Blacknurse Attack: Model and Simulation

The BlackNurse attack is a novel low-rate Denial of Service (LDoS) threat with significant destructive potential against firewalls. We develop a BlackNurse attack model and examine its effects on session-based firewalls, focusing on session table utilization, CPU load, and network throughput. Our experiments show that even at 15 Mbit/s, BlackNurse can increase CPU load to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{9 0 \%}$</tex> and severely disrupt network traffic. We also analyze CPU load changes (0s-60s) under varying attack packet types, firewall session table capacities (1-20), and packet transmission rates (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$1 \mathrm{k} / \mathrm{s}-30 \mathrm{k} / \mathrm{s}$</tex>). These findings underscore the efficiency of the BlackNurse attack and its serious implications for firewall security, providing critical insights for optimizing firewall design and strengthening defense strategies.

Authors

Institutions

Publication Details

Published
2025-04-18
DOI
https://doi.org/10.1109/icccs65393.2025.11069528
Primary Topic
Network Packet Processing and Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Blacknurse Attack: Model and Simulation

Liang Liu, Zhijun Wu, Weiqing Yu
Network Packet Processing and Optimization
article

Blacknurse Attack: Model and Simulation

Liang Liu, Zhijun Wu, Weiqing Yu
article en

Abstract

The BlackNurse attack is a novel low-rate Denial of Service (LDoS) threat with significant destructive potential against firewalls. We develop a BlackNurse attack model and examine its effects on session-based firewalls, focusing on session table utilization, CPU load, and network throughput. Our experiments show that even at 15 Mbit/s, BlackNurse can increase CPU load to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{9 0 \%}$</tex> and severely disrupt network traffic. We also analyze CPU load changes (0s-60s) under varying attack packet types, firewall session table capacities (1-20), and packet transmission rates (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$1 \mathrm{k} / \mathrm{s}-30 \mathrm{k} / \mathrm{s}$</tex>). These findings underscore the efficiency of the BlackNurse attack and its serious implications for firewall security, providing critical insights for optimizing firewall design and strengthening defense strategies.

Civil Aviation University of China (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 83%
Network Packet Processing and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Blacknurse Attack: Model and Simulation — Liang Liu, Zhijun Wu, et al. · (2025) | TGRS Research Map | TGRS