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...

Unsolicited bulk email, aka spam is a persistent threat to the usefulness of the Internet. The fight against spam today relies solely on filtering at the recipient’s mail server, which can delay mail delivery. We present a spam countering approach consisting of two complementary techniques. The first, token-based authentication, can identify emails from valid senders that a user expects to hear...

Email spam is the most effective form of online advertising. Unlike telephone marketing, email spamming does not require huge human or financial resources investment. Most existing spam filtering techniques concentrate on the emails’ content. However, most spammers obfuscate their emails’ content to circumvent content-based spam filters. An integrated solution for restricting spam emails is nee...

A three-way decisions solution based on Bayesian decision theory for filtering spam emails is examined in this paper. Compared to existed filtering systems, the spam filtering is no longer viewed as a binary classification problem. Each incoming email is accepted as a legitimate or rejected as a spam or undecided as a further-exam email by considering the misclassification cost. The three-way d...

The Pattern classification system classifies the pattern into feature space within a boundary. In case adversarial applications use, for example Spam Filtering, the Network Intrusion Detection System (NIDS), Biometric Authentication, the pattern classification systems are used. Spam filtering is an adversary application in which data can be employed by humans to attenuate perspective operations...

The majority of Web email is known to be generated by machines even when one excludes spam. Many machine-generated email messages such as invoices or travel itineraries are critical to users. Recent research studies establish that causality relations between certain types of machine-generated email messages exist and can be mined. These relations exhibit a link between a given message to a past...