• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.111-118
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• 2012

In this paper, a technique wherein the DHCP server has a restriction in providing the IP address to the computers that has no malicious bot curing vaccine is proposed, so that users will cooperate in the curing of malicious bot to avoid inconvenience. In order to provide restricted ip address periodically, the DHCP server makes a request of vaccine installation check for user's computer. Proposed technique is effective in the curing of malicious bot, because it does not depend on specific systems or organizations.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.1
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• pp.47-55
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• 2009

Bot is a kind of worm/virus that is remotely controlled by a herder. Bot can be used to launch distributed denial-of-service(DDoS) attacks or send spam e-mails etc. Launching cyber attacks using malicious Bots is motivated by increased monetary gain which is not the objective of worm/virus. However, it is very difficult for infected user to detect this infection of Botnet which becomes more serious problems. This is why botnet is a dangerous, malicious program. The Bot DNS Sinkhole is a domestic bot mitigation scheme which will be proved in this paper as one of an efficient ways to prevent malicious activities caused by bots and command/control servers. In this paper, we analysis botnet activities over more than one-year period, including Bot's lifetime, Bot command/control server's characterizing. And we analysis more efficient ways to prevent botnet activities. We have showed that DNS sinkhole scheme is one of the most effective Bot mitigation schemes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.199-207
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• 2013

Recently, hacking is seen as a criminal activity beyond an activity associated with curiosity in the beginning. The malignant bot which is used as an attack technique is one of the examples. Malignant Bot is one of IRC Bots and it leaks user's information with attacker's command by attacking specified IP range. This paper will discuss an access method and a movement process by analyzing shadowbot which is a kind of a malignant Bot and will suggest possible countermeasure. This study has two distinct features. First, we analyze malignant Bot by analyzing tools such as VM ware. Second, we formulate a hypothesis and will suggest possible countermeasure through analyzing malignant Bot's access method and movement. Performance evaluation will be conducted by applying possible countermeasure to see if it can prevent attacks from malignant bot.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2885-2891
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• 2015

Twitter, one of online social network services, is one of the most popular micro-blogs, which generates a large number of automated programs, known as tweet bots because of the open structure of Twitter. While these tweet bots are categorized to legitimate bots and malicious bots, it is important to detect tweet bots since malicious bots spread spam and malicious contents to human users. In the conventional work, temporal information was utilized for the classficiation of human and bot. In this paper, by utilizing geo-tagged tweets that provide high-precision location information of users, we first identify both Twitter users' exact location and the corresponding timestamp, and then propose an improved two-stage tweet bot detection algorithm by computing an entropy based on spatio-temporal information. As a main result, the proposed algorithm shows superior bot detection and false alarm probabilities over the conventional result which only uses temporal information.

• Journal of Korea Game Society
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• v.15 no.4
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• pp.69-78
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• 2015

As the online game industry has been growing rapidly, more and more malicious activities to gain economic benefits have been reported as well. Game bot is one of the biggest problems in the online game industry. So we proposed a bot detection method based on the ERG theory of motivation for the first time. Most of the previous studies focused on behavior-based detection by monitoring patterns of the specific actions. In this paper, we applied the motivation theory to analyze user behaviors on a real game dataset. The result shows that normal users in the game followed the ERG theory of motivation in the same way as it works in real world. But in the case of game bots, the theory could not be applied because the game bot has specific reasons, unlike normal game users. We applied the ERG theory to users to distinguish game bot users from normal users. We detected the game bot with high accuracy of 99.78% by applying the theory.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2689-2694
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• 2012

In recent years, cyber crimes were intended to get financial benefits through malicious attempts such as DDoS attacks, stealing financial information and spam. Botnets, a network composed of large pool of infected hosts, lead such malicious attacks. The botnets have adopted several evasion techniques and variations. Therefore, it is difficult to detect and eliminate them. Current botnet solutions use a signature based detection mechanism. Furthermore, the solutions cannot cover broad areas enough to detect world-wide botnets. In this paper, we propose IRC (Internet Relay Chat) that is used to control the botnet communication in a session channel of IRC servers connected through the analysis of the relationship of the channel and the connection with the server bot-infected hosts and how to detect.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.457-459
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• 2004

최근 악성코드들의 주요한 특징 중 하나는 악성코드와 해킹기법이 결합된 형태이며 기존의 악성코드들 보다 더욱 공격 성향을 내포하고 있다는 점이다. 이러한 악성코드에는 대표적으로 IRC를 이용하는 Bot 계열 악성 코드들이 있으며 해킹과 결합되어 그 피해 또한 스팸성 악성코드들보다 심각하다. 또한 이러한 악성코드들은 다양한 변종이 신속하게 제작 및 유포되고 있어, 백신을 이용한 방어만으로는 적절히 대처할 수 없다는 문제점을 가지고 있다. 본 논문에서는 IRC를 이용하는 공격성 악성코드들을 분석하고, 이들 악성코드들을 효과적으로 탐색하여 감염 여부를 판단할 수 있는 악성 Bot 탐색 시스템의 설계 및 구현에 관하여 기술한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2878-2884
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• 2015

Twitter, one of online social network services, is one of the most popular micro-blogs, which generates a large number of automated programs, known as tweet bots because of the open structure of Twitter. While these tweet bots are categorized to legitimate bots and malicious bots, it is important to detect tweet bots since malicious bots spread spam and malicious contents to human users. In the conventional work, temporal information was utilized for the classficiation of human and bot. In this paper, by utilizing geo-tagged tweets that provide high-precision location information of users, we first identify both Twitter users' exact location. Then, we propose a new tweet bot detection algorithm by using both an entropy based on geographic variable of each user and device information of each user. As a main result, the proposed algorithm shows superior bot detection and false alarm probabilities over the conventional result which only uses temporal information.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.4
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• pp.63-73
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• 2010

Malicious bot programs, the source of distributed denial of service attack, are widespread and the number of PCs which were infected by malicious bot program are increasing geometrically thesedays. The continuous distributed denial of service attacks are happened constantly through these bot PCs and some financial incident cases have found lately. Therefore researches to response distributed denial of service attack are necessary so we propose an effective feature generation method for distributed denial of service attack detection using entropy. In this paper, we apply our method to both the DARPA 2000 datasets and also the distributed denial of service attack datasets that we composed and generated ourself in general university. And then we evaluate how the proposed method is useful through classification using bayesian network classifier.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.750-761
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• 2021

Even though the replying comments on Internet articles have positive effects on discussions and communications, the malicious comments are still the source of problems even driving people to death. Automatic detection of malicious comments is important in this respect. However, the current filtering method of the malicious comments, based on forbidden words, is not so effective, especially for the replying comments written in Korean. This paper proposes a new filtering approach based on morpheme analysis, identifying coarse and polite morphemes. Based on these two groups of morphemes, the soundness of comments can be calculated. Further, this paper proposes various impact measures for comments, based on the soundness. According to the experiments on malicious comments, one of the impact measures is effective for detecting malicious comments. Comparing our method with the clean-bot of a portal site, the recall is enhanced by 37.93% point and F-measure is also enhanced up to 47.66 points. According to this result, it is highly expected that the new filtering method based on morpheme analysis can be a promising alternative to those based on forbidden words.