{"title":"Network Stegoinsider Detection","authors":"A. Salita, A. Krasov","doi":"10.1109/SmartIndustryCon57312.2023.10110748","DOIUrl":null,"url":null,"abstract":"The number of crimes committed by insiders has increased dramatically over the past 10 years. Insiders use various technologies, including steganography, to bypass security measures and steal confidential information. In this paper, we analyse the methods that can be used to identify the steganographic channel and steganographic insider, such as Shannon information entropy method, Kolmogorov-Smirnov method, probability distribution variance comparison method, machine learning method and neural network method. Based on these methods, some programs were written to identify steganographic channels in the network. Each of the methods was tested on real enterprise traffic. As a result it is possible to say whether these methods are suitable for use in the enterprise network or nor.","PeriodicalId":157877,"journal":{"name":"2023 International Russian Smart Industry Conference (SmartIndustryCon)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Russian Smart Industry Conference (SmartIndustryCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SmartIndustryCon57312.2023.10110748","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

The number of crimes committed by insiders has increased dramatically over the past 10 years. Insiders use various technologies, including steganography, to bypass security measures and steal confidential information. In this paper, we analyse the methods that can be used to identify the steganographic channel and steganographic insider, such as Shannon information entropy method, Kolmogorov-Smirnov method, probability distribution variance comparison method, machine learning method and neural network method. Based on these methods, some programs were written to identify steganographic channels in the network. Each of the methods was tested on real enterprise traffic. As a result it is possible to say whether these methods are suitable for use in the enterprise network or nor.
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网络Stegoinsider检测
在过去的10年里,内部人员犯罪的数量急剧增加。内部人士使用各种技术,包括隐写术,绕过安全措施,窃取机密信息。本文分析了可用于识别隐写通道和隐写内幕的方法,如Shannon信息熵法、Kolmogorov-Smirnov法、概率分布方差比较法、机器学习方法和神经网络方法。在此基础上,编写了网络隐写信道识别程序。每种方法都在真实的企业流量中进行了测试。因此,很难说这些方法是否适合在企业网络中使用。
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