DDoS Defense via Transparent Server Offloading
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Solution Overview
Problem
Existing methods for defending against Distributed Denial of Service (DDoS) attacks often rely on network traffic filtering, which can lead to false positives and undetected attacks, especially with encrypted or obfuscated traffic, and do not effectively mitigate application-layer attacks.
Innovation Solution
The solution involves transparently offloading server functionality to client or third-party devices, allowing for the replication of server functions at multiple locations to manage overload situations without requiring knowledge of the content of malicious traffic, utilizing a resource provider lookup function to redirect requests to available resources and minimize server load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network traffic filtering is used to detect DDoS attacks, then detection capability is improved, but false positives increase and encrypted traffic cannot be effectively analyzed
Solution Approach 1:
The patent introduces a mediator component that sits between the client and server, performing protocol analysis and anomaly detection without requiring deep inspection of encrypted application data. This intermediary approach enables detection of DDoS patterns through behavioral analysis while avoiding the false positives associated with content-based filtering of encrypted traffic.
Solution Approach 2:
The patent replaces traditional mechanical packet filtering and content inspection with a protocol-based analysis system that examines structured protocol fields and behavioral patterns. This substitution allows effective detection of DDoS attacks through protocol compliance checking rather than relying on filtering encrypted payload content, thereby reducing false positives.
2Reliability
If rate limiting is applied to protect servers from overload, then server protection is improved, but service availability decreases
Solution Approach 1:
The patent implements dynamic rate limiting that adjusts thresholds and restrictions in real-time based on detected attack patterns and legitimate traffic characteristics. This dynamic approach allows the system to maintain high service availability during normal operation while automatically tightening restrictions when DDoS attacks are detected, thereby protecting servers without permanently reducing service availability.
Solution Approach 2:
The patent applies different rate limiting strategies to different types of traffic and protocol layers. Instead of uniform rate limiting across all traffic, the system applies localized restrictions specific to identified attack patterns while allowing legitimate traffic to pass through at normal rates, thus maintaining service availability while providing targeted protection.
3Measurement precision
If traditional DDoS detection methods are used, then known attack patterns are detected, but zero-day and application-layer attacks remain undetected
Solution Approach 1:
The patent performs preliminary protocol compliance checking and anomaly detection before traffic reaches the server, establishing baseline behavioral patterns and detecting deviations that indicate potential zero-day or application-layer attacks. This preliminary action enables the system to identify novel attack patterns that traditional signature-based methods would miss.
Solution Approach 2:
The patent implements feedback mechanisms that continuously learn from detected traffic patterns and adjust detection parameters accordingly. This feedback loop enables the system to adapt to new attack types and refine its detection capabilities over time, improving both detection accuracy and versatility against evolving threats including zero-day and application-layer attacks.
Data Source
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AI summary
A method is presented that enables a server to make use of client or third party resources. The client request data contains data about the network location of the client. The server may store this location data of each client. Before or after execution of the request, the server determines if the server is in or close to an overload situation. If the server is not in an overload situation, no further changes are needed. If the server is in or close to an overload situation, the server selects a new location in the network from the database with all client locations. The server allocates a new instance of the server function at a resource provider on (or close to) this new location. The server may select one or more clients from the database. The selected clients are transparently redirected to the offloaded server function. Subsequent requests from clients are handled by the offloaded server function. The offloaded server function employs the same functionality and thus may decide to offload a server function to another network location.