How does X-PHY® Server Defender confirm and mitigate DDoS attacks using cross-layer validation?

Modified on Fri, 6 Sep at 12:05 PM

The X-PHY® Server Defender employs anomaly detection, information sharing across layers, correlation analysis, and deep neural network (DNN) fusion to calculate a confidence score for attack confirmation and initiate mitigation measures if necessary.

Physical Parameters monitored for DDoS detection:

Signal strength
Noise level
Bit error rate (BER)
Packet loss
Jitter leading to physical layer attacks or hardware malfunctions

The X-PHY® Server Defender confirms and mitigates DDoS attacks through a process known as cross-layer validation, which encompasses several key steps:

1.	Anomaly Detection: Components at each layer of the OSI model independently monitor for anomalies using specific metrics and signatures. This includes analyzing parameters such as link utilization, signal strength, packet loss, and various traffic patterns.
2.	Information Sharing: Once anomalies are detected, the components share this information with a central analysis module, providing context from their respective layers to enhance the assessment process.
3.	Correlation & Cross-Checking: The analysis module correlates the data from across the layers, using metrics from the physical layer as a baseline to check for consistency and patterns that align with known DDoS attack characteristics.
4.	DNN Fusion: The information is then translated into numerical representations that are fed into a deep neural network (DNN). This DNN is trained to identify complex relationships and subtle attack patterns, potentially leading to determining DDoS attack vectors that may not be evident through traditional rule-based methods.
5.	Attack Confirmation: Based on the DNN's output and the cross-layer correlation, the system calculates a confidence score for the detected anomaly. If this score exceeds a predetermined threshold, it confirms the attack and initiates appropriate mitigation measures.