scholarly journals Secure Real-Time Artificial Intelligence System against Malicious QR Code Links

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Mohammed S. Al-Zahrani ◽  
Heider A. M. Wahsheh ◽  
Fawaz W. Alsaade
Keyword(s):  
Artificial Intelligence ◽  
Private Information ◽  
Code Generation ◽  
Qr Code ◽  
Suitable Model ◽  
Decision Tree Classifier ◽  
Data Types ◽  
Qr Codes ◽  
Detection Techniques ◽  
Tree Classifier

Recently, hackers intend to reproduce malicious links utilizing several ways to mislead users. They try to control victims’ machines or get their data remotely by gaining access to private information they use via cyberspace. QR codes are two-dimensional barcodes with the capacity to encode various data types and can be viewed by digital devices, such as smartphones. However, there is no approved protocol in QR code generation; therefore, QR codes might be exposed to several questionable attacks. QR code attacks might be perpetrated using barcodes, and there are some security countermeasures. Some of these solutions are restricted to malicious link detection techniques with knowledge of cryptographic methods. Therefore, this study aims to detect malicious links embedded in 1D (linear) and 2D (QR) codes. A cybercrime attack was proposed based on barcode counterfeiting that can be used to perform online attacks. A dataset of 100000 malicious and benign URLs was created via several resources, and their lexical features were obtained. Analyses were conducted to illustrate how different features and users deal with online barcode content. Several artificial intelligence models were implemented. A decision tree classifier was identified as the most suitable model for identifying malicious URLs. Our outcomes suggested that a secure artificial intelligence barcode scanner (BarAI) is recommended to detect malicious barcode links with an accuracy of 90.243%.

scholarly journals Animated Two-Dimensional Barcode Generation Using Optimization Algorithms – Redesign of Formulation, Operator, and Quality Evaluation

2009 ◽  
Vol 13 (3) ◽  
pp. 245-254 ◽  
Author(s):  
Satoshi Ono ◽  
◽  
Kensuke Morinaga ◽  
Shigeru Nakayama
Keyword(s):  
Code Generation ◽  
Optimization Problem ◽  
Quality Evaluation ◽  
Qr Code ◽  
Two Dimensional ◽  
Quick Response ◽  
Qr Codes ◽  
Running Head ◽  
Generation Problem ◽  
Font Color

To improve on our previously proposed but problem-plagued innovation for generating animated and illustrated Quick Response (QR) codes, this paper proposes a method which formulates the animated QR code generation problem as an optimization problem rather than as a set of still QR code decoration problems. The proposed method also uses optimization operators designed for this problem and quality evaluation to maintain natural, smooth movement. Experiments demonstrate that the proposed method can generate animated QR codes involve a maximum of eight illustrations moving inside the code which maintaining decoding feasibility and smooth illustration movement.<FONT color="red" size="3">Erratum<br /></FONT> <FONT color="red" size="2">Due to a wrong manipulation during the correction of the proofs of the above paper, the running head title (short title) was incorrect. The correct running head title should have read as "Animated Two–Dimensional Barcode Generation."</FONT>

scholarly journals A Preliminary Look at Heuristic Analysis for Assessing Artificial Intelligence Explainability

2020 ◽  
Vol 8 ◽  
pp. 61-72
Author(s):  
Kara Combs ◽  
Mary Fendley ◽  
Trevor Bihl
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Tree ◽  
Human Factors ◽  
Black Box ◽  
Decision Processes ◽  
Decision Tree Classifier ◽  
Tree Classifier ◽  
Explainable Ai ◽  
Heuristic Analysis

Artificial Intelligence and Machine Learning (AI/ML) models are increasingly criticized for their “black-box” nature. Therefore, eXplainable AI (XAI) approaches to extract human-interpretable decision processes from algorithms have been explored. However, XAI research lacks understanding of algorithmic explainability from a human factors’ perspective. This paper presents a repeatable human factors heuristic analysis for XAI with a demonstration on four decision tree classifier algorithms.

scholarly journals A Puzzle-Based Data Sharing Approach with Cheating Prevention Using QR Code

Symmetry ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1896
Author(s):  
Chwei-Shyong Tsai ◽  
Hsin-Liang Chen ◽  
Hsien-Chu Wu ◽  
Josh Jia-Ching Ying
Keyword(s):  
Data Sharing ◽  
Digital Signature ◽  
Private Information ◽  
Image Authentication ◽  
Qr Code ◽  
Potential Hazard ◽  
Qr Codes ◽  
Security Issues ◽  
Share Data ◽  
Encoding Method

The information technique has developed rapidly. The technique of QR codes is widely applied in our daily life, and the mechanism is suitable to share data. A QR code uses symmetric encryption to store and retrieve data efficiently. However, the security issues of QR codes are seldom discussed by the wider community. Moreover, if the sender wishes only the authorized participant to attain the private data which are shared, the data must be encrypted. Furthermore, we do not know who should be censured when problems arise. In view of this, to maintain the integrity and the confidentiality of information security, this paper proposed a new puzzle-based data sharing scheme to share the private information safely. Firstly, we generated the digital signature of the information, then applied the random grids algorithm to obtain the shares. Then, we disarrayed the shares which contain the information and the digital signature with a puzzle-based encoding method. Afterwards, we concealed them into the cover QR codes. With the QR code mechanism of error correction, the marked QR code remain meaningful. Finally, we could send marked QR codes via transmission. The receiver could use XOR operation to obtain the private information after solving the puzzles and verify whether it was tampered with by the digital signature. The proposed system can recover the lossless data and protect them from being divulged. To deal with the potential hazard of transmission in a public environment, there are more and more studies on data hiding and image authentication.

scholarly journals The inclusion of watermarks based on QR Code analysis

2018 ◽  
Vol 7 (2.18) ◽  
pp. 97
Author(s):  
Jumana Waleed ◽  
Sarah Saadoon Jasim ◽  
Thekra Abbas
Keyword(s):  
Digital Watermarking ◽  
Private Information ◽  
Experimental Results ◽  
Qr Code ◽  
Two Dimensional ◽  
Qr Codes ◽  
Code Analysis

With the quick arrival of high grades of acceptance, the QR Code technology is becoming more adaptable and usable every day by more and more people. Lately, the utilization of two dimensional QR codes for the powerful encoding of information with a big capacity becomes significantly growing; especially for encoding the identity. Because the identity is private information, it requires being further authenticated. This paper firstly works on analyzing the content of the QR Code and finding the unimportant locations inside it; Then, a combination of the digital watermarking concept and QR Code technology is used to substitute the founded unimportant locations by the watermark for the purpose of increasing the authenticity for the owner of the identity. The experimental results show that the inclusion of watermark bits inside the detected unimportant locations did not affect the process of decoding and retrieving information from the QR Code.  

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

2021 ◽  
Vol 16 (3) ◽  
Author(s):  
Heider A. M. Wahsheh ◽  
Mohammed S. Al-Zahrani
Keyword(s):  
Real Time ◽  
Computational Intelligence ◽  
Code Generation ◽  
Attack Detection ◽  
Detection Methods ◽  
Qr Code ◽  
Sensitive Information ◽  
Qr Codes ◽  
Intelligence System ◽  
Intelligence Models

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

scholarly journals Quick Response Code as a Communication Medium

2019 ◽  
Vol 8 (10) ◽  
pp. 4190-4192
Keyword(s):  
Qr Code ◽  
Quick Response ◽  
Data Types ◽  
Qr Codes ◽  
Digital Medium ◽  
Response Code ◽  
Plain Text ◽  
Naked Eye ◽  
Quick Response Code ◽  
Email Address

Quick Response (QR) Codes are tiny compatible printed pattern on solid surface to transfer a data from a printed medium to a digital medium. The coding information cannot be viewed by the naked eye thus the manipulation of printed pattern is very difficult. In general, QR code is printed in the two-dimension using white and block named QR code modules or data pixels. Static and Dynamic QR codes are available now a days. More than 3000 characters can be encoded over a very tiny space using QR graphics. The data are encoded by QR generator using ISO/IEC 18004:2006. Various types of data can be restored using QR codes and every QR Code contains segment devoted to informing the reader what sort of data it holds and used for coding and decoding the data easily. The most common data types of QR codes are SMS, Email address, phone number, plain text, geo location etc. Nowadays the QR codes are used in various fields. For example, it is used in the marketing and industries to provide the information about the products. In education it is used to register the information about the students in their certificates and to access the information in a website.

scholarly journals QR Code-based Learning Development: Accessing Math Game for Children Learning Enhancement

2019 ◽  
Vol 13 (11) ◽  
pp. 111 ◽  
Author(s):  
Widyasari Widyasari ◽  
Hadi Sutopo ◽  
Murniati Agustian
Keyword(s):  
Elementary School ◽  
Field Test ◽  
Mathematics Learning ◽  
Qr Code ◽  
Qr Codes ◽  
School Students ◽  
Learning Enhancement ◽  
Learning Mathematics ◽  
Learning Development ◽  
Math Game

Mathematics in elementary school is difficult to understand, boring, formal, theoretical, and book-based learning, which makes students tired of listening and paying attention. The purpose of this study is to create a learning prototype based on QR codes, especially mathematics learning in elementary schools. Using the QR code, students can access math games related to the course. This learning model could encourage students to learn mathematics. The research included seven steps in research and development named after Borg &amp; Gall, such as need assessment, plan, early product development, first test, revise early product, field test and revise product. The object of the research is QR code-based learning, and the respondents are elementary school students and teachers. After analyzing data in the first and field test, researchers found the result. QR code-based learning could support children for learning mathematics.

scholarly journals ART-UP: A Novel Method for Generating Scanning-Robust Aesthetic QR Codes

2021 ◽  
Vol 17 (1) ◽  
pp. 1-23
Author(s):  
Mingliang Xu ◽  
Qingfeng Li ◽  
Jianwei Niu ◽  
Hao Su ◽  
Xiting Liu ◽  
...  
Keyword(s):  
State Of The Art ◽  
Visual Quality ◽  
Qr Code ◽  
Quick Response ◽  
Estimation Model ◽  
Qr Codes ◽  
Excellent Performance ◽  
Novel Method ◽  
Coarse To Fine

Quick response (QR) codes are usually scanned in different environments, so they must be robust to variations in illumination, scale, coverage, and camera angles. Aesthetic QR codes improve the visual quality, but subtle changes in their appearance may cause scanning failure. In this article, a new method to generate scanning-robust aesthetic QR codes is proposed, which is based on a module-based scanning probability estimation model that can effectively balance the tradeoff between visual quality and scanning robustness. Our method locally adjusts the luminance of each module by estimating the probability of successful sampling. The approach adopts the hierarchical, coarse-to-fine strategy to enhance the visual quality of aesthetic QR codes, which sequentially generate the following three codes: a binary aesthetic QR code, a grayscale aesthetic QR code, and the final color aesthetic QR code. Our approach also can be used to create QR codes with different visual styles by adjusting some initialization parameters. User surveys and decoding experiments were adopted for evaluating our method compared with state-of-the-art algorithms, which indicates that the proposed approach has excellent performance in terms of both visual quality and scanning robustness.

scholarly journals A Framework for AI-Assisted Detection of Patent Ductus Arteriosus from Neonatal Phonocardiogram

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 169
Author(s):  
Sergi Gómez-Quintana ◽  
Christoph E. Schwarz ◽  
Ihor Shelevytsky ◽  
Victoriya Shelevytska ◽  
Oksana Semenova ◽  
...  
Keyword(s):  
Patent Ductus Arteriosus ◽  
Heart Defects ◽  
Ductus Arteriosus ◽  
Area Under The Curve ◽  
Clinical Decision ◽  
Heart Sounds ◽  
Decision Tree Classifier ◽  
Support Tool ◽  
Tree Classifier ◽  
Patent Ductus

The current diagnosis of Congenital Heart Disease (CHD) in neonates relies on echocardiography. Its limited availability requires alternative screening procedures to prioritise newborns awaiting ultrasound. The routine screening for CHD is performed using a multidimensional clinical examination including (but not limited to) auscultation and pulse oximetry. While auscultation might be subjective with some heart abnormalities not always audible it increases the ability to detect heart defects. This work aims at developing an objective clinical decision support tool based on machine learning (ML) to facilitate differentiation of sounds with signatures of Patent Ductus Arteriosus (PDA)/CHDs, in clinical settings. The heart sounds are pre-processed and segmented, followed by feature extraction. The features are fed into a boosted decision tree classifier to estimate the probability of PDA or CHDs. Several mechanisms to combine information from different auscultation points, as well as consecutive sound cycles, are presented. The system is evaluated on a large clinical dataset of heart sounds from 265 term and late-preterm newborns recorded within the first six days of life. The developed system reaches an area under the curve (AUC) of 78% at detecting CHD and 77% at detecting PDA. The obtained results for PDA detection compare favourably with the level of accuracy achieved by an experienced neonatologist when assessed on the same cohort.

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