A Survey on Bio-Inspired Method for Detection of Spamming

A Survey on Bio-Inspired Method for Detection of Spamming

Mebarka Yahlali
DOI: 10.4018/IJSITA.2017070101
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The objective of this work is to show the importance of bi-inspiration SPAM filtering. To achieve this goal, the author compared two methods: Social bees vs inspiration from the Human Renal. The inspiration is taken from a biological model. Messages are indexed and represented by the n-gram words and characters independent of languages (because message can be received in any language). The results are promising and provide an important way for the use of this model for solving other problems in data mining. The author starts this article with a short introduction where the readers will see the importance of IT security—especially today. The author then explains and experiments on a two original meta-heuristics and explains the natural model and then the artificial model.
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2. State Of The Art

Among the anti-spam techniques exist in the literature include those based on machine learning and those not based on machine learning (c.f. Figure 1):

Figure 1.

SPAM Filtering approaches


There are two types of approaches for the detection and the filtering of SPAM (see Figure 1): the approach that is not based on Machine Learning and the Machine Learning-Based Approach.

2.1. The Approach Non-Based on Machine Learning

This approach consists of using one of the techniques or strategies of detection and filtering of SPAM as analysis of contents, black-lists, white-lists and authentication of a mailbox or a heuristic and meta-heuristics.

2.1.1. Content Analysis

Content analysis is an application implemented on the mail server as a complement to the user's mail application. Its role is to give a probability to an email to be a SPAM (or HAM) according to its contents.

2.1.2. Block List, Blacklist, Whitelist and the Authentication of Mailbox

The block list contains viral email’s addresses so that we should block any email that is sent from one of these addresses. It is filled and modified by the end who are not enough competent in computing will not be able to use this technique effectively and appropriately.

The principles of the legal computing to verify the signature of the email's author (authenticate the physical or real sender) and to trace an email to detect proxies and diversions of routing which the spammers use to bypass the other techniques of detection and filtering of SPAM.

2.1.4. Meta-Heuristics

Many of meta-heuristics have been proposed. Among these remarkable works, we can quote the Modelling of immune systems for the detection and the filtering of SPAM, meta-heuristic based on Artificial neural network with three layers, social bees for the filtering of the SPAM.

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