Distributed Web Application Firewall AI Security
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Solution Overview
Problem
Web applications face vulnerabilities to hacker attacks, including injection flaws, cross-site scripting, and phishing, due to the stateless nature of HTTP and the limitations of HTTPS in preventing man-in-the-middle attacks, which existing security measures fail to adequately address.
Innovation Solution
A Web Application Firewall (WAF) utilizing AI techniques and a distributed architecture to analyze HTTP requests, apply customizable rules, and learn from denied requests to block harmful traffic, sharing knowledge across instances to enhance attack recognition and protection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional security measures (HTTPS, stateless HTTP) are used, then basic communication is maintained, but security against hacker attacks (injection flaws, cross-site scripting, phishing) is insufficient
Solution Approach 1:
The patent introduces a Web Application Firewall (WAF) as an intermediary component between clients and web applications. The WAF intercepts and analyzes HTTP requests, applying security rules and AI-based detection to block malicious traffic before it reaches the target application, thereby resolving the security insufficiency of traditional HTTPS and stateless HTTP mechanisms
Solution Approach 2:
The system performs preliminary security analysis and rule application on HTTP requests before they are processed by the web application. By pre-filtering and blocking suspicious traffic at the WAF layer, the system prevents potential attacks from reaching the vulnerable application, addressing the reactive nature of traditional security measures
2Reliability
If a WAF with AI techniques and distributed architecture is implemented, then attack recognition and protection are enhanced, but system complexity increases
Solution Approach 1:
The patent implements a distributed WAF architecture where multiple WAF instances are deployed across different locations. Each instance independently analyzes traffic for its protected application, and results are shared through a centralized coordination mechanism. This segmentation allows the system to achieve high attack recognition accuracy through collaborative learning while managing complexity through modular, distributed deployment
Solution Approach 2:
The WAF system incorporates multiple functionality including rule-based filtering, AI-driven anomaly detection, collaborative learning across instances, and centralized coordination. By consolidating these diverse security functions into a single multi-functional platform, the system enhances attack recognition capabilities while avoiding the complexity of managing separate specialized security tools
Data Source
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AI summary
A method for protecting a Web application running on a first local Web Server from hacker attacks, said Web Server being connectable to at least one client, the method comprising the following steps: - providing a plurality of preset rules on said Server, which correspond to specific characteristics of HTTP requests; - receiving an HTTP request on said server from the client, said HTTP request comprising a plurality of characteristics; - analyzing said characteristcs of said received HTTP request in accordance with said rules provided on said server; - rejecting said HTTP request, if said rules identify said HTTP request as harmful request; - accepting said HTTP request, if said rules identify said HTTP request as trustable request; - classifying said HTTP request as doubtful request, if said rules identify said request neither as harmful request nor as trustable request; - evaluating the characteristics of said doubtful request; - generating a learned rule on basis of the evaluation.