Rule-Based Spam E-mail Annotation

نویسندگان

  • Giacomo Fiumara
  • Massimo Marchi
  • Rosamaria Pagano
  • Alessandro Provetti
چکیده

A new system for spam e-mail annotation by end-users is presented. It is based on the recursive application of hand-written annotation rules by means of an inferential engine based on Logic Programming. Annotation rules allow the user to express nuanced considerations that depend on deobfuscation, word (non)occurrence and structure of the message in a straightforward, human-readable syntax. We show that a sample collection of annotation rules are effective on a relevant corpus that we have assembled by collecting e-mails that have escaped detection by the industry-standard SpamAssassin filter. The system presented here is intended as a personal tool enforcing personalized annotation rules that would not be suitable for the general e-mail traffic.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A New Hybrid Approach of K-Nearest Neighbors Algorithm with Particle Swarm Optimization for E-Mail Spam Detection

Emails are one of the fastest economic communications. Increasing email users has caused the increase of spam in recent years. As we know, spam not only damages user’s profits, time-consuming and bandwidth, but also has become as a risk to efficiency, reliability, and security of a network. Spam developers are always trying to find ways to escape the existing filters therefore new filters to de...

متن کامل

A Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization

Spam is an unwanted email that is harmful to communications around the world. Spam leads to a growing problem in a personal email, so it would be essential to detect it. Machine learning is very useful to solve this problem as it shows good results in order to learn all the requisite patterns for classification due to its adaptive existence. Nonetheless, in spam detection, there are a large num...

متن کامل

Detecting E-mail Spam Using Spam Word Associations

Now-a-days, mailbox management has become a big task. A large proportion of the emails we receive are spam. These unwanted emails clog the inbox and are very ubiquitous. Here, a new technique for spam detection is presented that makes use of clustering and association rules generated by the Apriori algorithm. Vector space notation is used to represent the emails. The results obtained from exper...

متن کامل

Email classification for Spam Detection using Word Stemming

Unsolicited emails, known as spam, are one of the fast growing and costly problems associated with the Internet today. Among the many proposed solutions, a technique using Bayesian filtering is considered as the most effective weapon against spam. Bayesian filtering works by evaluating the probability of different words appearing in legitimate and spam mails and then classifying them based on t...

متن کامل

Email classification for Spam Detection using Word Stemming

Unsolicited emails, known as spam, are one of the fast growing and costly problems associated with the Internet today. Among the many proposed solutions, a technique using Bayesian filtering is considered as the most effective weapon against spam. Bayesian filtering works by evaluating the probability of different words appearing in legitimate and spam mails and then classifying them based on t...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2010