achieved an accuracy of 99.81%on the first dataset and 99.59%in the second dataset with a computation time of only 7.433 ms per sample.A real-time prototype was also developed to demonstrate deployment feasibility.These results highlight the potential of the proposed approach for practical,real-time QR code threat detection.
基金This work was supported in part by the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology under Grant 2016r055in part by the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions.
文摘With the rise of the Internet of Things(IoT),various devices in life and industry are closely linked.Because of its high payload,stable error correction capability,and convenience in reading and writing,Quick Response(QR)code has been widely researched in IoT.However,the security of privacy data in IoT is also a very important issue.At the same time,because IoT is developing towards low-power devices in order to be applied to more fields,the technology protecting the security of private needs to have the characteristics of low computational complexity.Visual Secret Sharing(VSS),with its features of safety and low computational cost,can fully meet the requirements of communication security in IoT.Therefore,a VSS scheme with QR code(VSS-QR)was proposed and has been applied to some extent.In VSS-QR,the secret is shared into a series of shares.These shares are usually common QR codes,which cannot cause the attention of the attacker.However,if there is dishonesty among participants,the secret cannot be recovered,which will lead to VSS-QR cannot be widely used due to its inadequate security.In this paper,we propose a visual secret sharing scheme with authentication based on QR code(VSSA-QR).Both the reconstructed secret QR code and shares can be verified whether they are forged by attackers.The above-mentioned operations conveniently are performed on low-power QR scanning devices.Not only does the proposed scheme prevent some dishonest participants or attackers from cheating,but also prevent all participants from conspiring.In addition,the payload is the QR code itself,which is higher than other schemes.Theoretical analysis and experiments prove that the proposed scheme is effective.
文摘The QR Code is a 2 dimensional matrix code with high error correction capability. It employs RS codes to generate error correction codewords in encoding and recover errors and damages in decoding. This paper presents several QR Code’s virtues, analyzes RS decoding algorithm and gives a software flow chart of decoding the QR Code with RS decoding algorithm.
