• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.70-72
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• 2002

전자우편(E-Mail)은 아주 편리한 통신수단이지만, 무분별한 광고성 스팸메일(Spam-Mail)의 침입과 무단으로 타인의 메일을 가로채거나 변조할 수 있기 때문에 메일의 신뢰성이 문제가 되고 있다. 본 연구에서는 이와 같은 문제를 해결하기 위하여 메일의 제목과 내용의 문자열을 분석하여 자동으로 스팸메일을 구분할 뿐만 아니라 보안도구인PGP(Pretty Good Privacy)를 이용하여 메일을 암호화하고 인증하여 근본적으로 스팸메일을차단하는 시스템을 개발한다.

• The Magazine of the IEIE
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• v.22 no.2
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• pp.90-98
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• 1995

• 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%.

• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.689-696
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• 2004

The conventional email method based on a recipient mailbox has a structural weakness, which may cause the spam message problem and the extreme waste of recipient mailbox space, and also require an explicit recipient notification scheme. This paper proposes a new email method based on a sender mailbox and evaluates its performance. Under the new email method, a message is stored at sender mailbox instead of recipient one until an intended recipient reads the message, so that the burden of mailbox management such as removing spam message is now shifted to sender side. And also a sender can confirm whether an intended recipient has read his or her message by simply rummaging his or her sender mailbox. The results of Performance evaluation show that 75% of mailbox space and 90% of message traffic are reduced in conditions that the portions of spam message and multicasting message are 90% and 80%, respectively.

• Journal of KIISE
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• v.44 no.11
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• pp.1231-1235
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• 2017

Given the network structure in online social network, it is important to determine a way to distinguish spam accounts from the network features. In online social network, the service provider attempts to detect social spamming to maintain their service quality. However the spammer group changes their strategies to avoid being detected. Even though the spammer attempts to act as legitimate users, certain distinguishable structural features are not easily changed. In this paper, we investigate a way to generate meaningful network structure features, and suggest spammer detection method using recursive structural features. From a result of real-world dataset experiment, we found that the proposed algorithm could improve the classification performance by about 8%.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.4
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• pp.280-286
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• 2009

Purpose: The aim of this study was to evaluate the hemodynamic changes after endovascular stenting in patients with unilateral middle cerebral artery (MCA) stenosis using statistical probabilistic anatomical mapping (SPAM) analysis of basal/acetazolamide (ACZ) Tc-99m ECD brain perfusion SPECT. Materials and Methods: Eight patients (3 men and 5 women, 64.8$\pm$10.5 years) who underwent endovascular stenting for unilateral MCA stenosis were enrolled. Basal/ACZ Tc-99m ECD brain perfusion SPECT studies were performed by one-day protocol before and after stenting. Using SPAM analysis, we compared basal cerebral perfusion (BCP) counts and cerebrovascular reserve (CVR) index of the MCA territory before stenting with those after stenting. Results: After stenting, no patient had any complication nor additional stroke. In SPAM analysis, 7 out of the 8 patients had improved BCP counts of the MCA territory and 7 out of the 8 patients had improved CVR index of the MCA territory after stenting. Before stenting, the mean BCP counts and CVR index in the affected MCA territory were 47.1$\pm$2.2 ml/min/100 g and -2.1$\pm$2.9%, respectively. After stenting, the mean BCP counts and CVR index in the affected MCA territory were improved significantly (48.3$\pm$2.9 ml/min/100 g, p =0.025 and 0.1$\pm$1.3%, p =0.036). Conclusion: This study revealed that SPAM analysis of basal/ACZ brain perfusion SPEG would be helpful to evaluate hemodynamic efficacy of endovascular stenting in unilateral MCA stenosis.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.43-48
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• 2010

Useful emails influence on consumers' purchase behavior and activate them to visit retail stores. Regular contact with consumers by e-mail has positive effects on brand loyalty. However, email marketing has a limitation. Spam now accounts for over half of all e-mail traffic. The increase of email users has resulted in the dramatic increase of spam emails during the past few years. In this paper, we proposed an ontology-based system offering personalized email services to overcome such limitation. Our method is not the ontology-driven spam filtering, but a personalized content service considering personal interests and relations among people by using FOAF and domain ontologies. Our system was successfully tested in email marketing domain.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1348-1375
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• 2018

Support Vector Machine (SVM) is a well-known machine learning classification algorithm, which has been widely applied to many data mining problems, with good accuracy. However, SVM classification speed decreases with increase in dataset size. Some applications, like video surveillance and intrusion detection, requires a classifier to be trained very quickly, and on large datasets. Hence, this paper introduces two filter-based instance selection techniques for optimizing SVM training speed. Fast classification is often achieved at the expense of classification accuracy, and some applications, such as phishing and spam email classifiers, are very sensitive to slight drop in classification accuracy. Hence, this paper also introduces two wrapper-based instance selection techniques for improving SVM predictive accuracy and training speed. The wrapper and filter based techniques are inspired by Cuckoo Search Algorithm and Bat Algorithm. The proposed techniques are validated on three popular e-fraud types: credit card fraud, spam email and phishing email. In addition, the proposed techniques are validated on 20 other datasets provided by UCI data repository. Moreover, statistical analysis is performed and experimental results reveals that the filter-based and wrapper-based techniques significantly improved SVM classification speed. Also, results reveal that the wrapper-based techniques improved SVM predictive accuracy in most cases.

• 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.