Host-Based Intrusion Detection: A Behavioral Approach Using Graph Model-Reference-Cited by-同舟云学术

Host-Based Intrusion Detection: A Behavioral Approach Using Graph Model

Published:2023 Issue: Volume: Page:1337-1346
ISSN:2367-3370
Container-title:Hybrid Intelligent Systems
language:
Short-container-title:

Author:

Cao Zechun,Stephen Huang Shou-Hsuan

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-27409-1_122

Reference20 articles.

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2. Cao, Z., Huang, S.H.S.: Detecting intruders and preventing hackers from evasion by tor circuit selection. In: 2018 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/12th IEEE International Conference On Big Data Science and Engineering (TrustCom/BigDataSE), pp. 475–480. IEEE, New York, NY (2018). https://doi.org/10.1109/TrustCom/BigDataSE.2018.00074, https://ieeexplore.ieee.org/document/8455942/

3. Chitrakar, R., Huang, C.: Selection of candidate support vectors in incremental SVM for network intrusion detection. Comput. Secur. 45, 231–241 (2014). https://doi.org/10.1016/j.cose.2014.06.006, https://linkinghub.elsevier.com/retrieve/pii/S0167404814000996

4. Government Accountability Office: DATA PROTECTION Actions Taken by Equifax and Federal Agencies in Response to the 2017 Breach. Tech. Rep. GAO Publication No. 18–559, Washington, D.C.: U.S. Government Printing Office (2018)

5. Gu, J., Lu, S.: An effective intrusion detection approach using SVM with naïve Bayes feature embedding. Comput. Secur. 103, 102158 (2021). https://doi.org/10.1016/j.cose.2020.102158, https://linkinghub.elsevier.com/retrieve/pii/S0167404820304314