Bots are automated programs that run on a website or mobile app to complete tasks, such as search engines and digital assistants (Siri, Alexa). Many bots are necessary and welcome, providing valuable services to users, helping improve site performance, or collecting information for analytics purposes. But other bots, which are often malicious in nature, can be used to steal data, manipulate advertising campaigns, or launch DDoS attacks. Detecting and mitigating bot traffic is essential for preserving site performance, accuracy of analytics, and user experience.

Bot Detection Engine for Managing Enterprise-Level Traffic

Bot detection is the process of identifying and filtering non-human traffic to a website or mobile application. Specialized solutions combine multiple methods to ensure robust and accurate detection. They use CAPTCHAs, behavioral analysis, device fingerprinting, IP reputation, and more to identify bots in real time and mitigate their impact. They provide a clear explanation of risk and flexible mitigation techniques, such as challenging, blocking, or dropping traffic. And they work in tandem with caching strategies to maintain speed and performance even in the face of high volumes of bot activity.

A bot detection engine for enterprise traffic must be able to detect both good and bad bots, based on the specific needs of an organization. This includes determining whether the bot is used for ad fraud, click fraud, scraping, data collection, or unauthorized web crawlers. Other methods that can help identify bots include combining traffic from different devices, monitoring server logs, and using SIEM tools like Splunk or Datadog to detect unusual patterns. Rate limiting can also help prevent excessive scraping or brute force login attempts by allowing a limited number of requests in a given timeframe.