Domain Registration Date Retrieval System for Improving Spam Mail Discrimination
نویسندگان
چکیده
Recently, many spam mails associated with “One-click fraud,” “Phishing,” and so on have been sent to unspecified large number of e-mail users. According to some previous works, most spam mails contained some URLs whose domains were registered relatively recently, such that the age of the domain used in the URL in the messages would be a good criterion for spam mail discrimination. However, it is difficult to obtain the age or the registration date of a specific domain for each message by WHOIS service since most WHOIS services would block frequent queries. In this paper, we propose a domain registration date retrieval system, which updates zone files of some Top Level Domains (TLDs) every day, keeps track of the registration date for new domains, and works as a DNS server that replys with the registration date of the queried domain. According to the performance evaluation, the prototype system could update the registration date for all the domains of “com” TLD in two hours.
منابع مشابه
SpamHunting: An instance-based reasoning system for spam labelling and filtering
In this paper we show an instance-based reasoning e-mail filtering model that outperforms classical machine learning techniques and other successful lazy learners approaches in the domain of anti-spam filtering. The architecture of the learning-based anti-spam filter is based on a tuneable enhanced instance retrieval network able to accurately generalize e-mail representations. The reuse of sim...
متن کاملA 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 کاملA 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 کاملEmail 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 کاملEmail 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 کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- JIP
دوره 22 شماره
صفحات -
تاریخ انتشار 2014