Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

November 5, 2024


Pages


DOI

Article

Research on the traceability of attack teams based on offensive and defensive confrontation

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Authors

Libo Guo Affiliation:
Shandong Energy Group CO., LTD., Jinan, Shandong, 250000, China.
, Lin Yang Affiliation:
Shandong Energy Group CO., LTD., Jinan, Shandong, 250000, China.
, Ye Wang Affiliation:
Shandong Energy Group CO., LTD., Jinan, Shandong, 250000, China.
, Xiang Chen Affiliation:
Shandong Energy Group CO., LTD., Jinan, Shandong, 250000, China.
, Yunhe Bai Affiliation:
Yunding Technology Co., Ltd., Jinan, Shandong, 250000, China.
and Shuangshuang Hou Affiliation:
Shandong Energy Group CO., LTD., Jinan, Shandong, 250000, China.


Abstract

This paper explores how attack teams effectively counter trace-back efforts to safeguard their anonymity and security in network attack and defense confrontations. As network attacks become more prevalent and complex, attackers constantly use more covert and sophisticated methods to conduct attacks, making tracking and tracing a critical challenge in cybersecurity. The paper begins by evaluating joint attack trace-back techniques and methods, which include those based on network traffic analysis, malicious code analysis, and log auditing. Simulated experiments in natural network environments validate the effectiveness and feasibility of the proposed strategies. The research findings demonstrate that anti-tracing strategies based on offensive confrontation can effectively enhance the anonymity of attack teams and their ability to withstand trace-back attacks, offering new insights and methods for cybersecurity defense.


Keywords

Energy Industry, Cybersecurity Compliance, Level Protection, Critical Information Infrastructure, Data Security, Personal Information, Commercial Cryptography, 03D78


Citation

Guo, L., Yang, L., Wang, Y., Chen, X., Bai, Y., & Hou, S. (2024). Research on the traceability of attack teams based on offensive and defensive confrontation. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-3011

Published by: Engineering Journals

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