Network traffic classification for data fusion: A survey
نویسندگان
چکیده
Traffic classification groups similar or related traffic data, which is one main stream technique of data fusion in the field network management and security. With rapid growth users emergence new networking services, has attracted increasing attention. Many techniques have been developed widely applied. However, existing literature lacks a thorough survey to summarize, compare analyze recent advances order deliver holistic perspective. This paper carefully reviews methods from comprehensive perspective by classifying them into five categories based on representative features, i.e., statistics-based classification, correlation-based behavior-based payload-based port-based classification. A series criteria are proposed for purpose evaluating performance methods. For each specified category, we discuss details, advantages disadvantages its methods, also present features commonly used. Summaries investigation offered providing specialized view state-of-art. convenience, cover discussion mostly used datasets adopted review. At end, identify list open issues future directions this research field. • Comprehensive evaluation assess review An analysis granularity dividing it four levels. Exploration directions.
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ژورنال
عنوان ژورنال: Information Fusion
سال: 2021
ISSN: ['1566-2535', '1872-6305']
DOI: https://doi.org/10.1016/j.inffus.2021.02.009