Protocol-Aware and Adaptive DDoS Defense Framework

DDoS attacks continue to grow in both volume and complexity, increasingly exploiting protocol-layer vulnerabilities in core Internet protocols such as NTP, DNS, and HTTP/S. Traditional defense mechanisms, primarily based on static rules and signature-based filtering, have limited adaptability and struggle to handle rapidly evolving attack strategies. This research proposes a protocol-aware and adaptive DDoS defense framework where XDP/eBPF and LLMs serve as modular, complementary components that can be deployed individually or in combination, depending on the attack scenario and the specific characteristics of the target protocol. XDP/eBPF enables high-performance, lowlevel packet filtering directly at the NIC level, offering efficient, line-rate mitigation capabilities. Meanwhile, LLMs are fine-tuned on structured protocol interaction logs (e.g., query sequences, entropy shifts, and temporal patterns) to detect semantic-level anomalies beyond traditional detection thresholds. The proposed framework improves detection accuracy and supports dynamic, context-sensitive mitigation strategies, such as real-time traffic throttling and adaptive rule generation. This modular design allows the system to dynamically adapt to evolving threats in heterogeneous networks.

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Publication Details

Published
2025-06-23
DOI
https://doi.org/10.1109/netsoft64993.2025.11080537
Citations
3
Primary Topic
Distributed systems and fault tolerance
Type
article
Field-Weighted Citation Impact
4.46
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article

Protocol-Aware and Adaptive DDoS Defense Framework

Gabi Dreo Rodosek, Jihye Kim
3 citations
Distributed systems and fault tolerance
4.46
article

Protocol-Aware and Adaptive DDoS Defense Framework

Gabi Dreo Rodosek, Jihye Kim
article en
3 citations

Abstract

DDoS attacks continue to grow in both volume and complexity, increasingly exploiting protocol-layer vulnerabilities in core Internet protocols such as NTP, DNS, and HTTP/S. Traditional defense mechanisms, primarily based on static rules and signature-based filtering, have limited adaptability and struggle to handle rapidly evolving attack strategies. This research proposes a protocol-aware and adaptive DDoS defense framework where XDP/eBPF and LLMs serve as modular, complementary components that can be deployed individually or in combination, depending on the attack scenario and the specific characteristics of the target protocol. XDP/eBPF enables high-performance, lowlevel packet filtering directly at the NIC level, offering efficient, line-rate mitigation capabilities. Meanwhile, LLMs are fine-tuned on structured protocol interaction logs (e.g., query sequences, entropy shifts, and temporal patterns) to detect semantic-level anomalies beyond traditional detection thresholds. The proposed framework improves detection accuracy and supports dynamic, context-sensitive mitigation strategies, such as real-time traffic throttling and adaptive rule generation. This modular design allows the system to dynamically adapt to evolving threats in heterogeneous networks.

Universität der Bundeswehr München (DE)
Openalex Percentile: Top 5%
Distributed systems and fault tolerance
4.46
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