• Title/Summary/Keyword: ATTACK SUCCESS

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Practical Biasing Power Analysis breaking Side Channel Attack Countermeasures based on Masking-Shuffling techniques (마스킹-셔플링 부채널 대응법을 해독하는 실용적인 편중전력분석)

  • Cho, Jong-Won;Han, Dong-Guk
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.9
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    • pp.55-64
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    • 2012
  • Until now, Side Channel Attack has been known to be effective to crack decrypt key such as smart cards, electronic passports and e-ID card based on Chip. Combination of Masking and shuffling methods have been proposed practical countermeasure. Newly, S.Tillich suggests biased-mask using template attack(TA) to attack AES with masking and shuffling. However, an additional assumption that is acquired template information previously for masking value is necessary in order to apply this method. Moreover, this method needs to know exact time position of the target masking value for higher probability of success. In this paper, we suggest new practical method called Biasing Power Analysis(BPA) to find a secret key of AES based on masking-shuffling method. In BPA, we don't use time position and template information from masking value. Actually, we do experimental works of BPA attack to 128bit secret key of AES based on masking-shuffling method performed MSP430 Chip and we succeed in finding whole secret key. The results of this study will be utilized for next-generation ID cards to verify physical safety.

Power Trace Selection Method in Template Profiling Phase for Improvements of Template Attack (프로파일링 단계에서 파형 선별을 통한 템플릿 공격의 성능 향상)

  • Jin, Sunghyun;Kim, Taewon;Kim, HeeSeok;Hong, Seokhie
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.27 no.1
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    • pp.15-23
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    • 2017
  • Template attack is a powerful side-channel analysis technique which can be performed by an attacker who has a test device that is identical to target device. Template attack is consisted of building template in profiling phase and matching the target device using template that were calculated in profiling phase. One methods to improve the success rate of template attack is to better estimate template which is consisted sample mean and sample covariance matrix of gaussian distribution in template profiling. However restriction of power trace in profiling phase led to poor template estimation. In this paper, we propose new method to select noisy power trace in profiling phase. By eliminating noisy power trace in profiling phase, we can construct more advanced mean and covariance matrix which relates to better performance in template attack. We proved that the proposed method is valid through experiments.

Related Key Differential Attacks on 32-Round GOST (연관키 차분 특성을 이용한 32-라운드 GOST 공격)

  • 이태건;고영대;홍석희;이상진
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.14 no.3
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    • pp.75-84
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    • 2004
  • In this paper, we present a related key differential attack on Full-round GOST Firstly, we present a distinguishing attack on full rounds of GOST, which can distinguish it from random oracle with probability 1- 64$2^{64}$ using a related key differential characteristic. We will also show that H. Seki et al.'s idea can be applied to attack on 31 rounds of GOST combining our related key differential characteristic. Lastly, we propose a related key differential attack on full rounds of GOST. In this attack we can recover 12 bits of the master key with $2^{35}$ chosen plaintexts and $2^{36}$ encryption times for the 91.7% expectation of success rate.

Influences on Time and Spatial Characteristics of Soccer Pass Success Rate: A Case Study of the 2018 World Cup in Russia (시간과 공간적 특성에 따른 축구 패스 성공률 분석: 2018 러시아 월드컵 대회 자료를 중심으로)

  • Lee, Seung-Hun;Kim, Young-Hoon
    • Journal of Digital Convergence
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    • v.19 no.1
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    • pp.475-483
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    • 2021
  • The purpose of this study is to identify the temporal and spatial characteristics of pass accuracy by utilizing the second processing data and official records collected from the 2018 FIFA World Cup Russia video data. For a total of 128 games, the success rate of passes based on the results of the game, passing time, and passing position was two-way ANOVA with repeated measure. The results showed no difference between winning and losing groups, and no interaction effects were found for passing time and location. The difference in passing time was high in the first half, with the highest success rate in the middle of the first half (79.2%) and the middle of the second half (77.9%) in the 15~30 minutes and the 60~75 minutes. Pass success rates were in the order of defense-midfield area (83.9%), midfield-attack area (81.7%), defense area (70.6%) and attack area (61.1%). In conclusion, there was no difference in the passing success rate of the winning and losing teams depending on the characteristics of the relative competitive strength of the World Cup games, and it is believed that follow-up research is needed to analyze the game contents rather than the factors of the winning and losing in the future.

A Kill-Assessment Technique Using Hypothesis Testing and Kalman Filter (가설 검증과 칼만 필터를 이용한 격추평가 기법 연구)

  • Kim, Ho-Jeong;Lee, Dong-Gwan
    • Journal of the Korea Institute of Military Science and Technology
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    • v.9 no.4
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    • pp.5-14
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    • 2006
  • The correct and opportune decision of reengaging the intercepted target is required in order to enhance the engagement performance of the surface to air missile systems that has the ability to defense or attack against various targets at the same time. The engagement efficiency and success of these systems will be largely enhanced by assigning quickly its system resources to the intercepted target and minimizing the waste of system resources for the target which is not able to attack any more. The kill-assessment algorithm has to be able to evaluate automatically whether various targets intercepted by missiles are killed or not on the basis of the reasonable confidence level. The definition of kill assessment is discussed and the kill assessment algorithm is designed reliably by using Kalman filter and a probability theory. Finally its performance is evaluated and analyzed by the Monte Carlo simulation.

Cryptanalysis of the Authentication in ACORN

  • Shi, Tairong;Guan, Jie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.8
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    • pp.4060-4075
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    • 2019
  • ACORN is an authenticated encryption algorithm proposed as a candidate in the currently ongoing CAESAR competition. ACORN has a good performance on security and efficiency which has been a third-round candidate. This paper mainly concentrates on the security of ACORN under the forgery attack and the non-repudiation of ACORN. Firstly, we analyze the differential properties of the feedback function in ACRON are analyzed. By taking advantage of these properties, the forgery attacks on round-reduced ACORN are proposed with a success probability higher than $2^{-128}$ when the number of finalization rounds is less than 87. Moreover, the non-repudiation of ACRON in the nonce-reuse setting is analyzed. The known collision can be used to deny the authenticated message with probability $2^{-120}$. This paper demonstrates that ACORN cannot generate the non-repudiation completely. We believe it is an undesirable property indeed.

Adversarial Wall: Physical Adversarial Attack on Cityscape Pretrained Segmentation Model (도시 환경에서의 이미지 분할 모델 대상 적대적 물리 공격 기법)

  • Suryanto, Naufal;Larasati, Harashta Tatimma;Kim, Yongsu;Kim, Howon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.402-404
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    • 2022
  • Recent research has shown that deep learning models are vulnerable to adversarial attacks not only in the digital but also in the physical domain. This becomes very critical for applications that have a very high safety concern, such as self-driving cars. In this study, we propose a physical adversarial attack technique for one of the common tasks in self-driving cars, namely segmentation of the urban scene. Our method can create a texture on a wall so that it can be misclassified as a road. The demonstration of the technique on a state-of-the-art cityscape pretrained model shows a fairly high success rate, which should raise awareness of more potential attacks in self-driving cars.

Deep Learning Assisted Differential Cryptanalysis for the Lightweight Cipher SIMON

  • Tian, Wenqiang;Hu, Bin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.2
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    • pp.600-616
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    • 2021
  • SIMON and SPECK are two families of lightweight block ciphers that have excellent performance on hardware and software platforms. At CRYPTO 2019, Gohr first introduces the differential cryptanalysis based deep learning on round-reduced SPECK32/64, and finally reduces the remaining security of 11-round SPECK32/64 to roughly 38 bits. In this paper, we are committed to evaluating the safety of SIMON cipher under the neural differential cryptanalysis. We firstly prove theoretically that SIMON is a non-Markov cipher, which means that the results based on conventional differential cryptanalysis may be inaccurate. Then we train a residual neural network to get the 7-, 8-, 9-round neural distinguishers for SIMON32/64. To prove the effectiveness for our distinguishers, we perform the distinguishing attack and key-recovery attack against 15-round SIMON32/64. The results show that the real ciphertexts can be distinguished from random ciphertexts with a probability close to 1 only by 28.7 chosen-plaintext pairs. For the key-recovery attack, the correct key was recovered with a success rate of 23%, and the data complexity and computation complexity are as low as 28 and 220.1 respectively. All the results are better than the existing literature. Furthermore, we briefly discussed the effect of different residual network structures on the training results of neural distinguishers. It is hoped that our findings will provide some reference for future research.

Attack Surface Expansion through Decoy Trap for Protected Servers in Moving Target Defense

  • Park, Tae-Keun;Park, Kyung-Min;Moon, Dae-Sung
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.10
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    • pp.25-32
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    • 2019
  • In this paper, we propose a method to apply the attack surface expansion through decoy traps to a protected server network. The network consists of a large number of decoys and protected servers. In the network, each protected server dynamically mutates its IP address and port numbers based on Hidden Tunnel Networking that is a network-based moving target defense scheme. The moving target defense is a new approach to cyber security and continuously changes system's attack surface to prevent attacks. And, the attack surface expansion is an approach that uses decoys and decoy groups to protect attacks. The proposed method modifies the NAT table of the protected server with a custom chain and a RETURN target in order to make attackers waste all their time and effort in the decoy traps. We theoretically analyze the attacker success rate for the protected server network before and after applying the proposed method. The proposed method is expected to significantly reduce the probability that a protected server will be identified and compromised by attackers.

AERODYNAMIC OPTIMIZATION OF MULTI-ELEMENT AIRFOILS FOR LIFT ENHANCEMENT (다중 익형 주위의 고양력을 위한 위치 최적화)

  • Lee, Dae-Il;Choi, Byung-Chul;Park, Young-Min
    • 한국전산유체공학회:학술대회논문집
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    • 2011.05a
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    • pp.441-446
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    • 2011
  • To investigate aerodynamic performance of high-lift devices, 2D design is the base of the success of high-lift system design for transport aircraft, which can shorten the periods of three-dimensional design and analysis. For the simulation coupled viscous and inviscous euler method (MSES) is used. In this parametric study, Gap and Overlap which can define position of flap is used as design variables and we investigale relation between angle of attack and flap position for lift enhancement.

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