{"title":"未知二进制协议逆向工程的网络消息字段类型聚类","authors":"Stephan Kleber, F. Kargl, Milan State, M. Hollick","doi":"10.1109/DSN-W54100.2022.00023","DOIUrl":null,"url":null,"abstract":"Reverse engineering of unknown network protocols based on recorded traffic traces enables security analyses and debugging of undocumented network services. One important step in protocol reverse engineering is to determine data types of message fields. Existing approaches for binary protocols (1) lack comprehensive methods to interpret message content and determine the data types of discovered segments in a message and (2) assume the availability of context, which prevents the analysis of complex and lower-layer protocols. Overcoming these limitations, we propose the first generic method to analyze message field data types in unknown binary protocols by clustering of segments with the same data type. Our extensive evaluation shows that our method in most cases provides clustering of up to 100 % precision at reasonable recall. Particularly relevant for use in fuzzing and misbehavior detection, we increase the coverage of message bytes over the state-of-the-art to 87 % by almost a factor of 30. We provide an open-source implementation to allow follow-up works.","PeriodicalId":349937,"journal":{"name":"2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Network Message Field Type Clustering for Reverse Engineering of Unknown Binary Protocols\",\"authors\":\"Stephan Kleber, F. Kargl, Milan State, M. Hollick\",\"doi\":\"10.1109/DSN-W54100.2022.00023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Reverse engineering of unknown network protocols based on recorded traffic traces enables security analyses and debugging of undocumented network services. One important step in protocol reverse engineering is to determine data types of message fields. Existing approaches for binary protocols (1) lack comprehensive methods to interpret message content and determine the data types of discovered segments in a message and (2) assume the availability of context, which prevents the analysis of complex and lower-layer protocols. Overcoming these limitations, we propose the first generic method to analyze message field data types in unknown binary protocols by clustering of segments with the same data type. Our extensive evaluation shows that our method in most cases provides clustering of up to 100 % precision at reasonable recall. Particularly relevant for use in fuzzing and misbehavior detection, we increase the coverage of message bytes over the state-of-the-art to 87 % by almost a factor of 30. We provide an open-source implementation to allow follow-up works.\",\"PeriodicalId\":349937,\"journal\":{\"name\":\"2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DSN-W54100.2022.00023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSN-W54100.2022.00023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Network Message Field Type Clustering for Reverse Engineering of Unknown Binary Protocols
Reverse engineering of unknown network protocols based on recorded traffic traces enables security analyses and debugging of undocumented network services. One important step in protocol reverse engineering is to determine data types of message fields. Existing approaches for binary protocols (1) lack comprehensive methods to interpret message content and determine the data types of discovered segments in a message and (2) assume the availability of context, which prevents the analysis of complex and lower-layer protocols. Overcoming these limitations, we propose the first generic method to analyze message field data types in unknown binary protocols by clustering of segments with the same data type. Our extensive evaluation shows that our method in most cases provides clustering of up to 100 % precision at reasonable recall. Particularly relevant for use in fuzzing and misbehavior detection, we increase the coverage of message bytes over the state-of-the-art to 87 % by almost a factor of 30. We provide an open-source implementation to allow follow-up works.