• Journal of Information Technology Services
• /
• v.13 no.3
• /
• pp.299-308
• /
• 2014

Due to indiscriminately received spam messages on information society, spam messages cause damages not only to person but also to our community. Nowadays a lot of spam filtering techniques, such as blocking characters, are studied actively. Most of these studies are content-based spam filtering technologies through machine learning.. Because of a spam message transmission techniques are being developed, spammers have to send spam messages using term spamming techniques. Spam messages tend to include number of nouns, using repeated words and inserting special characters between words in a sentence. In this paper, considering three features, SPSS statistical program were used in parameterization and we derive the equation. And then, based on this equation we measured the performance of classification of spam messages. The study compared with previous studies FP-rate in terms of further minimizing the cost of product was confirmed to show an excellent performance.

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

• Journal of Digital Contents Society
• /
• v.16 no.5
• /
• pp.815-822
• /
• 2015

By the growing of SMS phishing victims, applications for processing spam messages are being released in succession. However most spam messages that cleverly modified the content like separating the consonants and vowels are fail to be filtered. In this paper, we implemented an application 'AntiSpam' which is able to identify spam strings in the text message to solve this problem. 'AntiSpam' searches spam strings in the text message by using set-based POI search algorithm, and then calculate the possibility of whether it is spam or not in accordance with the search results. In addition, it catches skillfully disguised spam messages in order to avoid missing the spam filtering. Users, who received a message, can check the result in spam message possibility decision result and the contents of the message and they can choose how to handling the message.

• KIISE Transactions on Computing Practices
• /
• v.23 no.1
• /
• pp.57-64
• /
• 2017

Short message service (SMS) is one of the most important communication methods for people who use mobile phones. However, illegal advertising spam messages exploit people because they can be used without the need for friend registration. Recently, spam message filtering systems that use machine learning have been developed, but they have some disadvantages such as requiring many calculations. In this paper, we implemented a spam message filtering system using the set-based POI search algorithm and sentence similarity without servers. This algorithm can judge whether the input query is a spam message or not using only letter composition without any server computing. Therefore, we can filter the spam message although the input text message has been intentionally modified. We added a specific preprocessing option which aims to enable spam filtering. Based on the experimental results, we observe that our spam message filtering system shows better performance than the original set-based POI search algorithm. We evaluate the proposed system through extensive simulation. According to the simulation results, the proposed system can filter the text message and show high accuracy performance against the text message which cannot be filtered by the 3 major telecom companies.

• The KIPS Transactions:PartC
• /
• v.18C no.2
• /
• pp.61-70
• /
• 2011

Even though internet community is becoming the basic communication tool with rapidly changing internet environment, its damage is on the rise due to increasing spam messages of unspecified individuals. Currently, various methods to block spam mails, but studies on block spam messages from being automatically posted in community are still insufficient. This study suggested methods to block spam messages in internet community by collecting spam messages posted in internet community to analyze characteristics and frequencies of the messages and create block regulations. It collects spam messages of all messages saved in database of internet community, analyze the collected messages to create normalized rules that can define spam messages, and inspect spam messages among posted messages by using the regulations to block them. The suggested method has a structure that can block various types of spam messages by using information of spam messages collected and flexibly deal with changing spam message types.

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

• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.7
• /
• pp.271-276
• /
• 2014

Short message service(SMS) in a mobile communication environment is a very convenient method. However, it caused a serious side effect of generating spam messages for advertisement. Those who send spam messages distort or deform SMS sentences to avoid the messages being filtered by automatic filtering system. In order to increase the performance of spam filtering system, we need to recover the distorted sentences into normal sentences. This paper proposes a method of normalizing the various types of distorted sentence and extracting keywords through automatic word spacing and compound noun decomposition.

• The KIPS Transactions:PartC
• /
• v.11C no.5
• /
• pp.689-696
• /
• 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 Electrical Engineering and Technology
• /
• v.10 no.1
• /
• pp.401-407
• /
• 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.

• Smart Media Journal
• /
• v.7 no.4
• /
• pp.24-29
• /
• 2018

Text analysis technique for natural language processing in deep learning represents words in vector form through word embedding. In this paper, we propose a method of constructing a document vector and classifying it into spam and normal text message, using word embedding and deep learning method. Automatic spacing applied in the preprocessing process ensures that words with similar context are adjacently represented in vector space. Additionally, the intentional word formation errors with non-alphabetic or extraordinary characters are designed to avoid being blocked by spam message filter. Two embedding algorithms, CBOW and skip grams, are used to produce the sentence vector and the performance and the accuracy of deep learning based spam filter model are measured by comparing to those of SVM Light.