Practicality analysis of utilizing text-based CAPTCHA vs. graphic-based CAPTCHA authentication

Abstract

CAPTCHA as “Completely Automated Public Turing test to tell Computers and Humans Apart” is becoming an essential tool to help reduce many automated security authentication attacks. This research focused on studying differences running text-based CAPTCHA vs. graphical-based CAPTCHA in a utilization applicable dominant practicality manner. The ordinary text-based CAPTCHA works simple to prevent automated submissions as thought of being relatively easy to exploit. On the other hand, graphic-based CAPTCHA can be more preferred from users side, but can be providing some complexities making clear tradeoff analysis need between its usability and security. Even though graphic-based CAPTCHA has been generally considered as improvement of text-based CAPTCHA with respect to security, its usage is still not common, raising a practicality gap needing some search for comparing the two methods side by side comprehensively involving usability applicability and cultural preference beside security. In this regard, this research contributes towards filling the gap in knowledge running thorough local experimentations for finding different CAPTCHA performance tradeoffs in terms of real statistical humanoid possibilities of practicality easiness, repetition secrecy, and configuration solving timing, that can be used as basis for conducting further techno improvement human-oriented research.

Deciphering Themes and Trajectories: A Bibliometric Study on Learning Design & Technology over Four Decades

“…These advanced deep learning techniques are mainly used in image-based CAPTCHA generation models, focusing on image generation. According to the study, image-based CAPTCHA is more popular than text-based CAPTCHA [5] . Thus, besides security measurement, the user-friendly performance is also considered in most of the research [24,33,[43][44][45][46][47][48] .…”

“…This indicates the tendency to balance the security and user-friendly in CAPTCHA generation process. However, there still exists issues with identifying an appropriate balance between effectively avoiding attacks and maintaining user-friendliness [5,49,50] .…”

“…In CAPTCHA generation area, traditional image processing methods include add noise, rotation and geographic transformer to the CAPTCHA images [5,6] . However, CAPTCHA that is generated by classical image processing cannot defend against the attack of advanced deep learning algorithms.…”

“…Research results show that image or image-text CAPTCHA (graphic-based) can protect CAPTCHA and improve its robustness. Researchers [5] found that users prefer graphical-based CAPTCHA over text-based CAPTCHAs, despite their complexity. Furthermore, numerous authors employ advanced techniques for synthesizing or generating CAPTCHA, yet there is absence of common benchmarks and the distinctive designs of various CAPTCHA schemes.…”

Unweighted Voting Method to Detect Sinkhole Attack in RPL-Based Internet of Things Networks

“…This type of attack can deplete the energy resources of surrounding nodes, creating energy gaps within Wireless Sensor Networks (WSNs) [3]. Among various routing attacks, the sinkhole attack falls under the Denial of Service (DoS) category and poses a severe threat to IoT environments [20]. Its destructive impact is further amplified when combined with other attacks, potentially causing significant damage.…”