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Detecting Cryptojacking Traffic Based on Network Behavior Features

  • Published:2021-12 Issue: Volume: Page:
  • ISSN:
  • Container-title:2021 IEEE Global Communications Conference (GLOBECOM)
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Author:

Hu Xiaoyan1,Shu Zhuozhuo1,Song Xiaoyi1,Cheng Guang1,Gong Jian1

Affiliation:

1. School of Cyber Science & Engineering, Southeast University,Nanjing,China,211189

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Fundamental Research Funds for the Central Universities (SEU)

Publisher

IEEE

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An optimized neural network with AdaHessian for cryptojacking attack prediction for Securing Crypto Exchange Operations of MEC applications;Journal of Cloud Computing;2024-03-18

2. Real-Time Symbolic Reasoning Framework for Cryptojacking Detection Based on Netflow-Plus Analysis;Lecture Notes in Computer Science;2024

3. Cryptojacking: Detection and Prevention Techniques;2023 9th International Conference on Smart Computing and Communications (ICSCC);2023-08-17

4. CJ-Sniffer: Measurement and Content-Agnostic Detection of Cryptojacking Traffic;25th International Symposium on Research in Attacks, Intrusions and Defenses;2022-10-26

5. Prevention of Cryptojacking Attacks in Business and FinTech Applications;Handbook of Research on Cybersecurity Issues and Challenges for Business and FinTech Applications;2022-10-21
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