Event Dates
Location
Online
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 reviews a set of open-source tools, including snort, pcap, TcpDump, wireshark, and NetworkMiner.
It also highlights 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 will also discuss the challenges in network forensics.
Potential workarounds will be given for law enforcement and future work is identified for researchers in the field.
Detailed Learning Objectives:
1) Definition and value of network forensics
2) Challenges in network forensics for researchers and law enforcement
3) Network forensics tools, limitations, and workarounds
Funding for this Forensic Technology Center of Excellence event has been provided by the National Institute of Justice.
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 reviews a set of open-source tools, including snort, pcap, TcpDump, wireshark, and NetworkMiner.
It also highlights 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 will also discuss the challenges in network forensics.
Potential workarounds will be given for law enforcement and future work is identified for researchers in the field.
Detailed Learning Objectives:
1) Definition and value of network forensics
2) Challenges in network forensics for researchers and law enforcement
3) Network forensics tools, limitations, and workarounds
Funding for this Forensic Technology Center of Excellence event has been provided by the National Institute of Justice.
Date Created: February 3, 2021