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Magnet Forensics Windows Memory Analysis Certificate for Marc Robinson

Network Forensics: Challenges & Tools Course Certificate

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Using Searchable Photo Database IACA Certificate of Training for Marc Robinson AVFA EET
Forensic Technology Center of Excellence
In response to criminal investigations involving digital evidence, law enforcement needs forensically sound tools to acquire, evaluate, process, and present the data to the court. In the case of network forensics, challenges arise when the evidence is buried in large volumes of data.The financial burdens of purchasing and licensing proprietary tools are not sustainable for law enforcement. This webinar reviewed a set of open-source tools, including snort, pcap, TcpDump, wireshark, and NetworkMiner. It highlighted a recent open-source toolkit, FileTSAR, developed by Purdue University. This user-friendly toolkit can extract digital evidence from large amounts of network traffic and reconstruct unencrypted files, web pages, emails, and VOIP. FileTSAR achieves great performance by leveraging Spark, ElasticSearch, Kafka, and Kibana.Since existing tools all have their own limitations, the presenters also discussed the challenges in network forensics. Potential workarounds were given for law enforcement and future work was identified for researchers in the field.
In response to criminal investigations involving digital evidence, law enforcement needs forensically sound tools to acquire, evaluate, process, and present the data to the court. In the case of network forensics, challenges arise when the evidence is buried in large volumes of data.The financial burdens of purchasing and licensing proprietary tools are not sustainable for law enforcement. This webinar reviewed a set of open-source tools, including snort, pcap, TcpDump, wireshark, and NetworkMiner. It highlighted a recent open-source toolkit, FileTSAR, developed by Purdue University. This user-friendly toolkit can extract digital evidence from large amounts of network traffic and reconstruct unencrypted files, web pages, emails, and VOIP. FileTSAR achieves great performance by leveraging Spark, ElasticSearch, Kafka, and Kibana.Since existing tools all have their own limitations, the presenters also discussed the challenges in network forensics. Potential workarounds were given for law enforcement and future work was identified for researchers in the field.