a method of extracting malicious expressions in bulletin board systems by using context analysis

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.

A method of extracting malicious expressions in bulletin board systems by using context analysis

Presenter: Jun-Yi Wu　Authors: Hiroshi Hanafusa, Kazuhiro Morita, Masao Fuketa, Jun-ichi Aoe

2011 IPM

國立雲林科技大學National Yunlin University of Science and Technology

Intelligent Database Systems Lab

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I. M.Outline

Motivation Objective Methodology Experiments Conclusion Comments

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Intelligent Database Systems Lab

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I. M.Motivation

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The extracting scheme of the traditional method depends on words or a sequence of words without considering contexts of articles.

To takes a lot of human efforts to alert malicious articles.

Malicious expression text Non-malicious expression text

Intelligent Database Systems Lab

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I. M.Objective

To presents a new context filtering algorithm to reduce the effort of human and to improve the rate of false positive without degrading the rate of false negative.

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Intelligent Database Systems Lab

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I. M.Methodology

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The presented system Rule-based extracting knowledge Multi-attribute matching

Intelligent Database Systems Lab

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I. M.Methodology

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The presented system

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I. M.Methodology

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The presented system The outline of context analysis

Malicious expression text Non-malicious expression text

Intelligent Database Systems Lab

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I. M.Methodology

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The presented system Inadequate and crime expressions

Inadequate Crime

Abuse、 Discrimination、 Dating Service Website、 Obscenity

Murder&Violence、 Explosion&Arson、 Crime Material、 Drug

Intelligent Database Systems Lab

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I. M.Methodology

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Rule-based extracting knowledge Definition of multi-attribute rules

For example : “He kills someone”

STR: string, or, word spelling.CAT: category by general concepts, or a part of speeches.SEM: sematic information

Intelligent Database Systems Lab

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I. M.Methodology

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Multi-attribute matching Construction of machines(MAPM) Goto and out function

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I. M.Methodology

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Multi-attribute matching Procedure

For example : “I get a strong sward”

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I. M.Experiments

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I. M.Experiments

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I. M.Experiments

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I. M.Experiments

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Time evaluation and error analysis

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I. M.Conclusion

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The presented method MULTI is a very useful approach for filtering services for inadequate expressions.

It is difficult task to register new words and expressions into dictionaries together with their categories and semantics.

The rules bases of the presented method MULTI is building for frequent expressions step by step, but there are difficult problems as shown in the following examples:

‘‘RQJmcf2O” kill ‘‘Aaaaqqqbbb”

Intelligent Database Systems Lab

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I. M.Comments

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Advantage Many examples

Drawback Some mistakes

Application Information retrieval Context analysis