• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.47-49
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• 2009

본 연구에서는 이메일 사용자별로 제공받은 사용자 선호 정보 대상으로 EM 클러스터링을 수행하여 사용자 클러스터를 만든 후, 사용자 클러스터들의 이메일 반응 분포를 계산함으로써 사용자 취향에 따라 동일한 이메일에 대해서도 서로 다른 반응을 가질 수 있다는 사실을 확인하려고 한다. 그 결과로부터 현재의 내용기반 방식과는 다르게 사용자 선호도를 고려한 스팸 메일 필터 구축 방법을 제안한다.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1092-1100
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• 2004

An E-mails have regarded as one of the most popular methods for exchanging information because of easy usage and low cost. Meanwhile, exponentially growing unwanted mails in user's mailbox have been raised as main problem. Recognizing this issue, Korean government established a law in order to prevent e-mail abuse. In this paper we suggest hybrid spam mail filtering system using weighted Bayesian classifier which is extended from naive Bayesian classifier by adding the concept of preprocessing and intelligent agents. This system can classify spam mails automatically by using training data without manual definition of message rules. Particularly, we improved filtering efficiency by imposing weight on some character by feature extraction from spam mails. Finally, we show efficiency comparison among four cases - naive Bayesian, weighting on e-mail header, weighting on HTML tags, weighting on hyperlinks and combining all of four cases. As compared with naive Bayesian classifier, the proposed system obtained 5.7% decreased precision, while the recall and F-measure of this system increased by 33.3% and 31.2%, respectively.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.35-36
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• 2017

이메일 서비스 사용자들은 스패머가 무차별적으로 발송하는 스팸메일에 의한 정신적 경제적 피해를 입고 있다. 이러한 피해를 막기 위해 필터링, RBL (Real-time Blackhole List)과 같은 스팸차단 기법이 등장하였고 많은 메일서버에서 사용되고 있다. 그러나 이는 스팸메일의 근본적인 원인은 해결하지 못하며, 높은 차단율을 유지하기 위해서는 지속적인 관리 및 업데이트가 필요하다. 이러한 한계점을 극복하기 위한 기법으로 송신자 자가인증 기법이 있다. 본 논문에서는 송신자 자가인증 기법을 적용하여, 스팸메일을 근본적으로 차단하고 지속적인 업데이트가 필요 없는 스팸차단 서버 및 애플리케이션을 구현하였다.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.853-862
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• 2003

Many more use e-mail purely on a personal basis and the pool of e-mail users is growing daily. Also, the amount of mails, which are transmitted in electronic commerce, is getting more and more. Because of its convenience, a mass of spam mails is flooding everyday. And yet automated techniques for learning to filter e-mail have yet to significantly affect the e-mail market. This paper suggests Web Mail Filtering Agent for Personalized Classification, which automatically manages mails adjusting to the user. It is based on web mail, which can be logged in any time, any place and has no limitation in any system. In case new mails are received, it first makes some personal rules in use of the result of observation ; and based on the personal rules, it automatically classifies the mails into categories according to the contents of mails and saves the classified mails in the relevant folders or deletes the unnecessary mails and spam mails. And, we applied Bayesian Algorithm using Dynamic Threshold for our system's accuracy.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.64-71
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• 2006

Electronic mail (E-mail) is an integral part of communication for the recent Internet users. However, e-mail has also come to serve as a means to support flood of unwanted spam mails and junk mails having bad purposes. This paper was conducted in order to develop an intelligent e-mail system using user behavior pattern that can prevent these unnecessary information and enable the user to enjoy communication via e-mail in a cleaner environment. The concentrated analysis of the user behavior in terms of using e-mail functions has resulted in better classification between unnecessary and necessary information, thereby facilitating faster disposal of spam mails.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.409-416
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• 2006

In this paper, we propose an algorithm for extracting text regions from spam-mail images using color layer. The CLTE(color layer-based text extraction) divides the input image into eight planes as color layers. It extracts connected components on the eight images, and then classifies them into text regions and non-text regions based on the component sizes. We also propose an algorithm for recovering damaged text strokes from the extracted text image. In the binary image, there are two types of damaged strokes: (1) middle strokes such as 'ㅣ' or 'ㅡ' are deleted, and (2) the first and/or last strokes such as 'ㅇ' or 'ㅁ' are filled with black pixels. An experiment with 200 spam-mail images shows that the proposed approach is more accurate than conventional methods by over 10%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.348-354
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• 2005

These days, Electronic mail is being used in everyday's life. And on the other hand, we are facing spam mails' problems. Spam mails are widely used by means of marketing in e-Commerce. To block these spam mails, we are using filtering or pricing systems. But these solutions are raising other problems such as impediment in reception or availability caused by false positive or payment resistance. To solve these problems, we propose an Indirect Model on Electronic Mail Control System(IMEMCS) which controls an unsolicited electronic mail and prevents an useful electronic mail from discarding. We design and implement the IMEMCS to enhance the usefulness and the availability. Being tested the IMEMCS to verify the usability and the efficiency, it gave us a very successful result.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.568-570
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• 2005

인터넷의 급속한 성장으로 인터넷과 E-mail의 사용자가 증가하게 되면서, E-mail은 많은 사람들이 정보를 주고 받는 대표적인 통신수단의 하나로 자리 잡게 되었다. 그러나, 편리하고 비용이 거의 들지 않기 때문에 개인이나 업체들의 광고 수단으로 악용되고 있으며, 이에 따라 스팸 메일로 인한 시간과 비용의 낭비가 크게 증가하고 있다. 본 논문에서는 메시지 규칙에 기반을 둔 필터링 방식이 아닌 동보 전송 형태의 스팸 메일을 차단할 수 있는 방법을 연구한다.

• Convergence Security Journal
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• v.20 no.3
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• pp.61-69
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• 2020

Since spear-phishing mail attacks focus on a particular target persistently to collect and take advantage of information, it can incur severe damage to the target as a part of the intelligent and new attacks such as APT attacks and social engineering attacks. The usual spam filtering services can have limits in countering spear-phishing mail attacks because of different targets, goals, and methods. In this paper, we analyze mail security services of several enterprises hosted by midium and small-sized enterprises with relatively security vulnerabilities in order to see whether their services can effectively respond spear-phishing mail attacks. According to the analysis result, we can say that most of mail security hosting services lack in responding spear-phishing mail attacks by providing functions for mainly managing mails including spam mail. The analysis result can be used as basic data to extract the effective and systematic countermeasure.

• The KIPS Transactions:PartC
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• v.13C no.6 s.109
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• pp.733-740
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• 2006

Spam Message has been Causing widespread damages on the Internet. One source of the problems is rooted from an anonymously posted message in the bulletin board in Internet communities. This type of the Spam messages tries to advertise products, to harm other's reputation, to deliver religious messages and so on. In this paper we present the Spam message filtering using the Bayesian approach. In order to increase usefulness of the Spam filter in the bulletin board in Internet communities, we made the Spam filter which can divide the Spam message into six categories such as advertisement, pornography, abuse, religion and other. The test conducted against messages posted on the popular web sites.