NetTiSA: Extended IP Flow with Time-series Features for Universal Bandwidth-constrained High-speed Network Traffic Classification
원문 초록
Network traffic monitoring based on IP Flows is a standard monitoring approach that can be deployed to various network infrastructures, even the large IPS-based networks connecting millions of people. Since flow records traditionally contain only limited information (addresses, transport ports, and amount of exchanged data), they are also commonly extended for additional features that enable network traffic analysis with high accuracy. Nevertheless, the flow extensions are often too large or hard to compute, which limits their deployment only to smaller-sized networks. This paper proposes a novel extended IP flow called NetTiSA (Network Time Series Analysed), which is based on the analysis of the time series of packet sizes. By thoroughly testing 25 different network classification tasks, we show the broad applicability and high usability of NetTiSA, which often outperforms the best-performing related works. For practical deployment, we also consider the sizes of flows extended for NetTiSA and evaluate the performance impacts of its computation in the flow exporter. The novel feature set proved universal and deployable to high-speed ISP networks with 100\,Gbps lines; thus, it enables accurate and widespread network security protection.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Towards Interpretable Time Series Foundation Models
MoFE-Time: Mixture of Frequency Domain Experts for Time-Series Forecasting Models
Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and Projection
skfolio: Portfolio Optimization in Python
mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale
A foundation model with multi-variate parallel attention to generate neuronal activity
토론
이 논문과 연결된 포럼 글이 아직 없습니다.