• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.4
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• pp.51-61
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• 2009

Recently, the cyber-attacks using botnets are being increased, Because these attacks pursue the money, the criminal aspect is also being increased, There are spreading of spam mail, DDoS(Distributed Denial of Service) attacks, propagations of malicious codes and malwares, phishings. leaks of sensitive informations as cyber-attacks that used botnets. There are many studies about detection and mitigation techniques against centralized botnets, namely IRC and HITP botnets. However, P2P botnets are still in an early stage of their studies. In this paper, we analyzed the traffics of the Peacomm bot that is one of P2P-based storm bot by using honeynet which is utilized in active analysis of network attacks. As a result, we could see that the Peacomm bot sends a large number of UDP packets to the zombies in wide network through P2P. Furthermore, we could know that the Peacomm bot makes the scale of botnet maintained and extended through these results. We expect that these results are used as a basis of detection and mitigation techniques against P2P botnets.

• Journal of Convergence Society for SMB
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• v.5 no.1
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• pp.19-23
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• 2015

Distributed Denial of Service attack is a form of denial of service attacks, the attacker to attack a place in a number of points of attack by a wide variety of forms over the network to perform a service on a point attack . Do not use a specific server or client attempts to make a connection to many services available that prevents this attack and so normally used . Corresponding methods of DDoS attacks has a corresponding managerial aspects and technical aspects of the proposed two.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.967-970
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• 2011

본 논문에서는 커널 모드에서 악성 봇이 호스트를 전염 시키는 순간 나타나는 일반적인 행동 특성들을 기반으로 효과적인 악성 봇 탐지가 가능한 프로그램을 구현하였다. 구현된 프로그램은 false-positive(오탐지)를 줄이기 위해서 악성 봇의 전염 과정에서 발생하는 복제 행동, 레지스트리 등록, uninstall 등록, 복제된 파일의 경로 정보 그리고 사용할 API 임포트 정보 등과 같은 악성 행위 탐지 기준 6가지를 고려한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.446-449
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• 2020

다크웹을 이용한 사이버 범죄율이 국내외에서 가파르게 상승 중이다. 그러나 다크웹의 특성상 숨겨져 있는 인터넷 영역에서 공유되는 악성코드들을 찾기란 어렵다. 특히 다크웹상 여러 서비스들은 크롤러 bot과 같은 정보 수집을 막고자 다양한 기법을 적용하고 있다. 따라서 우리는 기존의 연구 방법에 따라 다크웹 상의 URL을 수집한 후, 추가적으로 다운로더를 만들어 exe, zip과 같은 특정 형식의 파일을 수집하였다. 앞으로 해당 파일들은 통합 바이러스 스캔 엔진에서 검사하여 의심 파일들을 분별할 예정이다. 의심 파일들은 정적 / 동적 분석을 통해 상세한 보고서를 제출하여 향후 다크웹 내의 악성코드 분포 / 출처 분석에 유의미한 결과를 도출할 수 있다.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.463-468
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• 2021

Although the IoT is showing explosive growth due to the development of technology and the spread of IoT devices and activation of services, serious security risks and financial damage are occurring due to the activities of various botnets. Therefore, it is important to accurately and quickly detect the activities of these botnets. As security in the IoT environment has characteristics that require operation with minimum processing performance and memory, in this paper, the minimum characteristics for detection are selected, and KNN (K-Nearest Neighbor), Naïve Bayes, Decision Tree, Random A comparative study was conducted on the performance of machine learning algorithms such as Forest to detect botnet activity. Experimental results using the Bot-IoT dataset showed that KNN can detect DDoS, DoS, and Reconnaissance attacks most effectively and efficiently among the applied machine learning algorithms.

• Convergence Security Journal
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• v.22 no.1
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• pp.19-27
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• 2022

With the innovative development of ICT technology, hacking techniques of hackers are also evolving into sophisticated and intelligent hacking techniques. Threat detection research to counter these cyber threats was mainly conducted in a passive way through hacking damage investigation and analysis, but recently, the importance of cyber threat information collection and analysis is increasing. A bot-type automation program is a rather active method of extracting malicious code by visiting a website to collect threat information or detect threats. However, this method also has a limitation in that it cannot prevent hacking damage because it is a method to identify hacking damage because malicious code has already been distributed or after being hacked. Therefore, to overcome these limitations, we propose a model that detects actual threats by acquiring and analyzing threat information while identifying and managing cyber bases. This model is an active and proactive method of collecting threat information or detecting threats outside the boundary such as a firewall. We designed a model for detecting threats using cyber strongholds and validated them in the defense environment.

• Journal of the Korea Society of Computer and Information
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• v.21 no.7
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• pp.1-8
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• 2016

Nowadays, distributed denial of service (DDoS) attacks on web sites reward attackers financially or politically because our daily lifes tightly depends on web services such as on-line banking, e-mail, and e-commerce. One of DDoS attacks to web servers is called HTTP-GET flood attack which is becoming more serious. Most existing techniques are running on the application layer because these attack packets use legitimate network protocols and HTTP payloads; that is, network-level intrusion detection systems cannot distinguish legitimate HTTP-GET requests and malicious requests. In this paper, we propose a practical detection technique against HTTP-GET flood attacks, based on the access behavior of inline objects in a webpage using NetFlow data. In particular, our proposed scheme is working on the network layer without any application-specific deep packet inspections. We implement the proposed detection technique and evaluate the ability of attack detection on a simple test environment using NetBot attacker. Moreover, we also show that our approach must be applicable to real field by showing the test profile captured on a well-known e-commerce site. The results show that our technique can detect the HTTP-GET flood attack effectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1720-1726
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• 2011

The DDoS attacks which are increasing recently must have many zombie PCs before attacking targeted systems by attacker. A zombie PC is infected by attacker's malignant code and may be operated by the his/her special malicious purposes. But most users generally don't know that their PCs are infected and used as zombies by illegal activities covertly. In this paper, we propose a new scheme that decreases vulnerable PCs and isolates them from Internet before being zombie PCs. The proposed scheme point the reputations of connected PCs and decide whether their Internet connections are keeping continuously or not. Also We show the figures how to infect susceptable PCs to zombie PCs, and analyze the decrease effects of DDoS attacks adapted by the proposed scheme with various experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1445-1462
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• 2012

While botnets are used for various malicious activities, it is well known that they are widely used for email spam. Though the spam filtering systems currently in use block IPs that send email spam, simply blocking the IPs of zombie PCs participating in a botnet is not enough to prevent the spamming activities of the botnet because these IPs can easily be changed or manipulated. This IP blocking is also insufficient to prevent crimes other than spamming, as the botnet can be simultaneously used for multiple purposes. For this reason, we propose a system that detects botnets and zombie PCs based on email spam analysis. This study introduces the concept of "group pollution level" - the degree to which a certain spam group is suspected of being a botnet - and "IP pollution level" - the degree to which a certain IP in the spam group is suspected of being a zombie PC. Such concepts are applied in our system that detects botnets and zombie PCs by grouping spam mails based on the URL links or attachments contained, and by assessing the pollution level of each group and each IP address. For empirical testing, we used email spam data collected in an "email spam trap system" - Korea's national spam collection system. Our proposed system detected 203 botnets and 18,283 zombie PCs in a day and these zombie PCs sent about 70% of all the spam messages in our analysis. This shows the effectiveness of detecting zombie PCs by email spam analysis, and the possibility of a dramatic reduction in email spam by taking countermeasure against these botnets and zombie PCs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1431-1439
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• 2017

In the security field, log analysis is important to detect malware or abnormal behavior. Recently, image visualization techniques for malware dectection becomes to a major part of security. These techniques can also be used in online games. Users can leave a game when they felt bad experience from game bot, automatic hunting programs, malicious code, etc. This churning can damage online game's profit and longevity of service if game operators cannot detect this kind of events in time. In this paper, we propose a new technique of PNG image conversion based churn prediction to improve the efficiency of data analysis for the first. By using this log compression technique, we can reduce the size of log files by 52,849 times smaller and increase the analysis speed without features analysis. Second, we apply data mining technique to predict user's churn with a real dataset from Blade & Soul developed by NCSoft. As a result, we can identify potential churners with a high accuracy of 97%.