This dissertation thesis is focused on bulk unsolicited messages which are present in
current time in all sectors of electronic communications. It is not only e-mail
communication, but also in online forums, discussion contributions, social networking
and more. Analyze spam messages is therefore an essential element in preventing
flooding user mailboxes.
Antispam countermeasures is a set of processes, software tools and methods. It is
necessary to harmonize all these components into one cooperating piece of service.
Administrators of email servers are trying to keep their servers optimally configured. The
problem is that spammers trying continuously these defense mechanisms and filter bypass
to enhance spam processes. Their work is very sophisticated and this fight does not yet
have a clear winner. After enhancement techniques either processes takes place after a
certain time to balance the advantages and disadvantages.
For these reasons it is necessary to have a tool which can be analyzed in depth junk
messages with dynamic data views. This tool can be Online Analytical Processing (OLAP
below), which is very suitable for this purpose.
Presented a method of data extraction and transformation and preparation for storage in
a warehouse DT-MEZ (Data Pump - metadata email messages). This method is part of
the methodology ASOLAP (Antispam - OLAP).
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:259614 |
| Date | January 2016 |
| Creators | Vasilenko, Alexandr |
| Contributors | Klimešová, Dana, Toman, Prokop |
| Publisher | Česká zemědělská univerzita v Praze |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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