The evolution of CAPTCHA
Summary
TLDRThe video script discusses the evolution of CAPTCHAs, starting with their creation by Luis Von Ahn in 2000 to combat spam bots on Yahoo. It explains how the initial success of CAPTCHAs was due to computers' poor optical character recognition, but over time, with advancements in AI, CAPTCHAs became easier for bots to solve. reCAPTCHA was introduced to digitize books and improve services like Google Maps. The script highlights the ongoing battle between bot makers and website security, with Google's reCAPTCHA version three monitoring user behavior for more accurate human-bot differentiation.
Takeaways
- 🧩 CAPTCHAs were created to distinguish humans from bots, with the first version introduced in 2000 by Luis Von Ahn to combat spam email accounts.
- 🔍 The original CAPTCHA relied on the human ability to read distorted text, which computers at the time struggled with due to poor optical character recognition (OCR) technology.
- ⏱ Luis Von Ahn was concerned about the time wasted by users typing CAPTCHAs, estimating 500,000 hours daily in solving them.
- 📚 reCAPTCHA was introduced as an innovative solution to digitize old books by using CAPTCHAs for two words, one as a control and the other from uncertain scans.
- 💡 Google acquired reCAPTCHA in 2009 and utilized it for digitizing books and archives, demonstrating its practical application beyond just security measures.
- 🤖 The rise of online services that solve CAPTCHAs for bots and the use of CAPTCHAs on certain websites to deter bots highlighted the ongoing battle between bots and website security.
- 📈 Advances in A.I. led to computers being able to solve CAPTCHAs more accurately than humans, which flipped the original purpose of CAPTCHAs and made them a challenge for humans.
- 🔒 reCAPTCHA version two introduced the 'I'm not a robot' checkbox, collecting additional data on user behavior to improve the accuracy of distinguishing humans from bots.
- 🕵️♂️ reCAPTCHA version three monitors user behavior in the background without the need for interaction, using machine learning to determine if the user is human or a bot.
- 🛑 The evolution of CAPTCHAs has been a continuous arms race, with bot makers adapting to new challenges and developing strategies to bypass security measures.
- 🌐 The internet's evolution ensures that the battle between bot makers and website security will continue, necessitating ongoing innovation in CAPTCHA technology.
Q & A
What problem did Yahoo face in 2000 that led to the creation of CAPTCHA?
-In 2000, Yahoo faced a problem where automatic bots were creating millions of free email accounts and using them to send spam.
Who developed the concept of CAPTCHA and what does it stand for?
-Luis Von Ahn, a Ph.D. student in computer science, developed the concept of CAPTCHA, which stands for Completely Automated Public Turing test to tell Computers and Humans Apart.
Why were CAPTCHAs initially successful in preventing bots?
-CAPTCHAs were initially successful because computers at the time were not proficient in optical character recognition (OCR), while humans could easily read distorted characters.
What was Luis Von Ahn's concern regarding the use of CAPTCHAs?
-Luis Von Ahn was concerned that solving CAPTCHAs was wasting a significant amount of human time and脑力, as it took an average of 10 seconds per user to type in a CAPTCHA.
How does reCAPTCHA improve upon the original CAPTCHA concept?
-reCAPTCHA improved upon CAPTCHA by using the process of solving CAPTCHAs to help digitize old books by having users type in words from scanned documents that the system was unsure about.
Why did Google purchase reCAPTCHA in 2009?
-Google purchased reCAPTCHA in 2009 to use its technology for digitizing books for Google Books and the archives of the New York Times, and later to improve Google Maps services.
What is the role of online services that solve CAPTCHAs in the context of bot activities?
-Online services that solve CAPTCHAs allow bots to bypass these tests by forwarding CAPTCHAs to human solvers, thus enabling bots to continue their activities on the internet.
How have advances in AI impacted the effectiveness of CAPTCHAs?
-Advances in AI have made it easier for computers to solve CAPTCHAs, to the point where they can solve them with higher accuracy than humans, thus undermining the purpose of CAPTCHAs to distinguish between humans and bots.
What changes were introduced in reCAPTCHA version two to better identify users?
-reCAPTCHA version two introduced a 'I'm not a robot' checkbox that, when clicked, allowed Google to collect additional data about the user's behavior and context, which was then analyzed by a machine learning model to determine if the user was human or a robot.
How does reCAPTCHA version three differ from its predecessors?
-reCAPTCHA version three does not require users to click a box or solve puzzles. Instead, it continuously monitors user behavior in the background to determine if the user is human or a robot, and can take actions such as blocking, requesting email verification, or holding for human review based on the assessment.
What is the current challenge for bot makers in relation to reCAPTCHA version three?
-The current challenge for bot makers is to develop AI systems that can mimic human behavior closely enough to fool reCAPTCHA version three's behavior monitoring system, despite its advanced capabilities.
Outlines
🤖 The Evolution of CAPTCHAs
This paragraph discusses the history and purpose of CAPTCHAs, which were initially designed to prevent bots from creating email accounts and sending spam. It introduces Luis Von Ahn, the inventor of CAPTCHA, and explains how it worked by using distorted images that were difficult for computers to read but easy for humans. The paragraph also highlights the evolution of CAPTCHAs into reCAPTCHA, which aimed to digitize old books by using user input to improve OCR technology. However, the system faced challenges as bots became more adept at solving CAPTCHAs, leading to the development of reCAPTCHA version two, which used user behavior data to determine if a user was human or a bot.
🔒 The Ongoing Battle with Bots
The second paragraph delves into the ongoing struggle between bot makers and website security measures. It describes how reCAPTCHA version three operates by monitoring user behavior in the background to distinguish between humans and bots, without the need for explicit user interaction like clicking a box or solving puzzles. The paragraph also touches on the tactics employed by bot makers to circumvent these security measures, including the use of human labor to solve CAPTCHAs and the development of AI that can mimic human errors to fool systems. The narrative concludes with the acknowledgment that this battle will continue as the internet evolves.
Mindmap
Keywords
💡CAPTCHA
💡Bots
💡Optical Character Recognition (OCR)
💡reCAPTCHA
💡Digitization
💡Google Books
💡New York Times Archives
💡Google Maps
💡A.I. (Artificial Intelligence)
💡Incognito Mode
💡reCAPTCHA v2 and v3
💡VPN (Virtual Private Network)
Highlights
CAPTCHAs were created to prevent bots from creating millions of free email accounts and sending spam, as experienced by Yahoo in 2000.
Luis Von Ahn, a Ph.D. student in computer science, invented CAPTCHA to differentiate humans from computers using distorted images of characters.
CAPTCHAs were successful due to the poor optical character recognition (OCR) capabilities of computers at the time, compared to human reading abilities.
An average of 200 million CAPTCHAs are solved daily worldwide, highlighting the scale of this human-computer interaction.
Luis Von Ahn was concerned about the 500,000 hours of human time wasted daily on solving CAPTCHAs.
reCAPTCHA was introduced to make use of the time spent solving CAPTCHAs by digitizing old books through user input.
The digitization process involves scanning documents into images and then using OCR to convert those images into text, where reCAPTCHA aids in uncertain cases.
Google acquired reCAPTCHA in 2009 and utilized it for digitizing books for Google Books and archives of the New York Times.
As OCR technology improved, reCAPTCHA began to be used to enhance Google Maps services.
CAPTCHAs faced challenges as online services emerged that solved CAPTCHAs for a fee, allowing bots to bypass them.
Some websites used CAPTCHAs copied from those used by bots to break into systems, as a form of security measure.
Advancements in AI led to computers being able to solve CAPTCHAs more accurately than humans, reversing the original purpose of CAPTCHAs.
Google's AI system could solve CAPTCHAs with 99.8% accuracy in 2014, while human accuracy dropped to 33%.
reCAPTCHA version two introduced the 'I'm not a robot' checkbox, collecting additional user data for analysis.
User behavior, such as mouse movements and screen taps, became part of the data used to determine if a user is human or a robot.
reCAPTCHA version three monitors user behavior in the background without the need for interactive puzzles, using machine learning models.
The evolution of reCAPTCHA reflects the ongoing battle between bot makers and website security measures as the internet evolves.
Transcripts
While browsing the web, we see
these checkboxes and puzzles that aske us to prove that we are not robots.
This year, even Mark
Zuckerberg took one of these tests before an interview, and he passed!
So this begs the question, can these tests even keep robots away?
Well, to find out, let's talk about CAPTCHAs.
in 2000. Yahoo
was one of the most popular email providers.
And they had a problem.
People were creating automatic bots
that were making millions of free e-mail accounts
and then using them to send around spams.
And Yahoo didn't know how to stop them.
Luis Von Ahn, that was a Ph.D
student in computer science, came up with an idea. To show
distorted images of random characters and asked people to type them in.
He called it CAPTCHA: Completely Automated
Public Turing test to tell Computers and Humans Apart.
And it was a success.
You see, back then, computers weren't that good at optical
character recognition, a.k.a OCR.
But humans, we thought to ourselves from a really young age how to read. We can read
different handwritings, in different light conditions, from different angles.
So CAPTCHA was really successful in keeping bots away.
And every day, roughly 200 million CAPTCHAs were solved around the world.
But Von Ahn wasn't that happy with the situation.
He thought to himself that it takes 10 seconds
for an average user to type in a CAPTCHA.
So roughly every day, 500000 hours of humans, brains
and lives were just wasted on typing some random, useless characters.
So a few years later, he came up with reCAPTCHA, and used it
to digitize old books.
There are two steps to digitize a document.
First is to scan the document and turn it into an image.
And the second one is to use OCR and turn the image into text.
That's where reCAPTCHA stepped in.
You see, instead of showing random characters
so the user, reCAPTCHA would ask the user to type in two words.
The first one was a control.
It was a randomly selected word that the user had to get it right
in order to pass the test.
But the second one, it was coming from scans
of old documents that the system wasn't sure about.
And after enough people typed in the same word,
the answer would get locked in and added to the archives.
Google liked the idea of reCAPTCHA and bought it in 2009.
They then use it to digitize books for Google Books
and the archives of the New York Times from 1851.
And when they ran out of those, they used it to improve Google
Maps services. But reCAPTCHA couldn't last long in keeping bots away.
First of all, there are online services that their job is just to solve CAPTCHAs.
So bots can go around the Internet and do whatever they want.
And whenever a CAPTCHA shows up, they can forward the CAPTCHA to those services.
These services hire people from low income countries and ask them
to just sit behind a computer and solve CAPTCHAs throughout the whole day.
Some people came up with a different idea.
They made some websites with some non-family friendly content.
And whenever
a user wanted to visit their website, they had to type in some CAPTCHAs.
CAPTCHAs
that were directly copied from websites that the bots were trying to break into.
But worse than all was the advance of A.I.
You see, over the years, computers got better in solving CAPTCHAs
and actually CAPTCHA
makers had to come up with harder CAPTCHAs to be ahead of the game.
But at some point, CAPTCHAs became so hard that people couldn't solve them anymore,
but computers could. In 2014, Google ran a test.
And so that their A.I.
system could solve CAPTCHAs with 99.8% accuracy.
But humans could only solve it with 33% accuracy.
So at this point, CAPTCHAs were actually punishing humans
instead of keeping bots away.
So Google released reCAPTCHA version two
and it actually shows these boxes of "I'm not a robot" to the user.
After clicking the box, Google gets some extra data
about the user, like the country and the IP of the user.
Also, some data about the user behavior, like how the user moves
the mouse before clicking the box, or maybe how the user taps the screen.
Google then gives all of this data to a machine learning model
to figure out if a user is human or a robot.
So if a user is incognito mode
or using some sort of VPN, they are more likely to fail the test.
Then Google ask to solve these puzzles to find images of traffic lights or cars.
This was working in 2014 because A.I. wasn't advanced in image recognition.
But these days, it's not that hard to train a model to solve this puzzle.
Or still it's possible to ask services online, to use human to solve the puzzles.
So in 2018, enter reCAPTCHA version three.
This time there is no box to click or a puzzle to solve.
But the website constantly monitors user behavior
from background to figure out if it's a human or a robot.
So if a user is logged into their Google account and they are normal
using the same browser, they're more likely to pass the test.
But if they are in incognito mode or use some VPN, they might fail the test.
The website can then either block them, ask them for email
verification, or keep them on hold for human review.
However, the bot makers have already taken on the new challenge.
This time, not to make A.I.s that are more accurate than humans,
but the ones that make mistakes and can fool the system.
The battle between bot makers and the websites will go on
as the internet keeps evolving.
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