Overview

Last update:2024-06-13 19:18:20

With the popularization of the Internet and the acceleration of digitization, Bot traffic has become an indispensable part of current network traffic. Automation tools not only facilitate people’s lives, but also pose huge challenges to network security. According to the latest research data, the proportion of global bot traffic to internet traffic has exceeded 50%, with the majority coming from bad bots.

The composition of Bot traffic is very mixed, and not all Bot traffic is expected or disliked by enterprises. Good bots are mainly used to facilitate people’s lives and work, such as search engines, website monitoring, etc; bad bots mainly manifest as disrupting the security and stability of the network, such as CC attacks, database collisions, malicious scanning, automated ticket grabbing, etc. Especially in fields such as finance, e-commerce, and social media, bad bot attacks are the most widespread.

We need to release good bots that are beneficial to us, and at the same time, we need to alleviate bad bots to avoid the website from facing the following difficulties:

  • Batch vulnerability scanning and exploitation (especially 0day vulnerabilities), resulting in rapid discovery and exploitation of website vulnerabilities;
  • Automated database collisions, brute force cracking, etc., leading to the leakage of enterprise account and user information, resulting in reputation losses;
  • Continuous high-frequency automated access leads to a significant occupancy of the source station bandwidth and computing resources, increasing the operational costs of the enterprise;
  • Automated flash sales, advertising fraud, etc. have led to a decrease in the ROI of corporate marketing activities, damage to corporate reputation, and an impact on user experience.

Bot Management mainly includes the following detection policies:

Policy Description Applicable Scenarios
Basic Detection Identify bot traffic based on known bot intelligence, UA features, and customer defined bot features. Suitable for websites that do not accept invasive solutions such as embedded JS SDK and APP SDK, but hope to manage simple bot traffic.
Client-based Detection Proactively identify bot traffic based on specific client scenarios, including but not limited to embedding JS SDK in HTML pages, integrating APP SDK on the APP side, and other means. Suitable for websites that want to enhance bot recognition ability and combat complex Bot traffic.
Workflow Detection Based on the logic of legitimate user access behavior, customize rules to identify bot traffic that does not meet the expected logic. Suitable for websites that want to finely manage bot traffic.
Advanced Detection By using big data analysis and machine learning techniques to dynamically model access behavior, simple bots, complex bots, and advanced persistent threat bots (APBs) can be quickly discovered. Suitable for websites that are experiencing a large amount of complex bot traffic and advanced ongoing threat bot traffic.
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