• Title/Summary/Keyword: 공격 모델

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Building an Analysis Model for Social Engineering Based Cyberspace Operations (사회공학 사이버작전 분석모델 정립연구)

  • Shin, Kyuyong;Kim, Jeewon;Lim, Hyun-myung;Kim, Yongju;Yoo, Jincheol
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.6
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    • pp.1595-1606
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    • 2018
  • Recently, there has been an increase in the number of social engineering techniques that indirectly attack the target system administrators or organizational weaknesses rather than the traditional technical cyber attacks that directly attacked the target systems. Accordingly, the type analysis and case study of social engineering techniques are being actively conducted. There has been, however, little effort to derive an analysis model that systematically analyzes social engineering based cyberspace operations. Therefore, this paper aims at building a Social Engineering Based Cyberspace Operations Analysis Model, which can be used as a reference framework for a case study or attack scenario generation of social engineering based cyberspace operations.

Side Channel Attack on Block Cipher SM4 and Analysis of Masking-Based Countermeasure (블록 암호 SM4에 대한 부채널 공격 및 마스킹 기반 대응기법 분석)

  • Bae, Daehyeon;Nam, Seunghyun;Ha, Jaecheol
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.1
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    • pp.39-49
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    • 2020
  • In this paper, we show that the Chinese standard block cipher SM4 is vulnerable to the side channel attacks and present a countermeasure to resist them. We firstly validate that the secret key of SM4 can be recovered by differential power analysis(DPA) and correlation power analysis(CPA) attacks. Therefore we analyze the vulnerable element caused by power attack and propose a first order masking-based countermeasure to defeat DPA and CPA attacks. Although the proposed countermeasure unfortunately is still vulnerable to the profiling power attacks such as deep learning-based multi layer perceptron(MLP), it can sufficiently overcome the non-profiling attacks such as DPA and CPA.

Cybertrap : Unknown Attack Detection System based on Virtual Honeynet (Cybertrap : 가상 허니넷 기반 신종공격 탐지시스템)

  • Kang, Dae-Kwon;Hyun, Mu-Yong;Kim, Chun-Suk
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.6
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    • pp.863-871
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    • 2013
  • Recently application of open protocols and external network linkage to the national critical infrastructure has been growing with the development of information and communication technologies. This trend could mean that the national critical infrastructure is exposed to cyber attacks and can be seriously jeopardized when it gets remotely operated or controlled by viruses, crackers, or cyber terrorists. In this paper virtual Honeynet model which can reduce installation and operation resource problems of Honeynet system is proposed. It maintains the merits of Honeynet system and adapts the virtualization technology. Also, virtual Honeynet model that can minimize operating cost is proposed with data analysis and collecting technique based on the verification of attack intention and focus-oriented analysis technique. With the proposed model, new type of attack detection system based on virtual Honeynet, that is Cybertrap, is designed and implemented with the host and data collecting technique based on the verification of attack intention and the network attack pattern visualization technique. To test proposed system we establish test-bed and evaluate the functionality and performance through series of experiments.

S-PRESENT Cryptanalysis through Know-Plaintext Attack Based on Deep Learning (딥러닝 기반의 알려진 평문 공격을 통한 S-PRESENT 분석)

  • Se-jin Lim;Hyun-Ji Kim;Kyung-Bae Jang;Yea-jun Kang;Won-Woong Kim;Yu-Jin Yang;Hwa-Jeong Seo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.2
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    • pp.193-200
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    • 2023
  • Cryptanalysis can be performed by various techniques such as known plaintext attack, differential attack, side-channel analysis, and the like. Recently, many studies have been conducted on cryptanalysis using deep learning. A known-plaintext attack is a technique that uses a known plaintext and ciphertext pair to find a key. In this paper, we use deep learning technology to perform a known-plaintext attack against S-PRESENT, a reduced version of the lightweight block cipher PRESENT. This paper is significant in that it is the first known-plaintext attack based on deep learning performed on a reduced lightweight block cipher. For cryptanalysis, MLP (Multi-Layer Perceptron) and 1D and 2D CNN(Convolutional Neural Network) models are used and optimized, and the performance of the three models is compared. It showed the highest performance in 2D convolutional neural networks, but it was possible to attack only up to some key spaces. From this, it can be seen that the known-plaintext attack through the MLP model and the convolutional neural network is limited in attackable key bits.

IDS Evasion Detection System with Packet Reassemble Funtion (패킷 재조립 기능을 가진 IDS 우회공격 탐지 시스템)

  • Youk Sang-Jo;Park Myung-Ho;Lee Geuk
    • Journal of Digital Contents Society
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    • v.4 no.1
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    • pp.101-113
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    • 2003
  • IDS(Intrusion Detection System) evasion is a technology which uses vulnerability of IDS in order not to be detected by IDS. In this paper, at first, we classify IDS evasion technology. Second, we propose detection model of IDS evasion technology. Finally, we design and implement IDS evasion detection system with packet reassemble function.

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A Design and Implementation of Detection System against Evasional Attack to IDS (IDS 우회공격 탐지 시스템 설계 및 구현)

  • Gil, Min-Wook;Cha, Jun-Nam;Lee, Geuk
    • Convergence Security Journal
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    • v.2 no.2
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    • pp.165-177
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    • 2002
  • IDS(Intrusion Detection System) evasion is a technology which uses vulnerability of IDS in order not to be detected by IDS. In this paper, at first, we classify IDS evasion technology. Second, we propose detection model of IDS evasion technology. Finally, we design and implement detection system of IDS evasion.

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A Study on DDoS(Distributed Denial of Service) Attack Detection Model Based on Statistical (통계 기반 분산서비스거부(DDoS)공격 탐지 모델에 관한 연구)

  • Kook, Yoon-Ju;Kim, Yong-Ho;Kim, Jeom-Goo;Kim, Kiu-Nam
    • Convergence Security Journal
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    • v.9 no.2
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    • pp.41-48
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    • 2009
  • Distributed denial of service attack detection for more development and research is underway. The method of using statistical techniques, the normal packets and abnormal packets to identify efficient. In this paper several statistical techniques, using a mix of various offers a way to detect the attack. To verify the effectiveness of the proposed technique, it set packet filtering on router and the proposed DDoS attacks detection method on a Linux router. In result, the proposed technique was detect various attacks and provide normal service mostly.

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Efficient Detction and Defence Model against IP Spoofing Attack through Cooperation of Trusted Hosts (신뢰 호스트 상호 협력을 통한 IP 스푸핑 공격의 효율적 탐지 및 방어 모델 설계)

  • Lee, Hae-Dong;Ha, Hyeon-Tae;Baek, Hyun-Chul;Kim, Chang-Gun;Kim, Sang-Bok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.12
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    • pp.2649-2656
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    • 2012
  • Today, many enterprises have invested heavily for the part of information security in order to protect the internal critical information assets and the business agility. However, there is a big problem that big budget and too many manpower are needed to set the internal corporate network up to the same high level of defense for all of part. On the distributed enterprise networks in this paper, a defense model for effective and rapid response on the IP spoofing attack was designed to protect the enterprise network through the exchange of information between the trust hosts when an attacker attacked any target system using other trusted host.

A Robust Collaborative Filtering against Manipulated Ratings (조작된 선호도에 강건한 협업적 여과 방법)

  • Kim, Heung-Nam;Ha, In-Ay;Jo, Geun-Sik
    • Journal of Internet Computing and Services
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    • v.10 no.6
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    • pp.81-98
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    • 2009
  • Collaborative filtering, one of the most successful technologies among recommender systems, is a system assisting users in easily finding the useful information and supporting the decision making. However, despite of its success and popularity, one notable issue is incredibility of recommendations by unreliable users called shilling attacks. To deal with this problem, in this paper, we analyze the type of shilling attacks and propose a unique method of building a model for protecting the recommender system against manipulated ratings. In addition, we present a method of applying the model to collaborative filtering which is highly robust and stable to shilling attacks.

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Efficient Fault Injection Attack to the Miller Algorithm in the Pairing Computation using Affine Coordinate System (아핀좌표를 사용하는 페어링 연산의 Miller 알고리듬에 대한 효과적인 오류주입공격)

  • Bae, Ki-Seok;Park, Jea-Hoon;Sohn, Gyo-Yong;Ha, Jae-Cheol;Moon, Sang-Jae
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.21 no.3
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    • pp.11-25
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    • 2011
  • The Miller algorithm is employed in the typical pairing computation such as Weil, Tate and Ate for implementing ID based cryptosystem. By analyzing the Mrabet's attack that is one of fault attacks against the Miller algorithm, this paper presents au efficient fault attack in Affine coordinate system, it is the most basic coordinates for construction of elliptic curve. The proposed attack is the effective model of a count check fault attack, it is verified to work well by practical fault injection experiments and can omit the probabilistic analysis that is required in the previous counter fault model.