A Novel Bio-Inspired Approach for Multilingual Spam Filtering

Abstract

In today's digital world the email service has revolutionized the sphere of electronic communication. It has become a veritable social phenomenon in our daily life. Unfortunately, this technology has become incontestably the original source of malicious activities especially the plague called undesirable emails (SPAM) that has grown tremendously in the last few years. The battle against spam emails is extremely fierce. This paper deals with an intelligent spam filtering system called artificial heart-lungs system (AHLS) mimicked from the biological phenomenon of general circulation and oxygenation of blood. It is composed of different steps: Selection to stop automatically emails with undesirable identifier. Multilingual pre-processing to treat the problem of multilingual spam emails and vectoring them. Heart filter and lungs filter to classify unwelcome email in the spam folder and welcome email in the ham folder to present them to the recipient. The method uses an automatic updating of learning basis and black list, and a ranking step to order the spam mails according to their spam relevancy. For the authors' experimentation, they have constructed a new dataset M.SPAM composed of emails pre-classified as spam or ham with different language (English, Spanish, French, and melange) and using the validation measures (recall, precision, f-measure, entropy, accuracy and error, false positive rate and false negative rate, ROC and learning curve). The authors have optimized the sensitive parameters (text representation technique, lungs filters, and the size of initial leaning basis). The results are positive compared to the result of other bio-inspired techniques (artificial social bees, artificial social cockroaches), supervised algorithm (decision tree C4.5) and automatic algorithm (K-means). Finally, a visual result mining tool was developed in order to see the results in graphical form (3d cub and cobweb) with more realism using the functionality of zooming and rotation. The authors' aims are to eliminate a large proportion of unwelcome email, treated the multilingual emails, ensuring an automatic updating of their system and poses a minimal risk of eliminating ham email.

A Framework for Hoax News Detection and Analyzer used Rule-based Methods

“…Vu, uses multilanguage by introducing statistical rule-based methods to create rules for detecting in various languages [44]. Bouarara [45], uses multilanguage to detect email with learning-based methods automatically and ranks the steps to generate spam emails [47]. Contributing to our research by using the technique of collecting hoax news from the web in several different countries or languages, and produce site data effects are news hoax news from several languages including, Indonesian, English and Malaysian.…”

Automated content analysis across six languages

“…Expert human translation, however, is both expensive and time-consuming. Automated translation programs, on the other hand, are efficient and cost-effective [35,36], and other research has shown encouraging results using machine learning for automated sentiment analysis for multilingual corpora [37], including spam filtering [38,39]. Given limited time and money, researchers have had to choose between greater accuracy, greater efficiency, and greater expense.…”