Abstract Background Numerous online journals are referred to as predatory because their efforts focused primarily on collecting publication fees rather than content, peer review, or manuscript presentation. Many of these send Academic Spam Mails (ASM), requesting submissions. Purpose/Methods Over a 3-month period, all ASMs addressed the author were collected and analyzed. A fake was created wit...

The protection of personal identifiable information (PII) is increasingly demanded by customers and data protection regulation. To safeguard PII a organization has to find out which incoming communication actually contains it. Only then PII can be labeled, tracked, and protected. E-mails are one of the main means of communication. They consist of unstructured data difficult to classify. We deve...

Background Traditional client level spam filters rely on rule based heuristics. While these filters can be effective they have several limitations. The rules must be created by hand. This requires the filter creator to examine a corpus of spam and cull out characteristics. This is a time consuming process and it is easy to miss rules which are quite effective at detecting spam. While the word ”...

This paper would explore the problem of spam. It would explore its nature and also the reasons why it is a security risk. It would also describe some of the techniques that are currently used to deal with spam including basic technical and policy methodology. This paper intends to be a general-information source to the problem of spam and also provides information of where to get more detailed ...

In this paper we propose a concept for preventing unsolicited bulk e-mail (UBE, “spam”) at the outgoing SMTP server. In particular, we take the point of view of an Internet Service Provider (ISP), who wants to control the email traffic going out of its network. A central component of our concept contains the adaptation of a token bucket mechanism which allows the ISP to dynamically limit the nu...

Spam has become a major issue in computer security because it is a channel for threats such as computer viruses, worms and phishing. Many solutions feature machine-learning algorithms trained using statistical representations of the terms that usually appear in the e-mails. Still, these methods require a training step with labelled data. Dealing with the situation where the availability of labe...

The growth in the utilization of text mining tools and techniques in the last decade has been primarily driven by the increase in the sheer volume of unstructured texts and the need to extract useful and more importantly, quality information from them. The impetus to analyse unstructured data efficiently and effectively as part of the decision making processes within an organization has further...

The growth in the utilization of text mining tools and techniques in the last decade has been primarily driven by the increase in the sheer volume of unstructured texts and the need to extract useful and more importantly, quality information from them. The impetus to analyse unstructured data efficiently and effectively as part of the decision making processes within an organization has further...

The increasing use of e-mail in the world because of its simplicity and low cost, has led many Internet users are interested in developing their work in the context of the Internet. In the meantime, many of the natural or legal persons, to sending e-mails unrelated to mass. Hence, classification and identification of spam emails is very important. In this paper, the combined Particle Swarm Opti...

This paper presents a comparison of support vector machines (SVM), memory-based learning (MBL) and Naïve Bayes (NB) techniques for the classification of legitimate and spam mails. Although there are a number of method-comparative studies regarding spam mail filtering, most of the studies are tested on separate data sets. In order to evaluate the effectiveness of SVM, MBL and NB methods, we have...