{"title":"基于模型的网络取证工件提取方法","authors":"I. Alsmadi, M. Alazab","doi":"10.1109/CCC.2017.13","DOIUrl":null,"url":null,"abstract":"Forensic analysts typically search through a large volume of data in different locations looking for possible evidences. The process can be very tedious and time consuming. Automating the process of searching for possible evidences can be very useful even if this can be as an initial stage before further deep human or manual analysis. Toward this goal, we developed a tool to automate extracting forensic artifacts from network resources. We evaluated the tool using artifacts of network packets and switch memory dumps. We found out that their is a need to balance between customization and level of details or accuracy that such tools can produce. This means that it will be impractical to develop a one-for-all tool or else such tool will be very large, complex and possible inefficient.","PeriodicalId":367472,"journal":{"name":"2017 Cybersecurity and Cyberforensics Conference (CCC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Model Based Approach for the Extraction of Network Forensic Artifacts\",\"authors\":\"I. Alsmadi, M. Alazab\",\"doi\":\"10.1109/CCC.2017.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Forensic analysts typically search through a large volume of data in different locations looking for possible evidences. The process can be very tedious and time consuming. Automating the process of searching for possible evidences can be very useful even if this can be as an initial stage before further deep human or manual analysis. Toward this goal, we developed a tool to automate extracting forensic artifacts from network resources. We evaluated the tool using artifacts of network packets and switch memory dumps. We found out that their is a need to balance between customization and level of details or accuracy that such tools can produce. This means that it will be impractical to develop a one-for-all tool or else such tool will be very large, complex and possible inefficient.\",\"PeriodicalId\":367472,\"journal\":{\"name\":\"2017 Cybersecurity and Cyberforensics Conference (CCC)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Cybersecurity and Cyberforensics Conference (CCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCC.2017.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Cybersecurity and Cyberforensics Conference (CCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCC.2017.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Model Based Approach for the Extraction of Network Forensic Artifacts
Forensic analysts typically search through a large volume of data in different locations looking for possible evidences. The process can be very tedious and time consuming. Automating the process of searching for possible evidences can be very useful even if this can be as an initial stage before further deep human or manual analysis. Toward this goal, we developed a tool to automate extracting forensic artifacts from network resources. We evaluated the tool using artifacts of network packets and switch memory dumps. We found out that their is a need to balance between customization and level of details or accuracy that such tools can produce. This means that it will be impractical to develop a one-for-all tool or else such tool will be very large, complex and possible inefficient.