• Title/Summary/Keyword: network threat

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Design for Zombie PCs and APT Attack Detection based on traffic analysis (트래픽 분석을 통한 악성코드 감염PC 및 APT 공격탐지 방안)

  • Son, Kyungho;Lee, Taijin;Won, Dongho
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.24 no.3
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    • pp.491-498
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    • 2014
  • Recently, cyber terror has been occurred frequently based on advanced persistent threat(APT) and it is very difficult to detect these attacks because of new malwares which cannot be detected by anti-virus softwares. This paper proposes and verifies the algorithms to detect the advanced persistent threat previously through real-time network monitoring and combinatorial analysis of big data log. In the future, APT attacks can be detected more easily by enhancing these algorithms and adapting big data platform.

STRIDE-based threat modeling and DREAD evaluation for the distributed control system in the oil refinery

  • Kyoung Ho Kim;Kyounggon Kim;Huy Kang Kim
    • ETRI Journal
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    • v.44 no.6
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    • pp.991-1003
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    • 2022
  • Industrial control systems (ICSs) used to be operated in closed networks, that is, separated physically from the Internet and corporate networks, and independent protocols were used for each manufacturer. Thus, their operation was relatively safe from cyberattacks. However, with advances in recent technologies, such as big data and internet of things, companies have been trying to use data generated from the ICS environment to improve production yield and minimize process downtime. Thus, ICSs are being connected to the internet or corporate networks. These changes have increased the frequency of attacks on ICSs. Despite this increased cybersecurity risk, research on ICS security remains insufficient. In this paper, we analyze threats in detail using STRIDE threat analysis modeling and DREAD evaluation for distributed control systems, a type of ICSs, based on our work experience as cybersecurity specialists at a refinery. Furthermore, we verify the validity of threats identified using STRIDE through case studies of major ICS cybersecurity incidents: Stuxnet, BlackEnergy 3, and Triton. Finally, we present countermeasures and strategies to improve risk assessment of identified threats.

Cyber Threat Military Response Strategy Using Information Security Risk Management (정보보안 위험관리를 활용한 사이버 위협 군사 대응 전략)

  • Jincheol Yoo
    • Convergence Security Journal
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    • v.23 no.5
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    • pp.173-179
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    • 2023
  • The 4th Industrial Revolution technology has emerged as a solution to build a hyper-connected, super-intelligent network-oriented operational environment, overcoming the obstacles of reducing troops and defense budgets facing the current military. However, the overall risk management, including the increase in complexity of the latest inform ation technology and the verification of the impact with the existing information system, is insufficient, leading to serious threats to system integrity and availability, or negatively affecting interoperability between systems. It can be inhibited. In this paper, we suggest cyber threat response strategies for our military to prepare for cyber threats by examining information security risk management in the United States in order to protect military information assets from cyber threats that may arise due to the advancement of information technology.

Study on APT Penetration Analysis and Plan of Reaction for Secure XaaS (안전한 XaaS 구현을 위한 APT 공격 분석과 대응방안에 관한 연구)

  • Lee, Sun Ho;Kim, DaeYoub
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.5
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    • pp.841-850
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    • 2015
  • XaaS (Everything as a Service) provides re-usable, fine-grained software components like software, platform, infra across a network. Then users usually pay a fee to get access to the software components. It is a subset of cloud computing. Since XaaS is provided by centralized service providers, it can be a target of various security attacks. Specially, if XaaS becomes the target of APT (Advanced Persistent Threat) attack, many users utilizing XaaS as well as XaaS system can be exposed to serious danger. So various solutions against APT attack are proposed. However, they do not consider all aspects of security control, synthetically. In this paper, we propose overall security checkup considering technical aspect and policy aspect to securely operate XaaS.

A Study on Spam Protection Technolgy for Secure VoIP Service in Broadband convergence Network Environment (BcN 환경에서 안전한 VoIP 서비스를 위한 스팸대응 기술 연구)

  • Sung, Kyung;Kim, Seok-Hun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.4
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    • pp.670-676
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    • 2008
  • There is a difficult plane letting a security threat to occur in Internet networks as VoIP service uses technology-based the Internet is inherent, and you protect without adjustment of the existing security solution or changes with real-time service characteristics. It is a voice to single networks The occurrence security threat that it is possible is inherent in IP networks that effort and cost to protect a data network only are complicated relatively as provide service integrated data. This paper about various response way fields to be able to prevent analysis regarding definition regarding VoIP spam and VoIP spam technology and VoIP spam.

Research for Radar Signal Classification Model Using Deep Learning Technique (딥 러닝 기법을 이용한 레이더 신호 분류 모델 연구)

  • Kim, Yongjun;Yu, Kihun;Han, Jinwoo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.22 no.2
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    • pp.170-178
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    • 2019
  • Classification of radar signals in the field of electronic warfare is a problem of discriminating threat types by analyzing enemy threat radar signals such as aircraft, radar, and missile received through electronic warfare equipment. Recent radar systems have adopted a variety of modulation schemes that are different from those used in conventional systems, and are often difficult to analyze using existing algorithms. Also, it is necessary to design a robust algorithm for the signal received in the real environment due to the environmental influence and the measurement error due to the characteristics of the hardware. In this paper, we propose a radar signal classification method which are not affected by radar signal modulation methods and noise generation by using deep learning techniques.

Field Applicability of Design Methodologies for Groundwater Quality Monitoring Network

  • Lee, Sang-Il
    • Korean Journal of Hydrosciences
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    • v.10
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    • pp.47-58
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    • 1999
  • Protection of groundwater resources from contamination has been of increasing concern throughout the past decades. In practice, however, groundwater monitoring is performed based on the experience and intuition of experts or on the convenience. In dealing with groundwater contamination, we need to know what contaminants have the potential to threat the water quality and the distribution and concentration of the plumes. Monitoring of the subsurface environment through remote geophysical techniques or direct sampling from wells can provide such information. Once known, the plume can be properly menaged. Evaluation of existing methodologies for groundwater monitoring network design revealed that one should select an appropriate design method based on the purpose of the network and the avaliability of field information. Integer programming approach, one of the general purpose network design tools, and a cost-to-go function evaluation approach for special purpose network design were tested for field applicability. For the same contaminated aquifer, two approaches resulted in different well locations. The amount of information, however, was about the same.

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Study on Method to Develop Case-based Security Threat Scenario for Cybersecurity Training in ICS Environment (ICS 환경에서의 사이버보안 훈련을 위한 사례 기반 보안 위협 시나리오 개발 방법론 연구)

  • GyuHyun Jeon;Kwangsoo Kim;Jaesik Kang;Seungwoon Lee;Jung Taek Seo
    • Journal of Platform Technology
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    • v.12 no.1
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    • pp.91-105
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    • 2024
  • As the number of cases of applying IT systems to the existing isolated ICS (Industrial Control System) network environment continues to increase, security threats in the ICS environment have rapidly increased. Security threat scenarios help to design security strategies in cybersecurity training, including analysis, prediction, and response to cyberattacks. For successful cybersecurity training, research is needed to develop valid and reliable security threat scenarios for meaningful training. Therefore, this paper proposes a case-based security threat scenario development methodology for cybersecurity training in the ICS environment. To this end, we develop a methodology consisting of five steps based on analyzing actual cybersecurity incident cases targeting ICS. Threat techniques are standardized in the same form using objective data based on the MITER ATT&CK framework, and then a list of CVEs and CWEs corresponding to the threat technique is identified. Additionally, it analyzes and identifies vulnerable functions in programming used in CWE and ICS assets. Based on the data generated up to the previous stage, develop security threat scenarios for cybersecurity training for new ICS. As a result of verification through a comparative analysis between the proposed methodology and existing research confirmed that the proposed method was more effective than the existing method regarding scenario validity, appropriateness of evidence, and development of various scenarios.

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An Intrusion Detection System based on the Artificial Neural Network for Real Time Detection (실시간 탐지를 위한 인공신경망 기반의 네트워크 침입탐지 시스템)

  • Kim, Tae Hee;Kang, Seung Ho
    • Convergence Security Journal
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    • v.17 no.1
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    • pp.31-38
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    • 2017
  • As the cyber-attacks through the networks advance, it is difficult for the intrusion detection system based on the simple rules to detect the novel type of attacks such as Advanced Persistent Threat(APT) attack. At present, many types of research have been focused on the application of machine learning techniques to the intrusion detection system in order to detect previously unknown attacks. In the case of using the machine learning techniques, the performance of the intrusion detection system largely depends on the feature set which is used as an input to the system. Generally, more features increase the accuracy of the intrusion detection system whereas they cause a problem when fast responses are required owing to their large elapsed time. In this paper, we present a network intrusion detection system based on artificial neural network, which adopts a multi-objective genetic algorithm to satisfy the both requirements: accuracy, and fast response. The comparison between the proposing approach and previously proposed other approaches is conducted against NSL_KDD data set for the evaluation of the performance of the proposing approach.

Design of a User Authentication System using the Device Constant Information (디바이스 불변 정보를 이용한 사용자 인증 시스템 설계)

  • Kim, Seong-Ryeol
    • Journal of Convergence Society for SMB
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    • v.6 no.3
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    • pp.29-35
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    • 2016
  • This paper presents the design of a user authentication system (DCIAS) using the device constant information. Defined design a new password using the access device constant information to be used for user authentication during system access on the network, and design a new concept the user authentication system so that it can cope with the threat required from passive replay attacks to re-use the password obtained in other applications offer. In addition, by storing a password defined by the design of the encrypted random locations in the server and designed to neutralize the illegal access to the system through the network. Therefore proposed using the present system, even if access to the system through any of the network can not know whether any where the password is stored, and if all right even stored information is not easy to crack's encrypted to neutralize any replay attacks on the network to that has strong security features.