Email has become one of the fastest and most economical forms of communication. However, the increase of email users has resulted in the dramatic increase of spam emails during the past few years. As spammers always try to find a way to evade existing filters, new filters need to be developed to catch spam. Generally, the main tool for email filtering is based on text classification. A classifi...

E-Mail spam detection is a key problem in Cyber Security; and has evoked great interest to the research community. Various classification based and signature based systems have been proposed for filtering spam and detecting viruses that cause spam. However, most of these techniques require content of an email or user profiles, thus involving in high privacy intrusiveness. In this paper, we addr...

he 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. Many studies on spam indicate that it costs orga...

Social networking sites (SNSs) see a variety of spam and scams targeted at their users. In contrast to the limited amounts of information available beyond message text and headers when analyzing email spam, spam on SNSs is often accompanied by a wealth of data on the sender, which can be used to build more accurate detection mechanisms. We analyze 4 million private messages as well as other pub...

It is well known that Unsolicited Commercial Emails (UCE), commonly known as spam, are becoming a serious problem for email accounts of single users, small companies and large institutions. The presence of spam can seriously compromise normal user activities, forcing to navigate through mailboxes to find the relatively few interesting emails, so wasting time and bandwidth, occupying their stora...

In this paper 1 a study of SMS messages in a large US based cellular carrier utilizing both customer reported SMS spam and network Call Detail Records (CDRs) is conducted to develop a comprehensive understanding of SMS spam in order to develop strategies and approaches to detect and control SMS spam activity. The analysis provides insights into content classification of spam campaigns as well a...

Email has gained the explosive growth in the communication of people across the world. This worldwide communication also has some disadvantages like Spam mails. The spammers spread the useless, unwanted mails and even malicious contents to the usersemails. This increasing number of spam mails increases the need for the spam detection architecture with the machine learning classification. The pr...

Email has become one of the frequently used forms of communication. Everyone has at least one email account. Inflow of spam messages is a major problem faced by email users. Currently there are many spam filtering techniques. As the spam filtering techniques came up, spammers improved their methods of spamming. Thus, an effective spam filtering technique is the timely requirement. In this paper...

Designing a spam-filtering system that can run efficiently on heavily burdened servers is particularly important to the widely used email service providers (ESPs) (e.g., Hotmail, Yahoo, and Gmail) who have to deal with millions of emails everyday. Two primary challenges these companies face in spam filtering are efficiency and scalability. This study is undertaken to develop an efficient and sc...

For network intrusion and virus detection, ordinary methods detect malicious network traffic and viruses by examining packets, flow logs or content of memory for any signatures of the attack. This implies that if no signature is known/created in advance, attack detection will be problematical. Addressing unknown attacks detection, we develop in this paper a network traffic and spam analyzer usi...