Internet Scan Source Identification: A Survey

Recently, Internet scanning activities have increased significantly, while the purposes and impacts of these scans have grown increasingly complex. Organizations dedicated to enhancing Internet security, as well as malicious ones, both conduct frequent and systematic scans across the entire IPv4 address space and partial IPv6 address space. In this context, the scan source identification, on which scan intelligence relies, is crucial as it supports in-depth analysis of the scanning behavior of organizations and helps uncover the real identity and size of potential attack organizations. In this article, we provide an extensive survey on Internet scan source identification. We summarize the common methodology and propose a taxonomy for classification. Based on this taxonomy, we outline the current state of Internet scan source identification research. Furthermore, we identify existing challenges and suggest future directions in this field.

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Publication Details

Journal
IEEE Network
Published
2025-05-27
DOI
https://doi.org/10.1109/mnet.2025.3574126
Citations
1
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
1.49

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article

Internet Scan Source Identification: A Survey

Sai Zhang, Enhuan Dong, Xiaoming Fu, Jiahai Yang et al.
1 citations
IEEE Network
Advanced Malware Detection Techniques
1.49
article

Internet Scan Source Identification: A Survey

Sai Zhang, Enhuan Dong, Xiaoming Fu, Jiahai Yang, Shenao Li, Hui Zhang, Zhiliang Wang, Zimu Li, Jie Fang, Xin He, Zeyuan Guo
article en
1 citations

Abstract

Recently, Internet scanning activities have increased significantly, while the purposes and impacts of these scans have grown increasingly complex. Organizations dedicated to enhancing Internet security, as well as malicious ones, both conduct frequent and systematic scans across the entire IPv4 address space and partial IPv6 address space. In this context, the scan source identification, on which scan intelligence relies, is crucial as it supports in-depth analysis of the scanning behavior of organizations and helps uncover the real identity and size of potential attack organizations. In this article, we provide an extensive survey on Internet scan source identification. We summarize the common methodology and propose a taxonomy for classification. Based on this taxonomy, we outline the current state of Internet scan source identification research. Furthermore, we identify existing challenges and suggest future directions in this field.

IEEE NetworkVol. 40(1)
Beijing University of Posts and Telecommunications (CN), University of Göttingen (DE), Tsinghua University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 19%
Advanced Malware Detection Techniques
1.49
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