Your IP address is the marker that lets other computers on the Internet know where you are. It’s a crucial piece of information that allows web applications to deliver content and services that are relevant for your location. For example, a web browser can send you a page that is written in your language or a streaming platform can show you a list of products that are available to purchase in your country.
It’s also how the system IP address bot detection you use to email a friend at work knows to send the message from your corporate network and not from your home account. Without your IP address, the email would simply bounce back and never reach its destination.
Because bots often spoof their IP addresses, they may appear to be human. As such, detecting and blocking bots is challenging. The good news is that there are many ways to improve your detection capabilities.
A good way to prevent bots is to analyze traffic patterns. Look for sudden and repeated traffic peaks in a short period of time which is typical of scanning bot behavior. Likewise, analyze the type of data being sent to detect unusual requests from bots. For example, if a large number of small files are being sent to your website or mobile app API the request may be suspicious.
The ability to identify and distinguish between real users and bots is a key element in any effective security solution. To do this, a bot management solution should collect device fingerprinting data and behavioral analytics that detect suspicious or known bot activity. It should also assess the connection details of a user to see if they are connecting through proxies, VPNs or Tor. Moreover, it should be able to recognize emulators and virtual machines that could be used by bots to conceal their identity.
One important feature is that an advanced bot management solution shouldn’t rely on JavaScript signals. This is because these can be spoofed by sophisticated bots. It should also be able to process trillions of data signals in real-time and smoothly absorb the traffic peaks associated with bot attacks.
Another useful method of identifying bots is by looking at the type of software and hardware on the client machine. For example, using a unique fingerprinting system such as Google Picasso that can detect the operating system class of a client browser and graphic hardware enables an organization to recognize and block sophisticated bots.
Finally, an IP reputation database can help in identifying bots. These databases contain records for known bots, which are typically marked as “bad.” When a company uses a bot blocklist, it blocks illegitimate or malicious IP addresses from accessing its websites and mobile apps. Using the IP reputation database helps to improve the accuracy of an organization’s bot detection capabilities and reduce false positives. It is a great complement to traditional methods such as WAFs that only use IP addresses to distinguish between real and fake traffic.