Adaptive machine learning‐based alarm reduction via edge computing for distributed intrusion detection systems-Reference-Cited by-同舟云学术

Adaptive machine learning‐based alarm reduction via edge computing for distributed intrusion detection systems

Published:2019-01-10 Issue:19 Volume:31 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Wang Yu¹^ORCID,Meng Weizhi²^ORCID,Li Wenjuan²³^ORCID,Liu Zhe⁴,Liu Yang¹,Xue Hanxiao¹

Affiliation:

1. School of Computer ScienceGuangzhou University Guangzhou China

2. Department of Applied Mathematics and Computer ScienceTechnical University of Denmark Kongens Lyngby Denmark

3. Department of Computer ScienceCity University of Hong Kong Kowloon Tong Hong Kong

4. Interdisciplinary Centre for Security, Reliability and TrustUniversity of Luxembourg Luxembourg City Luxembourg

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.5101

Reference62 articles.

1. Guide to Intrusion Detection and Prevention Systems (IDPS)

2. An Immune-inspired Adaptive Automated Intrusion Response System Model

3. State transition analysis: a rule-based intrusion detection approach

4. GhoshAK WankenJ CharronF.Detecting anomalous and unknown intrusions against programs. In: Proceedings of the 14th Annual Computer Security Applications Conference;1998;Phoenix AZ.

5. TombiniE DebarH MéL DucasséM.A serial combination of anomaly and misuse IDSes applied to HTTP traffic. Paper presented at: 20th Annual Computer Security Applications Conference;2004;Tucson AZ.

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