• Corpus ID: 15903653

A Case Study of User-Level Spam Filtering

  title={A Case Study of User-Level Spam Filtering},
  author={Kamini Bajaj and Josef Pieprzyk},
  booktitle={Artificial Intelligence and Symbolic Computation},
There are number of Anti-Spam filters that have reduced the amount of email spam in the inbox but the problem still continues as the spammers circumvent these techniques. The problems need to be addressed from different aspects. Major problem for instance arises when these anti-spam techniques misjudge or misclassify legitimate emails as spam (false positive); or fail to deliver or block spam on the SMTP server (false negative); thus causing a staggering cost in loss of time, effort and finance… 

Figures from this paper

A Multi-layer Model to Detect Spam Email at Client Side

This paper proposes a multi-layer model that imposes, on top of SpamBayes, a second layer of non-textual filtering that exploits alternative machine learning techniques and improves the accuracy of classification and eliminates the grey email into spam and ham emails.

Email Classification Using Artificial Neural Network

A method for spam filtering using Artificial Neural Network to predict whether an email is spam or not is presented.

Using Fuzzy Logic for Email Spam Filtering

The approach described in this paper is to classify the spam mails according to degree of spam content using spam word ranking database and fuzzy rules.

A Hybrid E-Mail Spam Filtering Technique using Data Mining Approach

In the proposed work the traditionally available techniques of spam filtering are investigated and a new technique using hybrid methodology is presented, which incorporates the Bayesian classifier and the neural network.

An Intellect Learning on E-mail Security and Fraud, Spam and Phishing

  • Kumar Prof.Dr.P.S.Jagadeesh
  • Computer Science
  • 2015
In this intellect learning, the authors’ primary interest is to make a healthy charge on phishing, spam and email fraud towards the wealthy personal information and realm.

Identification of Function Points in Software Specifications Using Natural Language Processing. (Identification des points de fonction dans les spécifications logicielles à l'aide du traitement automatique des langues)

This research focuses on functional size estimation metrics commonly known as Function Point Analysis (FPA) that estimates the size of a software in terms of the functionalities it is expected to deliver from a user’s point of view.



Effective Anti-Spam Strategies in Companies: An International Study

  • M. SiponenCarl Stucke
  • Business
    Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06)
  • 2006
The 500 biggest companies in the US and Finland are explored, finding marginal support that having an e-mail address available on the Internet correlates with the amount of spam one receives and that Internet Service Providers and legislation should take strong action against spam.

An Empirical Study of Spam and Spam Vulnerable email Accounts

This study collected 400 thousand spam mails from a spam trap set up in a corporate mail server for a period of 14 months form January 2006 to February 2007 and classified spam based on attachment and contents.

Spam filtering using spam mail communities

The new approach does not base itself on any prejudices about spam and can be used to block nonspam nuisance mails also and support users who would want selective blocking of spam mails based on their interests.

A survey of learning-based techniques of email spam filtering

An overview of the state of the art of machine learning applications for spam filtering, and of the ways of evaluation and comparison of different filtering methods.

Spam filtering: Comparative analysis of filtering techniques

  • M. PaswanP. BalaG. Aghila
  • Computer Science
    IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012)
  • 2012
This paper provides the details about various spam filtering techniques and compares several techniques including its advantages, disadvantages, accuracy, etc.

Architecture of Adaptive Spam Filtering Based on Machine Learning Algorithms

An adaptive spam filtering model has been proposed based on Machine learning (ML) algorithms which will get better accuracy by reducing FP problems and a dynamic feature selection (DFS) technique also proposed in this paper for getting better accuracy.

Filtering spam e-mail with Generalized Additive Neural Networks

The performance of a Generalized Additive Neural Network on a publicly available e-mail corpus is investigated in the context of statistical spam filtering and suggests it may be utilized to flag spam e-mails in order to prioritize the reading of messages.

Miracle cures and toner cartridges:finding solutions to the spam problem

The exponential growth in unsolicited commercial email, or spam, over the past several years has resulted in a degradation of e-mail as a useful medium for information interchange. Spam traffic

A survey of emerging approaches to spam filtering

This survey focuses on emerging approaches to spam filtering built on recent developments in computing technologies, which include peer-to-peer computing, grid computing, semantic Web, and social networks.