Many researchers have applied statistical analysis techniques to email for classification purposes, such as identifying spam messages. Such approaches can be highly effective, however many examine incoming email exclusively — which does not provide detailed information about an individual user’s behavior. Only by analyzing outgoing messages can a user’s behavior be ascertained. Our contribution...

In our modern society telephony has developed to an omnipresent service. People are available at anytime and anywhere. Furthermore the Internet has emerged to an important communication medium. These facts and the raising availability of broadband internet access has led to the fusion of these two services. Voice over IP or short VoIP is the keyword, that describes this combination. The advanta...

Email has grown into one of the dominant forms of communication in the 21st century. However, email systems were designed without security in mind, thus allowing attackers to abuse the system and send unsolicited email (or spam). The problem of spam has become so severe that recent studies [1], [2] report that over 90% of the emails sent in 2007 were spam, resulting in productivity losses amoun...

Email has emerged as a dominant form of electronic communication between people. Spam is a major problem for email users, with estimates of up to 56% of email falling into that category [13]. Control of Spam is being attempted with technical [38-44] and legislative [19 -36] methods. In this paper we look at email and spam from a supply-demand perspective. We propose Gridemail, an email system b...

With the development of the diversification of spam, it raises the difficulties and challenges to content-based spam filtering. To address this problem, this paper firstly introduced the statistical features of Email headers, and then proposed a method to use these features to improve Bayesian anti-spam filter. The selected Email-header features are presented as the fingerprint vectors, and the...

Abstract Spam emails have been traditionally seen as just annoying and unsolicited containing advertisements, but they increasingly include scams, malware or phishing. In order to ensure the security integrity for users, organisations researchers aim develop robust filters spam email detection. Recently, most based on machine learning algorithms published in academic journals report very high p...

We develop new techniques to map botnet membership using traces of spam email. To group bots into botnets we look for multiple bots participating in the same spam email campaign. We have applied our technique against a trace of spam email from Hotmail Web mail services. In this trace, we have successfully identified hundreds of botnets. We present new findings about botnet sizes and behavior wh...

IP Address blacklisting [1, 2] works by storing a list of the origin of known spam and then ignoring further email sent from that IP address, under the assumption it is also spam. This approach has two problems: spammers are able to circumvent it by regularly switching IP addresses, and after spam has been sent from an IP address hijacked by a spammer, email sent by the unsuspecting computer us...

Spam has become an important problem for computer security because it is a channel for spreading threats, including computer viruses, worms and phishing. Currently, more than 85% of received emails are spam. Historical approaches to combating these messages, including simple techniques such as sender blacklisting or using email signatures, are no longer completely reliable on their own. Many so...

Spams are electronic junk mails that are costly for the individuals and organizations who receive them and Internet service providers who handle them. They also highly contribute to the lack of trust in email service by the users, intrusion of privacy, and fraud. Spam detectors with a wide range of effectiveness are exist in the market. To the best of our knowledge, none of the existing spam de...