Spam, also known as Unsolicited Commercial Email (UCE) is becoming a nightmare for Internet users and providers. Machine learning techniques such as the Support Vector Machines (SVM) have achieved a high accuracy filtering the spam messages. However, a certain amount of legitimate emails are often classified as spam (false positive errors) although this kind of errors are prohibitively expensiv...

Bayesian content filters gained popular acclaim when they were put forward in 2002 by Paul Graham as a potential long-term solution for the spam problem. They have since fallen from the limelight, however, due to perceived attack vulnerabilities inherent to all content-based filters as well as real and imagined vulnerabilities specific to Bayesian filters. It has also been assumed that Bayesian...

In this paper we present Linger a neural network based system for automated e-mail classification. Two scenarios are explored: filing e-mails into folders and spam e-mail filtering. Extensive experiments indicate that Linger compares favourably to other classification techniques. We study the effects of various feature selection, weighting and normalization methods, and also the portability of ...

Thiswork is devoted to the problemof optimising scores for anti-spamfilters, which is essential for the accuracy of any filter based anti-spam system, and is also one of the biggest challenges in this research area. In particular, this optimisation problem is considered from two different points of view: single andmultiobjective problem formulations. Some of existing approaches within both form...

Facing new type of challenge which maintain clusters in a dynamic web environment with a high volume of updates and costly re-clustering, the paper describes a novel behavior-based anti-Spam technology based on incremental immune-inspired clustering algorithm. we use an “internal image” network to represent the input data set in order to reduce data redundancy, whilst at the same time extractin...

Due to the increasing amount of spam email traffic, users are in danger, while server resources becoming overloaded. Therefore, it is necessary protect users, but also prevent SMTP system overload during attacks. The aim this paper design and implement an autoscalable distributed anti-spam based on a Proof work concept. proposed solution extends protocol order enable evaluation client?s credibi...

The electronic mail (email) is nowadays an essential communication service being widely used by most Internet users. One of the main problems affecting this service is the proliferation of unsolicited messages (usually denoted by spam) which, despite the efforts made by the research community, still remains as an inherent problem affecting this Internet service. In this perspective, this work p...

Spam is still an open problem from the network operator’s perspective. The common state-of-the-art strategy to place filters against spam is at the recipient’s edge. Although this strategy largely solves the spam problem from the user’s perspective – false positives/negatives may still exist – it cannot prevent spam from traversing the Internet. Consequently, with nowadays around 200 billion sp...

Spam emails are unsolicited, annoying and sometimes harmful messages which may contain malware, phishing or hoaxes. Unlike most studies that address the design of efficient anti-spam filters, we approach spam email problem from a different novel perspective. Focusing on needs cybersecurity units, follow topic-based for addressing classification into multiple categories. We propose SPEMC-15K-E S...