Spam Filter Analysis
نویسندگان
چکیده
Unsolicited bulk email (aka. spam) is a major problem on the Internet. To counter spam, several techniques, ranging from spam filters to mail protocol extensions like hashcash, have been proposed. In this paper we investigate the effectiveness of several spam filtering techniques and technologies. Our analysis was performed by simulating email traffic under different conditions. We show that genetic algorithm based spam filters perform best at server level and naı̈ve Bayesian filters are the most appropriate for filtering at user level.
منابع مشابه
A New Approach to Spam Mail Detection
The ever increasing menace of spam is bringing down productivity. More than 70% of the email messages are spam, and it has become a challenge to separate such messages from the legitimate ones. I have developed a spam identification engine which employs naive Bayesian classifier to identify spam. A new concept-based mining model that analyzes terms on the sentence, document is introduced. . The...
متن کاملLearning-based Spam Filters: the Influence of the Temporal Distribution of Training Data
The great number and variety of learning-based spam filters proposed during the last years cause the need in complex and many-sided evaluation of them, taking features of the phenomenon of spam into account. This paper is dedicated to the analysis of the dependence of filter performance on the temporal distribution of training data; the cause of this dependence is the changeability of email. Su...
متن کاملNetwork-based spam filter on Twitter
Rapidly growing micro-blogging social networks, such as Twitter, have been infiltrated by large number of spam accounts. Limited to 140 characters, Twitter spam is often vastly different from traditional email spam and link spam such that conventional methods of content-based spam filtering are insufficient. Many researchers have proposed schemes to detect spammers on Twitter. Most of these sch...
متن کاملSeven Hypothesis about Spam Filtering
For TREC 2006, the CRM114 team considered several different hypothesis on the topic of spam filtering. The hypothesis were that: 1 Spammers were changing tactics to successfully evade contentbased spam filters; 2 A pretrained database of known spam and nonspam improves overall accuracy; 3 Repeated training methods are more effective than singlepass Train Only Errors training 4 KNN/Hyperspace...
متن کاملAN EVALUATION OF FILTERING TECHNIQUES IN A NAÏVE BAYESIAN ANTI-SPAM FILTER by
An efficient anti-spam filter that would block all unsolicited messages i.e. spam, without blocking any legitimate messages is a growing need. To address this problem, this report takes a statistically-based approach, employing a Bayesian anti-spam filter, because it is content-based and self-learning (adaptive) in nature. We train the filter, using a large corpus of legitimate messages and spa...
متن کاملA Critical Analysis of Financial Fraud Spam in English in Terms of Persuasive Strategies: Personalization, Presupposition, and Lexical Choices
The term ‘spam’ addresses unsolicited emails sent in bulk; therefore, the term‘financial fraud spam’ refers to unwanted bulk emails in which different tricks and techniques areemployed to swindle money from the recipients. Estimates show that more than 80% of worldwideemail traffic in 2011 was spam. It should be noted that while the number of daily spam emails in2002 was 2.4 billion, this numbe...
متن کامل