It is well known that spammers can forge the header of an email, in particular, the trace information carried in the Received: fields, as an attempt to hide the true origin of the email. Despite its critical importance for spam control and holding accountable the true originators of spam, there has been no systematic study on the forgery behavior of spammers. In this paper, we provide the first...

Spam, the electronic equivalent of junk mail, affects over 600 million users worldwide. Even as anti-spam solutions change to limit the amount of spam sent to users, the senders adapt to make sure their messages are seen. This paper looks at application of the artificial immune system model to protect email users effectively from spam. In particular, it tests the spam immune system against the ...

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...

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 this paper, we report a QA system which can answer how type questions based on the confirmed knowledge base which was developed by using mails posted to a mailing list. We first discuss a problem of developing a knowledge base by using natural language documents: wrong information in natural language documents. Then, we describe a method of detecting wrong information in mails posted to a ma...