Poster: Automatic Network Protocol Fingerprint Discovery with Difference-Guided Fuzzing

Network protocol fingerprinting is a critical technique for identifying various implementations of network protocols, which is essential for vulnerability assessment and security management. However, current fingerprinting methods such as Nmap still heavily rely on manual probe crafting, requiring experts with domain knowledge and leading to inefficiencies and potential oversights. This paper introduces pFuzz, an automatic network protocol fingerprint discovery system utilizing difference-guided fuzzing, to address the challenge of the vast search space inherent in fingerprinting. We propose a difference tree to model the nested recursive condition structure of network protocols and a packet oracle map to capture and utilize multifield relationships revealed by value co-occurrence. Our evaluation of pFuzz on the widely used TCP/IP protocol demonstrates its effectiveness and efficiency on discovering fingerprints.

Authors

Institutions

Publication Details

Published
2024-10-28
DOI
https://doi.org/10.1109/icnp61940.2024.10858554
Citations
1
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Poster: Automatic Network Protocol Fingerprint Discovery with Difference-Guided Fuzzing

Xinda Wang, Yuxi Zhu, Jiahao Cao, Renjie Xie et al.
1 citations
Biometric Identification and Security
0.35
article

Poster: Automatic Network Protocol Fingerprint Discovery with Difference-Guided Fuzzing

Xinda Wang, Yuxi Zhu, Jiahao Cao, Renjie Xie, Jianping Wu, Mingwei Xu, Hanyi Peng
article en
1 citations

Abstract

Network protocol fingerprinting is a critical technique for identifying various implementations of network protocols, which is essential for vulnerability assessment and security management. However, current fingerprinting methods such as Nmap still heavily rely on manual probe crafting, requiring experts with domain knowledge and leading to inefficiencies and potential oversights. This paper introduces pFuzz, an automatic network protocol fingerprint discovery system utilizing difference-guided fuzzing, to address the challenge of the vast search space inherent in fingerprinting. We propose a difference tree to model the nested recursive condition structure of network protocols and a packet oracle map to capture and utilize multifield relationships revealed by value co-occurrence. Our evaluation of pFuzz on the widely used TCP/IP protocol demonstrates its effectiveness and efficiency on discovering fingerprints.

The University of Texas at Dallas (US), Tsinghua University (CN)
Openalex Percentile: Top 39%
Biometric Identification and Security
0.35
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.