A POINT CAPTCHA SYSTEM- ENHANCED CAPTCHA USING INVISIBLE CHECKBOX

Abstract

A POINT CAPTCHA SYSTEM- ENHANCED CAPTCHA USING INVISIBLE CHECKBOX ABSTRACT The present invention relates to an advanced CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) system that improves the accuracy of distinguishing between human users and automated bots. The system utilizes a combination of visible and invisible checkboxes, timing analysis, and mouse movement tracking to identify bots based on interaction patterns that are unlikely for human users. Human seen the visible checkboxes but bot seen the both visible and invisible checkboxes. human click the visible checkboxes but bot clicks the both visible and invisible checkboxes and then bot is trapped. The invention aims to enhance security by making it difficult for automated systems to bypass the CAPTCHA, thus providing a more robust defence against malicious bots. Fig 1

Specification

Description:FORM 2

THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENTS RULES, 2003

COMPLETE SPECIFICATION
(See Section 10; rule 13)

TITLE OF THE INVENTION
A POINT CAPTCHA SYSTEM- ENHANCED CAPTCHA USING INVISIBLE CHECKBOX

APPLICANT
K.RAMAKRISHNAN COLLEGE OF ENGINEERING
NH-45, Samayapuram,
Trichy, Tamilnadu, India- 621112


The following specification particularly describes the invention and the manner in which it is to be performed.
A POINT CAPTCHA SYSTEM- ENHANCED CAPTCHA USING INVISIBLE CHECKBOX
TECHNICAL FIELD
[001] The present invention relates to the field of authentication and digital security technologies. More specifically, the present invention related to a CAPTCHA (Completely Automated Public Turing test to tell Computers and Human Apart) CAPTCHA system is differentiate between human user and
BACKGROUND
[002] Some CAPTCHAs are difficult for users to solve, leading to frustration. For example, distorted text or ambiguous images can be hard to identify and solve. Users with disabilities, such as visual impairments, can find traditional CAPTCHAs particularly challenging. Even audio CAPTCHAs can be difficult for users with hearing impairments or non-native speakers. Completing a CAPTCHA can slow down the user experience, especially if the CAPTCHA is complicated or requires multiple attempts.
[003] The added friction of solving a CAPTCHA can lead to higher abandonment rates on websites. Human users may sometimes be misidentified as bots, which can lead to frustration and a poor user experience. Conversely, some CAPTCHAs might mistakenly allow bots to pass through the CAPTCHA.
[004] bots and machine learning algorithms are becoming increasingly capable of solving CAPTCHAs, reducing their effectiveness as a security measure. There are services where humans are paid to solve CAPTCHAs, which bots can use to bypass CAPTCHA Advanced protections.
[005] Solving CAPTCHAs on mobile devices can be particularly difficult due to small screen sizes and touch inputs, further complicating the user experience. Some CAPTCHA systems, like Google's reCAPTCHA, involve collecting user data, which raises privacy concerns, especially when integrated with other tracking mechanisms. Text-based CAPTCHAs may present difficulties for users who are not fluent in the language used in the CAPTCHA.
OBJECT OF THE INVENTION
[006] By including checkboxes that are only visible to bots, you create a clever trap that bots might fall into, making it easier to identify them.
[007] Yet another object of the present invention is to Measuring the time of clicks and mouse movements can further improve the accuracy of bot detection. Bots often click faster and more consistently than humans, and their mouse movements may lack the natural variability of human actions.
[008] Yet another object of the present invention is to Visible checkboxes are straightforward for users to interact with, potentially leading to a better user experience compared to traditional CAPTCHAs that require text entry or image recognition.
[009] Yet another object of the present invention is to Type of invisible elements are used, making it adaptable to various security levels and use cases.
[010] Yet another object of the present invention is to Combining this point captcha method with other CAPTCHA mechanisms (e.g., analysing mouse movement patterns) adds layers of security without overly complicating the user experience. These and other objects and advantages of the present invention will become readily apparent from the following detailed description take in conjunction with the accompanying drawings.
SUMMARY
[011] The point captcha system planning and design is Your primary objectives are to enhance bot detection, minimize user friction, and maintain accessibility. Study existing CAPTCHA systems, especially those that use behavioural analysis or invisible elements, to identify best practices and potential pitfalls. Plan the layout of your CAPTCHA, including the placement of visible checkboxes and the logic for invisible ones. Ensure the UI is simple and user-friendly.
[012] The point captcha system's technology stack React for layout and styling. JavaScript for client-side logic, such as handling checkbox clicks, timing, and mouse movement tracking.
[013] The point captcha system, frontend developments are to create the captcha interface Design and code the visible checkboxes that users will interact with. Ensure that they are intuitive and easy to use. Implement invisible checkboxes. These should be placed in such a way that they are hidden from users but detectable by bots. You can achieve this through CSS techniques like visibility: hidden; or positioning the checkboxes off-screen. Then track user interaction, Use JavaScript to record the time it takes for the user to interact with the CAPTCHA (time between page load and checkbox click). Capture mouse movements, including patterns, speed, and pauses. This can be done by attaching event listeners to the document that track the mouse movement events. Log checkbox clicks, including which boxes are clicked (visible or invisible).
[014] Then track user interaction, Use JavaScript to record the time it takes for the user to interact with the CAPTCHA (time between page load and checkbox click). Capture mouse movements, including patterns, speed, and pauses. This can be done by attaching event listeners to the document that track the mouse move events. Log checkbox clicks, including which boxes are clicked (visible or invisible). Data processing, Receive the interaction data from the frontend (e.g., time of clicks, mouse movements). Then analysis the data to Check if any invisible checkboxes were clicked and Evaluate the timing and mouse movement data to determine if they resemble human behaviour. in point captcha, bot detection logic If an invisible checkbox is clicked, flag the interaction as bot activity. Analyse timing and movement data using thresholds (e.g., if the time to click is too fast or mouse movement is too linear, it might indicate a bot). Combine these indicators to calculate a confidence score on whether the interaction is from a bot or a human.
[015] If identified as a bot, the backend can block the request or present an additional challenge. If identified as human, allow the form submission or other intended user action.
[016] Regularly update the positioning or nature of invisible checkboxes to avoid bots adapting. Encrypt communication between the frontend and backend to prevent tampering with the CAPTCHA logic. Ensure that any collected data (e.g., timing, movements) is stored and processed securely, in compliance with privacy laws like GDPR if applicable.
[017] Test individual components (e.g., checkbox visibility, timing calculation) to ensure they work as expected. Test the entire CAPTCHA process from start to finish, including bot detection logic. Conduct usability testing with real users to ensure the CAPTCHA is not too difficult or frustrating. Simulate bot interactions to test the effectiveness of this CAPTCHA system. Deploy the CAPTCHA system on a secure server. Choose a hosting provider that supports the chosen technology stack. Implement logging and monitoring to track CAPTCHA performance and detect any suspicious activity or failures. Regularly update the CAPTCHA logic based on new bot behaviours, user feedback, and technological advancements.
[018] In point captcha, Make sure our CAPTCHA is usable by people with disabilities. For example, provide an alternative text-based or audio CAPTCHA for users who cannot interact with the visual interface. Ensure our CAPTCHA complies with relevant data protection laws, particularly if it collects and processes user interaction data. Document the code, logic, and any configuration options for future maintenance and updates. Bots evolve, so regularly update our CAPTCHA system to maintain its effectiveness. This could include changing the location of invisible elements, updating timing thresholds, or integrating new behavioural metrics. Review the CAPTCHA's effectiveness by analysing success rates, user complaints, and false positives/negatives. Make adjustments based on user feedback and observed bot activity patterns.
BRIEF DESCRIPTION OF THE DRAWINGS
[019] User loads the CAPTCHA page. time when the page loads is recorded. Invisible checkboxes are rendered but not visible to the user The user clicks on the visible checkbox. The time difference between page load and the click is recorded. Mouse movements are tracked from the moment the page loads until the form is submitted.
[020] The user submits the form. The form data (including checkbox states, click time, and mouse movements) is sent to the server. The server receives the form data.
[021] The server checks if any invisible checkboxes are checked. If an invisible checkbox is checked, the user is flagged as a bot. The server checks the recorded time difference between page load and the checkbox click. If the click time is below a predefined threshold (e.g., 500ms), the user is flagged as a bot.
[022] The server analyses the recorded mouse movements. If the movements are too consistent, too fast, or follow a linear path, the user is flagged as a bot.
[023] Based on the results of the invisible checkbox check, click timing analysis, and mouse movement analysis, the server decides whether the user is a bot or a human. The server sends a response back to the user, indicating whether they are verified as a human or flagged as a bot.
DETAILED DESCRIPTION
[024] System component for the frontend interface is the form contain visible checkboxes and invisible checkboxes where the visible checkboxes for the human user and the invisible checkboxes for the bot identification. The point CAPTCHA is rendered in the HTML but not visible in the UI by the way that they are hidden from users but detectable by bots. You can achieve this through CSS techniques like visibility: hidden; or positioning the checkboxes off-screen. and Then track user interaction, Use JavaScript to record the time it takes for the user to interact with the CAPTCHA (time between page load and checkbox click). Capture mouse movements, including patterns, speed, and pauses. This can be done by attaching event listeners to the document that track the mouse movement events. Log checkbox clicks, including which boxes are clicked (visible or invisible).
[025] This CAPTCHA UI looks simple and easy to understand like many visible checkboxes which is visible to the human users because of some HTML and CSS works. Some invisible checkbox which is only visible to bot.
[026] Backend server is receives form data upon submission. After the submission, backend server will know about the all the checkboxes , it have the information about the visible checkboxes and the invisible check boxes if the user is clicked. The process the data to determine if any invisible checkboxes were checked then we identifies as a bot , not human. By using the invisible checkboxes we can find the bot interaction efficiently than any other captcha method.
[027] The methodology of the project, upon the user loading the CAPTCHA page, the system records the load time because the bot and human have high significant difference in the load time, if the human user is load the webpage then it takes the time of 2 or more minutes on other hand bot is load to the webpage then it takes very less time then the human user, the bot takes less than a second. The point CAPTCHA initializes mouse movement tracking because the mouse movement of the human and the bot have very variation, bot have accurate straight movement without any shacking but human have more shack in there mouse movement .
[028] This CAPTCHA have the mouse movement tracking invisible checkboxes are included in the form structure but styled to be hidden from the user's view. When the user interacts with the CAPTCHA (e.g., clicking a visible checkbox), the bot clicks the both visible checkbox and invisible checkbox also. the system records the time taken since the page load and captures the click event. Once the submits the form, the backend for processing.
[029] The backend checks if any of the invisible checkboxes were clicked. if so, it identifies the interaction as bot-driven. The backend compares the recorded click time against a predefined threshold. If the interaction time is unusually fast, the system flags it as suspicious. the backend analyses the user's mouse movements. consistent or linear movement patterns indicate possible bot activity. based on the analysis of invisible checkbox interaction, timing and mouse movements, the system determines whether the user is a bot or a human. A response is generated accordingly, either allowing access or blocking the bot.
[030] The advanced over existing system by introduction invisible element and analysing user behaviour, this CAPTCHA system is more resilient to bot attacks then traditional CAPTCHA's. the system operates largely in the background, requiring minimal interaction from human users while being highly effective against bots. The system can be easily integrated into existing web platforms and adjusted to evolves with new bot behaviours.
[031] Enhancing the security of websites and web application by preventing unauthorized access from bots protection online stores from automated attacks that can manipulate prices, steal inventory, or perform fraudulent transactions ensuring the integrity of user-generated content and preventing spam or bot-generated comments on forums and social media plat forms.
[032] Calculate the click time of the user, if the click time is less than or equals to the 500ms then it will be bot as detected. if the click time is high then the 500ms then the user is the human as detected.
[033] In mouse movements, we can analyse the difference of the human and the bot. human have many mouse movement then the bot, by using this event listener, we differentiate the bot and human. Mouse movement are record the x-axis, y-axis and time of move the mouse.
[034] By using the ML program, we can generate the many CAPTCHA according to the minimum period of time , after that period is complete the CAPTCHA is regenerate to new one.
[035] The regenerated CAPTCHA , the position of the visible checkbox is change and the invisible CAPTCHA is also change in position.
[036] The regenerated CAPTCHA, the count of visible checkbox is change it may increase or decrease. the count of invisible checkbox is also increase or decrease.
[037] This point captcha have a regularly update the positioning or nature of invisible checkboxes to avoid bots adapting. Encrypt communication between the frontend and backend to prevent tampering with the CAPTCHA logic. Ensure that any collected data (e.g., timing, movements) is stored and processed securely, in compliance with privacy laws like GDPR.
[038] The point CAPTCHA Conduct usability testing with real users to ensure the CAPTCHA is not too difficult or frustrating. Simulate bot interactions to test the effectiveness of this CAPTCHA system. Deploy the CAPTCHA system on a secure server. Choose a hosting provider that supports the chosen technology stack. Implement logging and monitoring to track CAPTCHA performance and detect any suspicious activity or failures.
[039] Make sure our CAPTCHA is usable by people with disabilities. For example, provide an alternative text-based or audio CAPTCHA for users who cannot interact with the visual interface. Ensure our CAPTCHA complies with relevant data protection laws, particularly if it collects and processes user interaction data.
[025] Bots evolve, so regularly update our CAPTCHA system to maintain its effectiveness. This could include changing the location of invisible elements, updating timing thresholds, or integrating new behavioural metrics.
, Claims:CLAIM
WE CLAIM,
1. A point CAPTCHA system using invisible checkboxes comprising:
a point CAPTCHA contains visible checkbox and invisible checkboxes, by clicking all the checkboxes to authentication and to bypass the CAPTCHA;
A visible checkbox for user interaction, only seen by the human;
atleast one Invisible checkbox detectable by automated bots but not visible to the human due to colour different or some CSS tools;
A timing mechanism to record the interaction time between the page load and the checkbox click;
A mouse movement tracker to record and analyse the user's cursor behaviour and mouse click pattern;
A backend server configured to receive form data, analyse it for bot detection, and respond based on the analysis results; and,
An AI algorithm, logical regression are used to analysis the result.
2. The CAPTCHA system as claimed in claim 1, wherein the invisible checkbox detection is used to identify automatic bot interactions.
3. The CAPTCHA system as claimed in claim 1, human clicks only the visible checkboxes to authenticate.
4. The CAPTCHA system as claimed in claim 1, bot clicks the both visible and invisible checkboxes.
5. The CAPTCHA system as claimed in claim 1, wherein the timing analysis identifies interactions that faster then a predefined human interaction threshold.
6. The CAPTCHA system as claimed in claim 1, wherein the mouse movement analysis identifies unnatural or overly consistent movement patterns that are indicative of bot activity.
7. The CAPTCHA system as claimed in claim 1, wherein the backend server is configured to provide a response indicating whether the user is verified as human or flagged as a bot.
8. The CAPTCHA system as claimed in claim 1, wherein the logical regression ML algorithm can be used to analyse the behaviour of human and bot , and give a score based on the behaviour.

Documents