• Journal of the Korea Society for Simulation
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• v.16 no.3
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• pp.75-87
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• 2007

As the VoIP service quality is getting better and many shortcomings are being overcome, users are getting interested in this service. Also, there are several additional features that provide a convenience to users such as presence service, instant messaging service and so on. But, as there are always two sides of rein, some security issues have users hesitate to make use of it. This paper deals with one of the issues, the VoIP spam problem. We took into account the signal pattern of voice message in spam call and we have constructed voice signal models of normal call, normal call with noise and spam call. Each voice signal case is inserted into our spam decision algorithm which detects the spam calls based on the amount of information in the call signal. We made use of the DEVS-$Java^{TM}$ for our modeling and simulation. The contribution of this work is in suggestion of a way to detect voice spam call signal and testing of the method using modeling and simulation methodology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2595-2602
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• 2010

This paper introduces a mobile spam filtering system that considers the style of short text messages sent to mobile phones for detecting spam. The proposed system not only relies on the occurrence of content words as previously suggested but additionally leverages the style information to reduce critical cases in which legitimate messages containing spam words are mis-classified as spam. Moreover, the accuracy of spam classification is improved by normalizing the messages through the correction of word spacing and spelling errors. Experiment results using real world Korean text messages show that the proposed system is effective for Korean mobile spam filtering.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.17-20
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• 2005

In this work, we compared several feature selection methods in the field of spam mail filtering. The proposed fuzzy inference method outperforms information gain and chi squared test methods as a feature selection method in terms of error rate. In the case of junk mails, since the mail body has little text information, it provides insufficient hints to distinguish spam mails from legitimate ones. To address this problem, we follow hyperlinks contained in the email body, fetch contents of a remote web page, and extract hints from both original email body and fetched web pages. A two-phase approach is applied to filter spam mails in which definite hint is used first, and then less definite textual information is used. In our experiment, the proposed two-phase method achieved an improvement of recall by 32.4% on the average over the $1^{st}$ phase or the $2^{nd}$ phase only works.

• Journal of Korea Multimedia Society
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• v.13 no.6
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• pp.841-848
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• 2010

Conventional filters using email header and body information equally judge whether an incoming email is spam or not. However this is unrealistic in everyday life because each person has different criteria to judge what is spam or not. To resolve this problem, we consider user preference information as well as email category information derived from the email content. In this paper, we have developed a personalized anti-spam system using ontologies constructed from rules derived in a data mining process. The reason why traditional content-based filters are not applicable to the proposed experimental situation is described. In also, several experiments constructing classifiers to decide email category and comparing classification rule learners are performed. Especially, an ID3 decision tree algorithm improved the overall accuracy around 17% compared to a conventional SVM text miner on the decision of email category. Some discussions about the axioms generated from the experimental dataset are given too.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.32-37
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• 2009

Recently, electronic mail(E-mail) is the most popular communication manner in our society. In such conventional environments, spam increasingly congested in Internet. In this paper, Chinese spam could be effectively detected using text and image features. Using text features, keywords and reference templates in Chinese mails are automatically selected using genetic algorithm(GA). In addition, spam containing a promotion image is also filtered out by detecting the text characters in images. Some experimental results are given to show the effectiveness of our proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8B
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• pp.521-528
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• 2007

This paper proposes a message authentication scheme to resist potential spam threats in SIP-based VoIP services. Our scheme applies the extended HTTP digest authentication mechanism between the inbound proxy and the UAS to verify that a service request is coming through the valid inbound proxy. The proposed scheme is simple and requires minimal modification the current SIP standards, and effective to filter invalid peer-to-peer spam calls. In this paper, an experimental spam attack using modified open source was tested on a commercial VoIP networks to exploit the possibility of spam attacks in real environment.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.3
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• pp.192-202
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• 2017

This study develops a text spam filtering system for Facebook based on two variable categories: keywords learned from Instagram and meta-information of Facebook posts. Since there is no explicit labels for spam/ham posts, we utilize hash tags in Instagram to train classification models. In addition, the filtering accuracy is enhanced by considering meta-information of Facebook posts. To verify the proposed filtering system, we conduct an empirical experiment based on a total of 1,795,067 and 761,861 Facebook and Instagram documents, respectively. Employing random forest as a base classification algorithm, experimental result shows that the proposed filtering system yield 99% and 98% in terms of filtering accuracy and F1-measure, respectively. We expect that the proposed filtering scheme can be applied other web services suffering from massive spam posts but no explicit spam labels are available.

• Journal of Information Management
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• v.38 no.4
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• pp.48-67
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• 2007

The economic burden which our society has to take exceeds the benefit that it becomes by the free circulation of information. Problems such as inconvenience or inequality between people can also occur since the regulation task of spam e-mail or SMS is imposed on two organs; the Department of Information and Communication and Free Trade Commission. The dualization of regulation separates related laws, which makes exception according to the $\ulcorner$Law on Information Communication Usage and Information Protection$\lrcorner$ or poses double regulation toward the same case. The spam prevention activity at free hands of information communication network provider such as portal site or mobile communication has many limitations along with comparison and analysis of spam regulations abroad. Therefore, examinations on legal obligation such as service restriction, identification and technical measure to spam prevention is needed. This study focuses on making the scope of spam regulation clear by considering the domestic related laws and the general environment of industry, on enacting law which regulates spam including advertisement and on deducting essential facts in enacting or modifying related laws and thus, deducting the form and contents of spam regulation law which is most decent in our domestic environment.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.20-29
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• 2007

Although E-mail system is considered as a most important communication media, 'Spam' is flooding the Internet with many copies of the same message, in an attempt to force the message on people who would not otherwise choose to receive it. Most spam is commercial advertising, often for dubious products, get-rich-quick schemes, or quasi-legal services. Therefore advanced anti-spam techniques are required to basically reduce its transmission volume on sender mail server or MTA, etc. In this study, we propose a new sender authentication model with encryption function based on modified DomainKey with SMS for Spam mail protection. From the SMS message, we can get secret information used for verification of its real sender on e-mail message. And by distributing this secret information with SMS like out-of-band channel, we can also combine proposed modules with existing PGP scheme for secure e-mail generation and authentication steps. Proposed scheme provide enhanced authentication function and security on Spam mail protection function because it is a 'dual mode' authentication mechanism.

• The KIPS Transactions:PartC
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• v.13C no.2 s.105
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• pp.259-266
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• 2006

As the volume of spam has increased to extreme levels, many anti-spam filtering techniques have been proposed. Among these techniques, the machine-Loaming filtering technique is one of the most popular filtering techniques. In this paper, we propose a machine-learning spam filtering technique based on the neural network, the genetic algorithm and the $X^2$-statistic. This proposed filtering technique is designed to overcome the problems in existing filtering techniques, and to achieve high spam filtering accuracy. It is able to classify spam and legitimate emil with 95.25 percent and 95.31 percent accuracy. This accuracy of the sum filtering is 7.75 percent and the 12.44 percent higher than rule-based filtering and the Bayesian filtering technique, respectively.