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- W4377224210 abstract "Data streaming has many applications in network monitoring, web services, e-commerce, stock trading, social networks, and distributed sensing. This paper introduces a new problem of real-time burst detection in flow spread, which differs from the traditional problem of burst detection in flow size. It is practically significant with potential applications in cybersecurity, network engineering, and trend identification on the Internet. It is a challenging problem because estimating flow spread requires us to remember all past data items and detecting bursts in real time requires us to minimize spread estimation overhead, which was not the priority in most prior work. This paper provides the first efficient, real-time solution for spread burst detection. It is designed based on a new real-time super spreader identifier, which outperforms the state of the art in terms of both accuracy and processing overhead. The super spreader identifier is in turn based on a new sketch design for real-time spread estimation, which outperforms the best existing sketches." @default.
- W4377224210 created "2023-05-23" @default.
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- W4377224210 date "2023-05-19" @default.
- W4377224210 modified "2023-09-26" @default.
- W4377224210 title "Real-time Spread Burst Detection in Data Streaming" @default.
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- W4377224210 doi "https://doi.org/10.1145/3589979" @default.
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