Reverse Proxy Bot Detection via Intermediary Analysis
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Solution Overview
Problem
Current technologies face challenges in distinguishing between legitimate user interactions and malicious bot activities in client/server computer systems, making it difficult for web server administrators to prevent unauthorized acts while allowing legitimate users to use the site as intended.
Innovation Solution
A system that employs detection tests and countermeasures to characterize client devices, using a security server computer system to select and apply appropriate countermeasures based on signals generated by client devices, including tests that identify human user input and differentiate between legitimate and bot-operated browsers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If detection tests and countermeasures are implemented to identify and block bot activities, then security of server computers is improved, but device complexity and user interaction overhead increase
Solution Approach 1:
A reverse proxy server is introduced as an intermediary component between client browsers and web servers. The reverse proxy receives requests from clients, executes detection tests to determine if the client is a bot or legitimate user, and then routes requests accordingly. This intermediary architecture isolates the complexity of detection mechanisms from both clients and origin servers, allowing security functionality to be added without significantly increasing the complexity experienced by end users or requiring modifications to existing server infrastructure.
2Measurement precision
If detection tests are performed to differentiate between legitimate users and bots, then measurement precision of client identification is improved, but loss of time in request processing increases
Solution Approach 1:
The system implements a tiered detection approach where not all clients undergo the same level of scrutiny. Legitimate users experiencing normal browsing patterns may undergo lighter or no detection, while suspicious requests or those from known bot sources trigger more comprehensive detection tests. This partial action strategy maintains high identification accuracy for problematic cases while minimizing time loss for legitimate traffic that doesn't require extensive verification.
Data Source
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AI summary
A computer system configured to improve security of server computers interacting with client computers, the system comprising: one or more processors executing instructions that cause the one or more processors to: select, from the plurality of detection tests, one or more first detection tests to be performed by a client computer; send, to the client computer, a first set of detection instructions that define the one or more first detection tests, and which when executed causes generating a first set of results that identifies a first set of characteristics of the client computer; receive the first set of results from the client computer; select one or more first countermeasures from a plurality of countermeasures based on the first set of characteristics identified in the first set of results; send, to the client computer, a first set of countermeasure instructions that define the one or more first countermeasures.