Spam as unsolicited e-mail has certainly crossed the border of just being bothersome. In 2003, it surpassed legitimate e-mail – growing to more than 50% of all Internet e-mails. Annually, it causes economic harms of several billion Euros. Fighting spam, beside legal approaches especially technical means are deployed in practical systems, mainly focussing on blocking and filtering mechanisms. Th...

Die rechtskonforme Verarbeitung personenbezogener Daten erweist sich in heutigen Anwendungssystemen häufig als schwer zu realisierende Anforderung. Beispielsweise liegt in der Filterung von Spam-Nachrichten aus E-Mail-Strömen eine der größten diesbezüglichen Herausforderungen für die heutigen E-Mail-Systeme, da hier der Personenbezug besonders evident ist. Ein oft angestrebter Ansatz beruht auf...

Spam has become a major issue in computer security because it is a channel for threats such as computer viruses, worms, and phishing. More than 86% of received e-mails are spam. Historical approaches to combating these messages, including simple techniques such as sender blacklisting or the use of e-mail signatures, are no longer completely reliable. Many current solutions feature machine-learn...

Spam issues have become worse on social media platforms and apps with the growth of IoT. To solve problem, researchers suggested several spam detection techniques. rates are still high despite use anti-spam technologies tactics, especially given ubiquity rogue e-mails that lead to dangerous websites. By using up memory or storage space, may cause servers run slowly. One most essential methods f...

Spam has become an issue of concern in almost all areas where the Internet is involved, and many people today have become victims of spam from publishers and individual journals. We studied this phenomenon in the field of scholarly publishing from the perspective of a single author. We examined 1,024 such spam e-mails received by Marcin Kozak from publishers and journals over a period of 391 da...

Spam has become a major issue in computer security because it is a channel for threats such as computer viruses, worms and phishing. More than 85% of received e-mails are spam. Historical approaches to combat these messages including simple techniques such as sender blacklisting or the use of email signatures, are no longer completely reliable. Currently, many solutions feature machine-learning...

statistical learning algorithms. The GL is the output of a list of classifiers which are not categorized as true positive (TP) nor true negative (TN) but in an unclear status. Many works have been done to filter spam from legitimate e-mails using classification algorithms and substantial performance has been achieved with some amount of false-positive (FP) tradeoffs. However, in spam filtering ...

The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widel...