Software As Service Attack Detection and Prevention for Deceitful QR code

Authors

  • Manushree Sahay Bharati Vidyapeeth (Deemed to be University) College of engineering Pune.
  • Sandeep Vanjale Bharati Vidyapeeth (Deemed to be University) College of Engineering,Pune-43.
  • Madhavi Mane Assistant Professor, Dept. of Computer Engineering, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune

Keywords:

Security analysis, Access control, Emotion interaction, identity authentication, social robot

Abstract

The economic benefits and cons of using SaaS (software as a service) are not without debate. The security risks associated with SaaS prevent some consumers and service providers from using it. Using examples including software-defined networking, cloud computing, mobile cloud computing, and the Internet of Things, this article highlights the flexibility and use of SaaS in a number of contexts. Data security, application security, and SaaS deployment security are only some of the SaaS security challenges that will be investigated next. After that, options on how to make a SaaS platform more secure are presented, including how they may work together. The most severe security hole in the SaaS program is the SQL injection attack. The loss of private or crucial information might arise from this. (e.g., financial, personal). Both material (such as data) and intangible (such as reputation) assets might be jeopardized by these types of attacks on a company or organization's sensitive information. The goal of this study is to see whether it is possible to use machine learning methods to identify SQL injections in applications. To prepare the classifiers used in the evaluation procedures, both malicious and safe payloads were used. When given a payload, they can determine whether it contains malicious code. The purpose of this research is to identify malicious actions in a cloud-based SaaS setting. The latest studies on the practicality and safety of QR codes are thoroughly analyzed in the anti-phishing recommendations for this method, known as a secure QR code. We found the most common use cases and the most common attack vectors to exploit them. We did a massive literature search to accomplish this. The most often reported kind of fraud using QR codes as an attack vector is social engineering, sometimes known as phishing. QR codes on cellphones have exploded in popularity in assembly lines for automobiles.

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References

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Published

10.11.2023

How to Cite

Sahay, M. ., Vanjale, S. ., & Mane, M. . (2023). Software As Service Attack Detection and Prevention for Deceitful QR code. International Journal of Intelligent Systems and Applications in Engineering, 12(4s), 454–462. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3806

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Section

Research Article

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