• The Journal of the Korea Contents Association
• /
• v.9 no.7
• /
• pp.45-56
• /
• 2009

There are many internet users who collect the public opinions and express their opinions for internet news or blog articles through the replying comment on online community. But, it is hard to search and explore useful messages on web blogs since most of web blog systems show articles and their comments to the form of sequential list. Also, spam and malicious comments have become social problems as the internet users increase. In this paper, we propose a clustering and visualizing system for responding comments on large-scale weblogs, namely 'Daum AGORA,' using similarity analysis. Our system shows the comment clustering result as a simple screen view. Our system also detects spam comments using Needleman-Wunsch algorithm that is a well-known algorithm in bioinformatics.

• The KIPS Transactions:PartB
• /
• v.10B no.7
• /
• pp.853-862
• /
• 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 Korean Institute of Communications and Information Sciences
• /
• v.32 no.12B
• /
• pp.750-757
• /
• 2007

This paper analyzes spam threats and proposes key exchange scheme for user authentication and SDP encryption to protect potential spam threats in SIP-based VoIP services. The existing HTTP digest authentication scheme exchanges many message because challenge is sent for every establishment of the session and doesn't provide a confidentiality of SDP. To protect SPIT, our scheme exchanges initial nonce and a session master key for authentication and SDP encryption during registration. In our scheme, the challenge and response procedure is not necessary and the communication overhead is much less than applying S/MIME or TLS.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.47 no.2
• /
• pp.95-102
• /
• 2010

This paper proposes a SPIT(Spam over IP Telephony) prevention framework which is using expanded white-list in real-time VoIP environment. The existing schemes are vulnerable to attack from spammers since they can continue to transfer SPIT upon changing their ID. And existing frameworks have experienced the time delay and overload as session initiates due to real-time operation. To solve these problems, the proposed scheme expands the scope of white lists by forming social networks using the white list, but it is to decide quickly whether pass a caller ID without searching the entire database. The proposed framework takes the three-stage architecture and the fast scoring system. The proposed framework minimize user's inconvenience and time delay for initiation of session, therefore, it is proper for real-time VoIP environment.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.5
• /
• pp.42-47
• /
• 2017

In the distribution of digital image, the median filtering is used for a forgery. This paper proposed the algorithm of a image forensics detection for the classification of median filtering. For the solution of this grave problem, the feature vector is composed of 42-Dim. The detected quantity 32, 64 and 128 of forgery image edges, respectively, which are processed by the Hough transform, then it extracted from the start-end point coordinates of the Hough Lines. Also, the Hough Peaks of the Angle-Distance plane are extracted. Subsequently, both of the feature vectors are composed of the proposed scheme. The defined 42-Dim. feature vector is trained in SVM (Support Vector Machine) classifier for the MF classification of the forged images. The experimental results of the proposed MF detection algorithm is compared between the 10-Dim. MFR and the 686-Dim. SPAM. It confirmed that the MF forensic classification ratio of the evaluated performance is 99% above with the whole test image types: the unaltered, the average filtering ($3{\times}3$), the JPEG (QF=90 and 70)) compression, the Gaussian filtered ($3{\times}3$ and $5{\times}5$) images, respectively.

• The Journal of the Convergence on Culture Technology
• /
• v.2 no.1
• /
• pp.79-85
• /
• 2016

Ransomware was a malicious code that active around the US, but now it spreads rapidly all over the world and emerges in korea recently because of exponential computer supply and increase in users. Initially ransomware uses e-mail as an attack medium in such a way that induces to click a file through the spam mail Pam, but it is now circulated through the smart phone message. The current trend is an increase in the number of damage, including attacks such as the domestic large community site by ransomware hangul version. Ransomware outputs a warning message to the user to encrypt the file and leads to monetary damages and demands for payment via bitcoin as virtual currency is difficult to infer the tracking status. This paper presents an analysis and solutions to damage cases caused by ransomware.

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

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.7
• /
• pp.1568-1576
• /
• 2015

This paper proposes a prediction reputation system for the anti-SPIT solution in real-time VoIP environment. Increased accuracy of the determination as to whether spam or not by deriving a threshold based on SPIT presence in the existing paper. The existing schemes need to get the user's feedback and/or have experienced the time delay and overload as session initiates due to real-time operation. To solve these problems, the proposed scheme predicts the reputation through the statistical analysis based on the period of session initiation of each caller and the call duration of each receiver. As per the second mentioned problem, this scheme performs the prediction before session initiation, therefore, it's proper for real-time VoIP environment.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.2
• /
• pp.47-52
• /
• 2016

The used digital images in the smart device and small displayer has been a downscaled image. In this paper, the detection of the downscaling image forgery is proposed using the feature vector according to the pixel value's gradients. In the proposed algorithm, AR (Autoregressive) coefficients are computed from pixel value's gradients of the image. These coefficients as the feature vectors are used in the learning of a SVM (Support Vector Machine) classification for the downscaling image forgery detector. On the performance of the proposed algorithm, it is excellent at the downscaling 90% image forgery compare to MFR (Median Filter Residual) scheme that had the same 10-Dim. feature vectors and 686-Dim. SPAM (Subtractive Pixel Adjacency Matrix) scheme. In averaging filtering ($3{\times}3$) and median filtering ($3{\times}3$) images, it has a higher detection ratio. Especially, the measured performances of all items in averaging and median filtering ($3{\times}3$), AUC (Area Under Curve) by the sensitivity and 1-specificity is approached to 1. Thus, it is confirmed that the grade evaluation of the proposed algorithm is 'Excellent (A)'.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.05a
• /
• pp.79-81
• /
• 2014

People increasingly rely on sources of information from E-commerce reviews. Product reviews is an important determinant of potential customers' buying choices. They are also utilized by product manufacturers to find problems of their products and to collect competitive intelligence information about their competitors. Unfortunately, it is well-known that many online product reviews are not made by genuine costumers of products. Reviewers could write some undeserving positive reviews to promote or fake negative reviews to defame some certain product, and we call them fake product reviews. Fake product review detection makes an attempt to detect fake reviews and removes them to restore the truthful ones for readers. To the best of our knowledge, there is still less published study on this problem. In this paper, we make a survey and an attempt to give a brief overview on fake product review detection. The related work of fake product review detection is presented including web spam and spam email. Then some methods to detect fake reviews are introduced and summarized. The trend of fake product review detection is concluded finally.