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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Recent changes to Introduction to Pyflag</title><link>https://sourceforge.net/p/pyflagsnortalog/wiki/Introduction%2520to%2520Pyflag/</link><description>Recent changes to Introduction to Pyflag</description><atom:link href="https://sourceforge.net/p/pyflagsnortalog/wiki/Introduction%20to%20Pyflag/feed" rel="self"/><language>en</language><lastBuildDate>Wed, 15 Feb 2012 14:21:54 -0000</lastBuildDate><atom:link href="https://sourceforge.net/p/pyflagsnortalog/wiki/Introduction%20to%20Pyflag/feed" rel="self" type="application/rss+xml"/><item><title>WikiPage Introduction to Pyflag modified by Afshin Sadeghi</title><link>https://sourceforge.net/p/pyflagsnortalog/wiki/Introduction%2520to%2520Pyflag/</link><description>
1.Introduction
Digital forensic is described to be as a type of investigation that is using computer generated data as it's source [1]. Network forensics is doing forensic analysis of captured network traffic [2],and disk or memory forensic looks inside the saved bunch of memory data ,This data can be from a part of operating system usage memory running on a computer device to even a part of a movie file stored inside a compressed “tar” file.

The goal of  this primary experiment was to make Pyflag to deal with 4 type of log files and make a report of possibilities and limitations of what Pyflag can do with them .This 4 types of log file are:

Snort log files,
Apache log files,
FileZilla log files,
Windows event files.
</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">Afshin Sadeghi</dc:creator><pubDate>Wed, 15 Feb 2012 14:21:54 -0000</pubDate><guid>https://sourceforge.netd2f96224d4d7c9738b4d6667cc9da8d14d975569</guid></item></channel></rss>