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Detail
Journal Article
네트워크 이상행위 탐지를 위한 암호트래픽 분석기술 동향
- Issue Date
- 2023-10
- Citation
- 전자통신동향분석, v.38, no.5, pp.71-80
- ISSN
- 1225-6455
- Publisher
- 한국전자통신연구원
- Language
- Korean
- Type
- Journal Article
- Abstract
- With the rapid advancement of the Internet, the use of encrypted traffic has surged in order to protect data during transmission. Simultaneously, network attacks have also begun to leverage encrypted traffic, leading to active research in the field of encrypted traffic analysis to overcome the limitations of traditional detection methods. In this paper, we provide an overview of the encrypted traffic analysis field, covering the analysis process, domains, models, evaluation methods, and research trends. Specifically, it focuses on the research trends in the field of anomaly detection in encrypted network traffic analysis. Furthermore, considerations for model development in encrypted traffic analysis are discussed, including traffic dataset composition, selection of traffic representation methods, creation of analysis models, and mitigation of AI model attacks. In the future, the volume of encrypted network traffic will continue to increase, particularly with a higher proportion of attack traffic utilizing encryption. Research on attack detection in such an environment must be consistently conducted to address these challenges.
- KSP Keywords
- Analysis Model, Analysis Process, Attack Detection, Detection Method, Encrypted traffic, Evaluation method, Network Attack, Network Traffic Analysis, Representation method, anomaly detection, model development
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
