The Spamalot system uses intelligent agents to interact with spam messages and systems referenced in spam. The goal of Spamalot is to consume spam senders’ resources by engaging the spammer in an unproductive conversation or information exchange. To date two Spamalot agents have been implemented: Arthur which handles Nigerian spam and Patsy which processes spam requesting information via web fo...

Increased use of email in daily transactions for many businesses or general communication due to its cost-effectiveness has made emails vulnerable attacks, including spam. Spam are unsolicited messages that very similar each other and sent multiple recipients randomly. This study analyzes the Rotation Forest model modifies it spam classification problem. Also, aim this is create a better classi...

As a convenient and low-cost mobile communication technology, Short Messaging Service (SMS) is experiencing very rapid growth. It is reported that 700 million mobile phone users worldwide sent 20 to 30 billion SMS messages every month in 2001. At the same time, SMS commerce applications have emerged to provide mobile users consumeroriented services. The huge SMS messaging customer base serves a...

A substantial majority of the email sent everyday is spam. Spam emails cause many problems if someone acts or clicks on the link provided in the email body. The problems may include infecting users personal machine with malware, stealing personal information, capturing credit card information, etc. Since spam emails are generated as a part of a very limited numbers of spam campaigns, it is usef...

Recently, email has become a common way for people to communicate and share information both officially personally. Email may be used by spammers transmit harmful materials Internet users. The data must protected from unauthorized access, which necessitates the development of reliable method identifying spam emails. As result, variety solutions have been devised. An innovative hybrid machine le...

Today the major problem that the people are facing is spam mails or e-mail spam. In recent years there are so many schemes are developed to detect the spam emails. Here the primary idea of the similarity matching scheme for spam detection is to maintain a known spam database, formed by user’s feedback, to block the subsequent near-duplicate spam’s. We propose a novel e-mail abstraction scheme, ...

This article presents an extensive characterization of a spam-infected e-mail workload. The study aims at identifying and quantifying the characteristics that significantly distinguish spam from non-spam (i.e., legitimate) traffic, assessing the impact of spam on the aggregate traffic, providing data for creating synthetic workload models, and drawing insights into more effective spam detection...

User feedback is vital to the quality of the collaborative spam fi lters frequently used in open membership email systems such as Yahoo Mail or Gmail. Users occasionally designate emails as spam or non-spam (often termed as ham), and these labels are subsequently used to train the spam fi lter. Although the majority of users provide very little data, as a collective the amount of training data ...

Statistical spam filters are known to be vulnerable to adversarial attacks. One of the more common adversarial attacks, known as the good word attack, thwarts spam filters by appending to spam messages sets of “good” words, which are words that are common in legitimate email but rare in spam. We present a counterattack strategy that attempts to differentiate spam from legitimate email in the in...

Spam is pervasive across many types of electronic communication, including email, instant messaging, and social networks. To reach more users and increase financial gain, many spammers now use multiple content-sharing platforms— including online social networks—to disseminate spam. In this paper, we perform a joint analysis of spam in email and social networks. We use spam data from Yahoo’s web...