Titlebook: Digital Forensics and Cyber Crime; 12th EAI Internation Pavel Gladyshev,Sanjay Goel,Daryl Johnson Conference proceedings 2022 ICST Institut

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書目名稱Digital Forensics and Cyber Crime影響因子(影響力)




書目名稱Digital Forensics and Cyber Crime影響因子(影響力)學(xué)科排名




書目名稱Digital Forensics and Cyber Crime網(wǎng)絡(luò)公開度




書目名稱Digital Forensics and Cyber Crime網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Digital Forensics and Cyber Crime被引頻次




書目名稱Digital Forensics and Cyber Crime被引頻次學(xué)科排名




書目名稱Digital Forensics and Cyber Crime年度引用




書目名稱Digital Forensics and Cyber Crime年度引用學(xué)科排名




書目名稱Digital Forensics and Cyber Crime讀者反饋




書目名稱Digital Forensics and Cyber Crime讀者反饋學(xué)科排名

不溶解

Victoria N. Hutchison,Simo Hostikka code obfuscation. The accuracy for the task of identifying whether the code is obfuscated reaches 98.6%, while the accuracy for the task of identifying the specific obfuscation algorithm performed reaches 97.6%.

淡紫色花

Victoria N. Hutchison,Simo Hostikkaer, we propose an incident response methodology matrix called BackDoor Incident Response Model (BDIRM) to handle incidents with backdoor effectively, thereby accelerating to eradicate the risk and impact of backdoor against organizations.

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mosque

Auto-Parser: Android Auto and Apple CarPlay Forensics,uced by these applications and propose a proof of concept open source tool to assist investigators in automatically extracting relevant artifacts from Android Auto and Apple CarPlay as well as other day-to-day essential applications.

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Backdoor Investigation and Incident Response: From Zero to Profit,er, we propose an incident response methodology matrix called BackDoor Incident Response Model (BDIRM) to handle incidents with backdoor effectively, thereby accelerating to eradicate the risk and impact of backdoor against organizations.

傻

,Gotta Catch’em All! Improving P2P Network Crawling Strategies,snapshot is reduced on average by 9% due to increased hit-rates during network crawling. While we show our improvements at the example of a new Bitcoin crawler, proven concepts can be transferred to other P2P networks as well.

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Meeting Material and Physical Needs,e feature extraction part, a steganalysis residual block module and a squeeze-and-excitation (SE) block are designed to improve the network’s representation ability. In comparison to the existing steganalysis methods, experimental results show that the proposed network performs better to detect DCT/DST-based HEVC steganography.