• Title/Summary/Keyword: Botnet C&C Communication

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Construction of an Audio Steganography Botnet Based on Telegram Messenger (텔레그램 메신저 기반의 오디오 스테가노그래피 봇넷 구축)

  • Jeon, Jin;Cho, Youngho
    • Journal of Internet Computing and Services
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    • v.23 no.5
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    • pp.127-134
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    • 2022
  • Steganography is a hidden technique in which secret messages are hidden in various multimedia files, and it is widely exploited for cyber crime and attacks because it is very difficult for third parties other than senders and receivers to identify the presence of hidden information in communication messages. Botnet typically consists of botmasters, bots, and C&C (Command & Control) servers, and is a botmasters-controlled network with various structures such as centralized, distributed (P2P), and hybrid. Recently, in order to enhance the concealment of botnets, research on Stego Botnet, which uses SNS platforms instead of C&C servers and performs C&C communication by applying steganography techniques, has been actively conducted, but image or video media-oriented stego botnet techniques have been studied. On the other hand, audio files such as various sound sources and recording files are also actively shared on SNS, so research on stego botnet based on audio steganography is needed. Therefore, in this study, we present the results of comparative analysis on hidden capacity by file type and tool through experiments, using a stego botnet that performs C&C hidden communication using audio files as a cover medium in Telegram Messenger.

An Encrypted Botnet C&C Communication Method in Bitcoin Network (비트코인 네크워크에서의 암호화된 봇넷 C&C 통신기법)

  • Kim, Kibeom;Cho, Youngho
    • Journal of Internet Computing and Services
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    • v.23 no.5
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    • pp.103-110
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    • 2022
  • Botnets have been exploited for a variety of purposes, ranging from monetary demands to national threats, and are one of the most threatening types of attacks in the field of cybersecurity. Botnets emerged as a centralized structure in the early days and then evolved to a P2P structure. Bitcoin is the first online cryptocurrency based on blockchain technology announced by Satoshi Nakamoto in 2008 and is the most widely used cryptocurrency in the world. As the number of Bitcoin users increases, the size of Bitcoin network is also expanding. As a result, a botnet using the Bitcoin network as a C&C channel has emerged, and related research has been recently reported. In this study, we propose an encrypted botnet C&C communication mechanism and technique in the Bitcoin network and validate the proposed method by conducting performance evaluation through various experiments after building it on the Bitcoin testnet. By this research, we want to inform the possibility of botnet threats in the Bitcoin network to researchers.

A Deep Learning Approach with Stacking Architecture to Identify Botnet Traffic

  • Kang, Koohong
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.12
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    • pp.123-132
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    • 2021
  • Malicious activities of Botnets are responsible for huge financial losses to Internet Service Providers, companies, governments and even home users. In this paper, we try to confirm the possibility of detecting botnet traffic by applying the deep learning model Convolutional Neural Network (CNN) using the CTU-13 botnet traffic dataset. In particular, we classify three classes, such as the C&C traffic between bots and C&C servers to detect C&C servers, traffic generated by bots other than C&C communication to detect bots, and normal traffic. Performance metrics were presented by accuracy, precision, recall, and F1 score on classifying both known and unknown botnet traffic. Moreover, we propose a stackable botnet detection system that can load modules for each botnet type considering scalability and operability on the real field.

VPN-Filter Malware Techniques and Countermeasures in IoT Environment (사물인터넷 환경에서의 VPN-Filter malware 기술과 대응방법)

  • Kim, Seung-Ho;Lee, Keun-Ho
    • Journal of Convergence for Information Technology
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    • v.8 no.6
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    • pp.231-236
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    • 2018
  • Recently, a wide variety of IoT environment is being created due to the rapid development of information and communication technology. And accordingly in a variety of network structures, a countless number of attack techniques and new types of vulnerabilities are producing a social disturbance. In May of 2018, Talos Intelligence, the Cisco threat intelligence team has newly discovered 'VPN-Filter', which constitutes a large-scale IoT-based botnet, is infecting consumer routers in over 54 countries around the world. In this paper, types of IoT-based botnets and the attack techniques utilizing botnet will be examined and the countermeasure technique through EXIF metadata removal method which is the cause of connection method of C & C Server will be proposed by examining the characteristics of attack vulnerabilities and attack scenarios of VPN-Filter.

Feature Selection with PCA based on DNS Query for Malicious Domain Classification (비정상도메인 분류를 위한 DNS 쿼리 기반의 주성분 분석을 이용한 성분추출)

  • Lim, Sun-Hee;Cho, Jaeik;Kim, Jong-Hyun;Lee, Byung Gil
    • KIPS Transactions on Computer and Communication Systems
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    • v.1 no.1
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    • pp.55-60
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    • 2012
  • Recent botnets are widely using the DNS services at the connection of C&C server in order to evade botnet's detection. It is necessary to study on DNS analysis in order to counteract anomaly-based technique using the DNS. This paper studies collection of DNS traffic for experimental data and supervised learning for DNS traffic-based malicious domain classification such as query of domain name corresponding to C&C server from zombies. Especially, this paper would aim to determine significant features of DNS-based classification system for malicious domain extraction by the Principal Component Analysis(PCA).

A Study of Command & Control Server through Analysis - DNS query log (명령제어서버 탐색 방법 - DNS 분석 중심으로)

  • Cheon, Yang-Ha
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.12
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    • pp.1849-1856
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    • 2013
  • DOS attack, the short of Denial of Service attack is an internet intrusion technique which harasses service availability of legitimate users. To respond the DDoS attack, a lot of methods focusing attack source, target and intermediate network, have been proposed, but there have not been a clear solution. In this paper, we purpose the prevention of malicious activity and early detection of DDoS attack by detecting and removing the activity of botnets, or other malicious codes. For the purpose, the proposed method monitors the network traffic, especially DSN traffic, which is originated from botnets or malicious codes.