Web Traffic Control via Dynamic Rule Generation
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Solution Overview
Problem
Existing web traffic control systems, such as firewalls, lack the ability to access and utilize supplemental user information related to a user's previous online activity, limiting their effectiveness in making informed decisions about incoming traffic and user interactions.
Innovation Solution
A system and method for web traffic control that collects information about incoming traffic, compares it to a generated ruleset based on supplemental user information, and makes decisions about how to handle each request or user interaction, with the ruleset being customizable for e-commerce platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a firewall is used to control web traffic, then basic traffic filtering is achieved, but the system cannot access supplemental user information about previous online activity
Solution Approach 1:
The patent introduces a rule generator as an intermediary component that bridges the firewall and the web application server. This rule generator collects supplemental user information, generates rules based on this information, and provides them to the firewall. This mediator enables the firewall to access user information without directly coupling the firewall to complex data collection systems, thus resolving the contradiction between information access and system complexity.
Solution Approach 2:
The system is divided into separate functional modules: the firewall handles traffic filtering, the web application server handles business logic, and the rule generator handles rule creation. This segmentation allows each component to focus on its specific function while maintaining clear interfaces, enabling the firewall to benefit from user information without becoming complex itself.
2Adaptability or versatility
If traditional firewall rules are used, then simple allow/block decisions are made, but dynamic control based on user activity patterns is not achieved
Solution Approach 1:
The rule generator automatically monitors user activity patterns, analyzes this data, and generates appropriate firewall rules without requiring manual intervention. The system serves itself by automatically adapting the ruleset based on observed behavior, providing dynamic traffic control while keeping ruleset management simple through automation.
Solution Approach 2:
The firewall rules are made dynamic through continuous monitoring of user activity by the rule generator. Rules are automatically updated based on real-time or near-real-time analysis of user behavior patterns, allowing the system to adapt to changing conditions while maintaining manageable complexity through automated rule generation rather than manual configuration.
3Reliability
If more user information is collected and processed, then better traffic control decisions are made, but processing time and system resources increase
Solution Approach 1:
The rule generator pre-generates rules based on user activity patterns before traffic needs to be filtered. By analyzing user behavior and creating rules in advance, the system prepares decision-making frameworks ahead of time, so that when actual traffic filtering is needed, decisions can be made quickly based on pre-processed information rather than analyzing raw data in real-time.
Solution Approach 2:
The system collects and processes only the most relevant user information needed for traffic control decisions, rather than analyzing all possible user data. The rule generator focuses on key behavioral patterns and metrics that have the greatest impact on traffic control accuracy, processing a selective subset of information to achieve good decision accuracy without the overhead of comprehensive data analysis.
Data Source
AI summary
A system for web traffic control is provided that is based on information related to a user's previous online activity. In one embodiment, the system is able to collect information about incoming traffic, compare the information to a generated ruleset, and make and implement a decision about how to handle each request/user interaction. In one embodiment, the ruleset is based on e-commerce rules. An e-commerce rule is a unit of decision making logic based on the user's previous online activity on the e-commerce platform, e.g. “If request is to add an item to user's cart, and if user already added something to their cart less than one second ago, then block request”. In some embodiments, the rules may be executed at the firewall and/or in a web application on the e-commerce platform. In some embodiments, one or more rules may be recommended to a merchant.