DDoS Preventer Analyzing Request Characteristics
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Solution Overview
Problem
Conventional methods for detecting and preventing Distributed Denial of Service (DDOS) attacks are ineffective when sophisticated attackers spoof multiple IP addresses or devices, as they rely solely on tracking the number of requests, failing to distinguish between legitimate and fake requests, leading to server overload and unresponsiveness.
Innovation Solution
Implementing a DDOS attack preventer that analyzes characteristics of each request, such as data patterns, input generation, and device characteristics, to differentiate between human-generated and machine-generated requests, thereby rejecting fake requests and ensuring legitimate ones are serviced.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional IP address tracking is used to detect DDOS attacks, then simple request counting is easy to implement, but the system becomes vulnerable to spoofed IP addresses and cannot distinguish legitimate from fake requests
Solution Approach 1:
The system transitions from tracking a single parameter (IP address) to analyzing multiple parameters including device characteristics, request patterns, data characteristics, and behavioral metrics. This multi-parameter approach enables reliable detection of spoofed requests while maintaining implementation feasibility through systematic analysis of available data points.
Solution Approach 2:
The patent introduces an intermediary analysis layer between the request and the server that examines device characteristics and request patterns. This intermediary component evaluates multiple attributes including browser information, device identifiers, and behavioral metrics to determine request legitimacy without requiring complex server-side changes.
2Productivity
If the server responds to every received request, then all legitimate requests are serviced, but the server becomes overloaded and unresponsive during DDOS attacks
Solution Approach 1:
The system performs preliminary analysis of incoming requests before they reach the server, evaluating device characteristics and request patterns in advance. This preliminary action filters out malicious requests early in the process, ensuring that only legitimate requests are forwarded to the server, thereby maintaining server responsiveness during attack conditions.
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor request patterns and device characteristics, adjusting the filtering criteria based on observed behavior. This feedback loop enables the system to adapt to evolving attack patterns while maintaining accurate distinction between legitimate and malicious requests, preserving server productivity and responsiveness.
Data Source
AI summary
A DDOS attack preventer implements an unconventional way of detecting and preventing DDOS attacks. The attack preventer receives and analyzes requests from a particular IP address or device. The attack preventer will track various characteristics of each request (e.g., characteristics of the data in the requests, characteristics of the input used to generate the requests, and characteristics of the device used to generate the requests). The attack preventer will analyze these characteristics to determine whether the requests are human-generated or machine-generated. If the requests are human-generated, the attack preventer services the requests. If the requests are machine-generated, the attack preventer rejects the requests.