The world is forecasted to produce, capture, copy, and consume about 181 zettabytes of data in 2025, a huge jump from just 15.5 zettabytes in 2015. In fact, big data analytics is expected to generate a revenue of $68 billion by 2025.
Most of this data comes from online sources and is used for various reasons, from lead generation and news monitoring to price intelligence and market research. Web scraping is the process of accessing online data through automated scrapers.
However, not every website owner is open to the idea of others peeking into their content. That’s why modern websites employ a host of methods to detect and ban scrapers. We’ll talk about them in detail below.
Reasons Websites Use Anti-Bot Systems
There are several reasons websites have anti-bot systems in place. Some of them are:
- Data Protection: Every website spends a ton of time and resources to generate and maintain its content. It makes sense why the owners don’t want an external party to enjoy all this hard work for free. Besides, web scrapers also extract user-generated content, product listings, pricing information, and copyrighted material, which could result in a negative reputation for the website.
- Website Performance: The more requests a web scraper sends to a website, the slower the site gets. Web scraping, when conducted on a large scale, can put a lot of strain on a website. It affects user experience and also increases operational costs for website owners.
- Security Risks: Not everyone using a web scraper is doing it with good intentions. Malicious agents may use web scrapers to look for vulnerabilities in a site. Anti-bot systems can help reduce the risk of unauthorized access and data breaches.
- API Use Preservation: Websites that use APIs (Application Programming Interfaces) allow controlled data access. However, web scrapers bypass this feature, resulting in service disruption for legitimate users who actually pay for this service.
Methods Websites Use To Detect Web Scrapers
Scraper detection mechanisms have advanced quite a bit in recent times due to the spike in web scraping activity. Many websites use the following techniques to detect web scrapers.
- User-Agent Analysis: Web scrapers usually have user-agent strings in their web requests for self-identification. An anti-bot system can analyze these strings to detect inorganic or non-standard user agents.
- Honeypot Traps: A honeypot is a page or link that a regular human user cannot see. However, a web scraper can see and scrape it. If a certain IP seems to be scraping all the honeytraps in a website, the server can quickly flag it as a bot.
- Signature Signals: A signature signal is a series of data points that could indicate the presence of a bot. Some of these include browser fingerprints and TLS fingerprints. For instance, in HTTP fingerprinting, the website server scans basic browser information, such as request headers, gzip compression, browser encoding, and user agent, to detect a bot.
- Behaviour Patterns: A human user cannot send a thousand requests in just two minutes. But a bot can, and an anti-bot system recognizes this difference. Many anti-bot mechanisms simply detect behavioural patterns and flag anything too fishy or inorganic.
How To Bypass Anti-Bot Detection Systems
A simple way to bypass these systems is not to alert them in the first place. How do you do that? By limiting your request frequency. Space your requests at longer intervals to avoid suspicion.
However, this might not be effective in all cases. The second line of defence against bans comes in the form of proxies.
These intermediaries will keep your IP address hidden from the target website, preventing IP blocks. Most proxy server providers offer IP rotation. So, you can use hundreds of IP addresses, minimizing the risk of being perceived as a bot.
While proxies are definitely helpful, they’re not as ban-proof as Oxylabs’ Web Unblocker, an AI and ML-powered proxy solution that lets you scrape the web without worrying about CAPTCHAs or other anti-bot measures.
The main appeal of Web Unblocker is in its machine-learning algorithm. Since the algorithm manages proxies and conducts response recognition, you don’t have to select the optimal browser attributes for every scraping task yourself.
The algorithm determines which browser configurations work best and uses it for your web scraping activities. But what if an attempt fails? That’s not a problem. Web Unblocker initiates another attempt without any manual intervention.
Even better, it does so with different combinations of browser perimeters to reduce the risk of another failure.
Conclusion
As anti-bot systems get better, web scraping will get more complicated. IP bans and blocks can result in financial loss and wasted time, often delaying business and research activities.
Integrating Web Unblocker into your existing code is the way to go if you want to bypass IP bans and CAPTCHAs. Powered by machine learning and artificial intelligence, the system is designed to switch to best-performing attributes for each web scraping task.
Read Also:
