• Title/Summary/Keyword: E-mail Spam

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Improved Spam Filter via Handling of Text Embedded Image E-mail

  • Youn, Seongwook;Cho, Hyun-Chong
    • Journal of Electrical Engineering and Technology
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    • v.10 no.1
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    • pp.401-407
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    • 2015
  • The increase of image spam, a kind of spam in which the text message is embedded into attached image to defeat spam filtering technique, is a major problem of the current e-mail system. For nearly a decade, content based filtering using text classification or machine learning has been a major trend of anti-spam filtering system. Recently, spammers try to defeat anti-spam filter by many techniques. Text embedding into attached image is one of them. We proposed an ontology spam filters. However, the proposed system handles only text e-mail and the percentage of attached images is increasing sharply. The contribution of the paper is that we add image e-mail handling capability into the anti-spam filtering system keeping the advantages of the previous text based spam e-mail filtering system. Also, the proposed system gives a low false negative value, which means that user's valuable e-mail is rarely regarded as a spam e-mail.

The Exploratory Analysis for Spam Mail Data Using Correspondence Analysis

  • Shin, Yang-Kyu
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.735-744
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    • 2005
  • The number of electronic mail(E-mail) has been increased dramatically as a result of expanding internet and information technology. Although there are many conveniences of E-mail in the bright side, some serious problems occur because of E-mail in its dark side. One of the problems is spam-mail which is unsolicited mail and also called bulk mail. This paper presents a set of patterns of spam-mail occurrences within a week using the correspondence analysis. The correspondence analysis is an exploratory multivariate technique that converts data into a particular type of graphical display in which the rows and columns are depicted as points. One of the meaningful patterns is a great increment of adult and phishing related spam-mails at weekends so any spam-mail filters should be designed to cope with this pattern.

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Studying on Expansion of Realtime Blocking List Conception for Spam E-mail Filtering (스팸 메일 차단을 위한 RBL개념의 확장에 관한 연구)

  • Kim, Jong-Min;Kim, Hion-Gun;Kim, Bong-Gi
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.10
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    • pp.1808-1814
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    • 2008
  • In addition to RBL function, which is used to applying for spam e-mail filtering, as an effective way to deal with the recently widespread spam types, this paper proposes how to extract URL that was comprised in the original e-mail, apply it to RBL, and expand it. The BotNet, which is used to using for sending spam mails these days, has a problem that it is not able to solve with the distributed addresses of sent mails in spam e-mails. In general, as these spam e-mails are sent from the infected Zombi PC of individual user, the sent address itself is not efficient and is meaningless to use in RBL. As an effective way to filter spam e-mail sent by BotNet, this paper analyzes URLs that contained in the original spam e-mail and proposes how to effectively improve filter rate, based on the distribution data of URL site tempting users. This paper proposes the sending mechanism of spam e-mails from BotNet and the methods to realize those types of spam e-mails. In order to gather analyzable spam e-mails, this paper also carries out an experiment by configuring trap system of spam e-mail. By analyzing spam e-mails, which have been received during the certain period of experiment, this paper shows that the expanded RBL method, using URLs that contained in spam e-mails, is effective way to improve the filter distribution of spam e-mail.

An Architecture for Certificate and Agent Based E-mailing to Block Spam Mail

  • Nam, Sang-Zo
    • Journal of Intelligence and Information Systems
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    • v.9 no.2
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    • pp.39-50
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    • 2003
  • Deleting unsolicited email, popularly known as spam mail, is an annoying task for Internet users. Moreover, spam mail causes a variety of social problems. At present, legal restrictions cannot eradicate spam senders. As a result, many technical methods to eliminate spam mail such as spam filtering and online stamps have been introduced. However, the process of blocking spam mail can inadvertently result in suspension of indispensable or beneficial communication. In this paper, we propose a certificate and agent based emailing architecture that can block spam mail, while at the same time approve certified mail. This architecture can be accelerated by synergistic utilization of digital signature and electronic document interchange.

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A Proposed Architecture for Certificate and Agent Based E-mailing to Block Spam Mail

  • Nam, Sang-Zo
    • Proceedings of the KAIS Fall Conference
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    • 2003.11a
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    • pp.28-34
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    • 2003
  • Deleting unsolicited email, popularly known as spam mail, is an annoying task for Internet users. Moreover, spam mail causes a variety of social problems. At present, legal restrictions cannot eradicate spam senders. As a result many technical methods to eliminate spam mail such as spam filtering and online stamps have been introduced. However, the process of blocking spam mail can inadvertently result in suspension of indispensable or beneficial communication. In this paper, we propose a certificate and agent based emailing architecture that can block spam mail, while at the same time approve certified mail. This architecture can be accelerated by synergistic utilization of digital signature and electronic document interchange.

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An Automatic Spam e-mail Filter System Using χ2 Statistics and Support Vector Machines (카이 제곱 통계량과 지지벡터기계를 이용한 자동 스팸 메일 분류기)

  • Lee, Songwook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.05a
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    • pp.592-595
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    • 2009
  • We propose an automatic spam mail classifier for e-mail data using Support Vector Machines (SVM). We use a lexical form of a word and its part of speech (POS) tags as features. We select useful features with ${\chi}^2$ statistics and represent each feature using text frequency (TF) and inversed document frequency (IDF) values for each feature. After training SVM with the features, SVM classifies each email as spam mail or not. In experiment, we acquired 82.7% of accuracy with e-mail data collected from a web mail system.

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A Design of the SMBC for Improving Reliability of Blocking Spam Mail (스팸 메일 차단 신뢰도 향상을 위한 SMBC 플랫폼 설계)

  • Park Nho-Kyung;Han Sung-Ho;Seo Sang-Jin;Jin Hyun-Joon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.11B
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    • pp.730-735
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    • 2005
  • While the E-mail is a important way of fast communication in these days. it is real that the E-mail is often misused as a commercial advertisement method and creates many social problems. Even though various filtering techniques for blocking spam mails have been developed, reliability of mail systems is decreased by misreading normal mails as spam mails, i.e. false-positive errors. In this paper, the SMBC(Spam Mail Blocking Center) platform employing spam mail recovery method based on privacy information is proposed and designed. The SMBC is designed in frame layer based on spam blocking system of proxy sewer and can be physically implemented in various topology so that flexible development with layered module is possible. Using privacy information makes the proposed SMBC platform minimize processing load and false-positive error rates so that it can improve mail system reliabilities.

A Spam Mail Classification Using Link Structure Analysis (링크구조분석을 이용한 스팸메일 분류)

  • Rhee, Shin-Young;Khil, A-Ra;Kim, Myung-Won
    • Journal of KIISE:Software and Applications
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    • v.34 no.1
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    • pp.30-39
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    • 2007
  • The existing content-based spam mail filtering algorithms have difficulties in filtering spam mails when e-mails contain images but little text. In this thesis we propose an efficient spam mail classification algorithm that utilizes the link structure of e-mails. We compute the number of hyperlinks in an e-mail and the in-link frequencies of the web pages hyperlinked in the e-mail. Using these two features we classify spam mails and legitimate mails based on the decision tree trained for spam mail classification. We also suggest a hybrid system combining three different algorithms by majority voting: the link structure analysis algorithm, a modified link structure analysis algorithm, in which only the host part of the hyperlinked pages of an e-mail is used for link structure analysis, and the content-based method using SVM (support vector machines). The experimental results show that the link structure analysis algorithm slightly outperforms the existing content-based method with the accuracy of 94.8%. Moreover, the hybrid system achieves the accuracy of 97.0%, which is a significant performance improvement over the existing method.

Design and Implementation of The Spam E-Mail filtering System (스팸메일 차단 시스템 설계 및 구현)

  • 김진만;장종욱
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.11a
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    • pp.413-417
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    • 2002
  • E-mail was very particular way of communication in the past, but it becomes one of daily communication methods now. Due to E-mail has a property which is not complete for security, sometimes it is used for purpose of commercial or badthings, therefore it becomes the latest problem to keep off a Spam-mail and commercial advertising E-mail, many ways to keep off were perposed for it. In this paper, I explained how to sort and keep off these Spam-mail and commercial advertising E-mail with three way, prevention by server level, prevention by construction of network level, prevention by client level. we designed a prevention system for Spam-mail and implemented it by Visual Basic.

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Performance Improvement of Spam Filtering Using User Actions (사용자 행동을 이용한 쓰레기편지 여과의 성능 개선)

  • Kim Jae-Hoon;Kim Kang-Min
    • The KIPS Transactions:PartB
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    • v.13B no.2 s.105
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    • pp.163-170
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    • 2006
  • With rapidly developing Internet applications, an e-mail has been considered as one of the most popular methods for exchanging information. The e-mail, however, has a serious problem that users ran receive a lot of unwanted e-mails, what we called, spam mails, which cause big problems economically as well as socially. In order to block and filter out the spam mails, many researchers and companies have performed many sorts of research on spam filtering. In general, users of e-mail have different criteria on deciding if an e-mail is spam or not. Furthermore, in e-mail client systems, users do different actions according to a spam mail or not. In this paper, we propose a mail filtering system using such user actions. The proposed system consists of two steps: One is an action inference step to draw user actions from an e-mail and the other is a mail classification step to decide if the e-mail is spam or not. All the two steps use incremental learning, of which an algorithm is IB2 of TiMBL. To evaluate the proposed system, we collect 12,000 mails of 12 persons. The accuracy is $81{\sim}93%$ according to each person. The proposed system outperforms, at about 14% on the average, a system that does not use any information about user actions.