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

Wahsheh, Heider A.; Al-Zahrani, Mohammed S.

doi:10.15837/ijccc.2021.3.4186

Cited by 10 publications

(3 citation statements)

References 14 publications

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“…One of the characteristics that are most frequently used for this filtering is genre [10]. This paper focused on a neural network based personalized music recommendation system that was created based on research on personalized music recommendation systems that solely use tag information [11] [12].…”

Section: Related Workmentioning

confidence: 99%

Emotion-Based Music Movie and TV Series Recommendation System Using Deep Learning Algorithm

Deepa¹,

Vijayalakshmi²,

Shanmathi³

et al. 2023

ACE

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It can be challenging to decide which music or movies to listen to from a huge number of options. The major purpose of our music and movie recommendation system is to provide clients with selections that fit their tastes. An assessment of a user's facial expression may provide insight into their current emotional or mental state. More than 60% of users anticipate that the number of songs in their music collection will grow to the point where they will be unable to find the song they need to play at some point in the future. It is feasible to assist a user in picking which music or movie to listen to or watch, by building a suggestion system. The face of the user is detected using the webcam. The snapshot of the user is taken based on their mood or feeling. It recognizes six facial expressions: angry, sad, fearful, joyful, surprised, and neutral. Based on the expression classification, the users are given three categories of recommendation as movies, music, or series based on their feelings. Seven different human facial expressions are classified using the Convolutional Neural Network (CNN) model. The Haar Cascade is an Object Detection Algorithm for recognizing faces in images and real-time video.

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Section: Related Workmentioning

confidence: 99%

Emotion-Based Music Movie and TV Series Recommendation System Using Deep Learning Algorithm

Deepa¹,

Vijayalakshmi²,

Shanmathi³

et al. 2023

ACE

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“…The strength of each methodology, its weakness and general research gaps identified. According to [8] 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.…”

Section: Sql Injection Attackmentioning

confidence: 99%

Software As Service Attack Detection and Prevention using Manipulated QR Code

Sahay¹

2023

cienc.eng.

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A sort of software service delivery paradigm known as "software as a service" (SaaS) includes a wide variety of commercial possibilities and problems. Despite being drawn to SaaS by its advantages, users and service providers are reluctant to incorporate their businesses into it because of security concerns. This article emphasizes the usefulness and adaptability of SaaS in a variety of situations, such as software defined networking, cloud computing, mobile cloud computing, and the Internet of Things. The examination of SaaS security issues, including data security, application security, and SaaS deployment security, is then started. Potential solutions or strategies that may be used in conjunction with one another are then offered for a secure SaaS platform. The SQL injection attack is the SaaS application's most dangerous vulnerability. This might result in sensitive and important data loss. (e.g., financial, personal). Through these kinds of assaults, attackers might steal sensitive information that is crucial to a business or organization, which has a detrimental effect on both physical (like data) and intangible (like reputation) assets. This research aims to investigate the viability of using machine learning techniques for application-level SQL injection detection. Various dangerous and benign payloads were utilized to train the classifiers employed in the testing methodologies. They detect if a payload includes malicious code when given one. This study aims to identify harmful activities in a Software as a Service (SaaS) environment based on the cloud. The anti-phishing advice for this technique, which is known as a secure QR code, includes a thorough analysis of the most current research on the usability and security of QR codes. The most important use cases and accompanying attack paths were identified. To do this, we conducted a comprehensive literature study. Social engineering, or phishing, is the fraud that exploits QR codes as an attack vector most often covered in the media. The usage of QR codes on smartphones has spread from auto production plants.

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“…Personal data can be associated with the QR codes on the patients' wristbands [15,16]. Healthcare services can use a QR code scanner application on their smartphone to access patient information, medication, and medical reports [17][18][19][20]. QR codes enable high-speed component scanning in factories [21].…”

Section: Introductionmentioning

confidence: 99%

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

Al-Zahrani

Wahsheh

Alsaade

2021

Security and Communication Networks

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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%.

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

Cited by 10 publications

References 14 publications

Emotion-Based Music Movie and TV Series Recommendation System Using Deep Learning Algorithm

Emotion-Based Music Movie and TV Series Recommendation System Using Deep Learning Algorithm

Software As Service Attack Detection and Prevention using Manipulated QR Code

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

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