In this paper we present a detailed study of the behavioral characteristics of spammers based on a two-month email trace collected at a large US university campus network. We analyze the behavioral characteristics of spammers that are critical to spam control, including the distributions of message senders, spam and non-spam messages by spam ratios; the statistics of spam messages from differen...

In this article, we propose a spam image clustering approach that uses data mining techniques to study the image attachments of spam emails with the goal to help the investigation of spam clusters or phishing groups. Spam images are first modeled based on their visual features. In particular, the foreground text layout, foreground picture illustrations and background textures are analyzed. Afte...

Email becomes the major source of communication these days. Most humans on the earth use email for their personal or professional use. Email is an effective, faster and cheaper way of communication. The importance and usage for the email is growing day by day. It provides a way to easily transfer information globally with the help of internet. Due to it the email spamming is increasing day by d...

While enjoying the convenience of email communications, many users have also experienced annoying email spam. Even if the current spam detecting approaches have gained a competitive edge against text-based email spam, they still face the challenge arising from imagebased spam (image spam in short). Image spam normally includes embedded images that contain the spam messages in binary format rath...

In this paper, we aim to explore the possibility of Transformer model in detecting spam Short Message Service (SMS) messages by proposing a modified that is designed for SMS messages. The evaluation our proposed performed on Spam Collection v.1 dataset and UtkMl's Twitter Detection Competition dataset, with benchmark multiple established machine learning classifiers state-of-the-art detection a...

An improved e-mail classification method based on Artificial Immune System is proposed in this paper to develop an immune based system by using the immune learning, immune memory in solving complex problems in spam detection. An optimized technique for e-mail classification is accomplished by distinguishing the characteristics of spam and non-spam that is been acquired from trained data set. Th...

A new trend in email spam is the emergence of image spam. Although current anti-spam technologies are quite successful in filtering text-based spam emails, the new image spams are substantially more difficult to detect, as they employ a variety of image creation and randomization algorithms. Spam image creation algorithms are designed to defeat well-known vision algorithms such as optical chara...

In spite of the fact, a number of researchers everywhere throughout the globe are busy in broad research with the aim to overcome the problem of spam; although an effective solution is yet to be discovered. Due to the fact that spam filtering is perplexing issue, it is unrealistic to spam messages with one arrangement. As the spam emails structure is not constant, hence we require a solution wh...

This paper proposes a novel behavior-based anti-spam technology for email service based on an artificial immune-inspired clustering algorithm. The suggested method is capable of continuously delivering the most relevant spam emails from the collection of all spam emails that are reported by the members of the network. Mail servers could implement the anti-spam technology by using the “black lis...