A Comparative Analysis of Object Detection Techniques for CAPTCHA Systems: A Comprehensive Overview

Dayanand; Wilson Jeberson; Klinsega Jeberson

A Comparative Analysis of Object Detection Techniques for CAPTCHA Systems: A Comprehensive Overview

March 2024

Vol-10, Issue-2

Paper ID: 22955

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Engineering

Keywords

CAPTCHA Object Detection Faster R-CNN SSD YOLO Cybersecurity Machine Learning Computer Vision.

Abstract

With the increasing prevalence of automated attacks on online platforms, the need for robust CAPTCHA systems has become paramount. CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) systems play a crucial role in distinguishing between human users and automated bots, thereby safeguarding online services from malicious activities. Object detection techniques have emerged as a promising approach for enhancing the security of CAPTCHA systems by accurately identifying and localizing objects within CAPTCHA challenges. This paper presents a comprehensive overview of various object detection techniques applied to CAPTCHA systems. We review and analyze state-of-the-art methods such as Faster R-CNN, SSD (Single Shot MultiBox Detector), YOLO (You Only Look Once), and others, highlighting their strengths, limitations, and applicability to CAPTCHA security. Additionally, we discuss challenges, emerging trends, and future directions in the field of object detection for CAPTCHA systems, aiming to provide valuable insights for researchers and practitioners in the cybersecurity domain

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Information

#	Name	Institute / Affiliation
1	Dayanand	Sam Higginbottom University of Agriculture Technology and Sciences Prayagraj, India
2	Wilson Jeberson	Sam Higginbottom University of Agriculture Technology and Sciences Prayagraj, India
3	Klinsega Jeberson	Sam Higginbottom University of Agriculture Technology and Sciences Prayagraj, India

How to Cite

Use the following formats to cite this article in your research.

APA Style

Dayanand, Jeberson, Wilson, & Jeberson, Klinsega (2024). A Comparative Analysis of Object Detection Techniques for CAPTCHA Systems: A Comprehensive Overview. International Journal of Advance Research and Innovative Ideas In Education, 10(2), 1578-1585.

MLA Style

Dayanand, et al. "A Comparative Analysis of Object Detection Techniques for CAPTCHA Systems: A Comprehensive Overview." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 2, 2024, pp. 1578-1585.

IEEE Style

Dayanand, Wilson Jeberson, and Klinsega Jeberson, "A Comparative Analysis of Object Detection Techniques for CAPTCHA Systems: A Comprehensive Overview," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 2, pp. 1578-1585, 2024.

Vancouver Style

Dayanand, Jeberson Wilson, Jeberson Klinsega. A Comparative Analysis of Object Detection Techniques for CAPTCHA Systems: A Comprehensive Overview. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(2):1578-1585.

Harvard Style

Dayanand, Jeberson, Wilson, & Jeberson, Klinsega (2024) 'A Comparative Analysis of Object Detection Techniques for CAPTCHA Systems: A Comprehensive Overview', International Journal of Advance Research and Innovative Ideas In Education, 10(2), pp. 1578-1585.

Chicago Style

Dayanand, Wilson Jeberson, and Klinsega Jeberson. "A Comparative Analysis of Object Detection Techniques for CAPTCHA Systems: A Comprehensive Overview." International Journal of Advance Research and Innovative Ideas In Education 10, no. 2 (2024): 1578-1585.

Turabian Style

Dayanand, Wilson Jeberson, and Klinsega Jeberson. "A Comparative Analysis of Object Detection Techniques for CAPTCHA Systems: A Comprehensive Overview." International Journal of Advance Research and Innovative Ideas In Education 10, no. 2 (2024): 1578-1585.