Most e-mail readers spend a significant amount of time regularly deleting junk e-mail (spam) messages, which are a part of marketing campaigning efforts of various companies wherein users normally signed in and it also results in increasing volume of storage space and consumes network bandwidth. A challenge, therefore, rests with the developers and improvement of automatic classifiers that can ...

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...

Most e-mail readers spend a significant amount of time regularly deleting junk e-mail (spam) messages, which are a part of marketing campaigning efforts of various companies wherein users normally signed in and it also results in increasing volume of storage space and consumes network bandwidth. A challenge, therefore, rests with the developers and improvement of automatic classifiers that can ...

Spam, also known as Unsolicited Commercial Email (UCE) is becoming a nightmare for Internet users and providers. Machine learning techniques such as the Support Vector Machines (SVM) have achieved a high accuracy filtering the spam messages. However, a certain amount of legitimate emails are often classified as spam (false positive errors) although this kind of errors are prohibitively expensiv...

Most e-mail readers spend a significant amount of time regularly deleting junk e-mail (spam) messages, which are a part of marketing campaigning efforts of various companies wherein users normally signed in and it also results in increasing volume of storage space and consumes network bandwidth. A challenge, therefore, rests with the developers and improvement of automatic classifiers that can ...

Spam emails are unsolicited, annoying and sometimes harmful messages which may contain malware, phishing or hoaxes. Unlike most studies that address the design of efficient anti-spam filters, we approach spam email problem from a different novel perspective. Focusing on needs cybersecurity units, follow topic-based for addressing classification into multiple categories. We propose SPEMC-15K-E S...

Spam detection is a significant problem which is considered by many researchers by various developed strategies. The best and main spam detection technique should consider and scan the content of the messages to find spam. This research concerns the development of the certain category of granular computing as a classifier for spam detection. In this research, Fuzzy Granular Computing Classifica...

Spam is one of the main problems in emails communications. As the volume of non-english language spam increases, little work is done in this area. For example, in Arab world users receive spam written mostly in arabic, english or mixed Arabic and english. To filter this kind of messages, this research applied several machine learning techniques. Many researchers have used machine learning techn...

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...

One of the many techniques which has recently been employed for filtering spam is one described in the Linux Journal article A Statistical Approach to the Spam Problem [Robinson]. This technique incorporates ideas from the seminal article A Plan For Spam [Graham] as well as R.A. Fisher's technique for combining p-values by means of the chi-square distribution [Hedges & Olkin]. The technique pre...