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|A Healthy Bot Management Strategy|
|Posted: Wed Oct 02, 2019 09:42:30 AM|
On the surface, bot detection seems simple: You want to accurately detect bad bots with a low rate of false positives (to avoid blocking legitimate human users and good bots) and a low rate of false negatives (to ensure that you’re detecting ALL bad bots). Go below the surface though, and the challenges of detection become much more complex.
There’s a good reason why analyst firm Forrester has cited attack detection as one of the major selection considerations for bot management solutions. The quality of detection determines the quality of the solution. And as attacking bots become ever more sophisticated, detection becomes ever more challenging.
To illustrate these points, consider the example of a bot attack aimed at cracking passwords. A bot management solution could apply several methodologies to detect the attack by:
A more sophisticated detection will correlate activity over time across IPs, device fingerprints, mobile device attributes and sensors, as well as other attributes, to provide comprehensive analysis for accurate attack source detection.
Here’s an overview of the basic functionality you need to mitigate — or manage — bots: