• 제목/요약/키워드: Cryptographic Analysis

검색결과 177건 처리시간 0.029초

T4급 링크 암호에 적합한 암호 동기방식 제안 (A Proposal on Cryptographic Synchronization for T4 Link Encryption)

  • 이훈재;김기환;강영진;이상곤;류영재
    • 한국정보통신학회논문지
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    • 제22권1호
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    • pp.202-210
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    • 2018
  • 현대 전장은 과학화 및 첨단화를 통해 빠른 현황 파악과 전력배치를 우선시하는 네트워크 중심 전으로 발전하고 있다. 이에 전술 데이터링크는 지속적으로 네트워크 속도 향상을 이루고 있으며, 최근 정찰용 무인기 및 각종 장비와의 무선통신을 위하여 보안 기술을 필요로 하고 있다. 또한 미래 정보전에서는 첨단 IT의 적극적인 활용이 필수적으로 요구되며, 다양한 시스템과 네트워크를 연동, 통합하기 위한 노력이 필요하다. 하지만 이러한 노력은 새롭게 변화하는 정보통신 환경에서 충분한 보안성을 전제 할 수 있어야 한다는 의미가 있다. 본 논문에서는 전술 데이터링크에 적합한 새로운 링크 암호동기방식을 제안한다. 제안한 암호 동기방식은 T4급 UAV 링크암호에 적합한 방식이며, 통신선로의 BER이 아주 낮은 경우에도 잘 견딜 수 있도록 설계하였고, 그 성능을 분석하였다.

Data Security on Cloud by Cryptographic Methods Using Machine Learning Techniques

  • Gadde, Swetha;Amutharaj, J.;Usha, S.
    • International Journal of Computer Science & Network Security
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    • 제22권5호
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    • pp.342-347
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    • 2022
  • On Cloud, the important data of the user that is protected on remote servers can be accessed via internet. Due to rapid shift in technology nowadays, there is a swift increase in the confidential and pivotal data. This comes up with the requirement of data security of the user's data. Data is of different type and each need discrete degree of conservation. The idea of data security data science permits building the computing procedure more applicable and bright as compared to conventional ones in the estate of data security. Our focus with this paper is to enhance the safety of data on the cloud and also to obliterate the problems associated with the data security. In our suggested plan, some basic solutions of security like cryptographic techniques and authentication are allotted in cloud computing world. This paper put your heads together about how machine learning techniques is used in data security in both offensive and defensive ventures, including analysis on cyber-attacks focused at machine learning techniques. The machine learning technique is based on the Supervised, UnSupervised, Semi-Supervised and Reinforcement Learning. Although numerous research has been done on this topic but in reference with the future scope a lot more investigation is required to be carried out in this field to determine how the data can be secured more firmly on cloud in respect with the Machine Learning Techniques and cryptographic methods.

Ensuring Data Confidentiality and Privacy in the Cloud using Non-Deterministic Cryptographic Scheme

  • John Kwao Dawson;Frimpong Twum;James Benjamin Hayfron Acquah;Yaw Missah
    • International Journal of Computer Science & Network Security
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    • 제23권7호
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    • pp.49-60
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    • 2023
  • The amount of data generated by electronic systems through e-commerce, social networks, and data computation has risen. However, the security of data has always been a challenge. The problem is not with the quantity of data but how to secure the data by ensuring its confidentiality and privacy. Though there are several research on cloud data security, this study proposes a security scheme with the lowest execution time. The approach employs a non-linear time complexity to achieve data confidentiality and privacy. A symmetric algorithm dubbed the Non-Deterministic Cryptographic Scheme (NCS) is proposed to address the increased execution time of existing cryptographic schemes. NCS has linear time complexity with a low and unpredicted trend of execution times. It achieves confidentiality and privacy of data on the cloud by converting the plaintext into Ciphertext with a small number of iterations thereby decreasing the execution time but with high security. The algorithm is based on Good Prime Numbers, Linear Congruential Generator (LGC), Sliding Window Algorithm (SWA), and XOR gate. For the implementation in C, thirty different execution times were performed and their average was taken. A comparative analysis of the NCS was performed against AES, DES, and RSA algorithms based on key sizes of 128kb, 256kb, and 512kb using the dataset from Kaggle. The results showed the proposed NCS execution times were lower in comparison to AES, which had better execution time than DES with RSA having the longest. Contrary, to existing knowledge that execution time is relative to data size, the results obtained from the experiment indicated otherwise for the proposed NCS algorithm. With data sizes of 128kb, 256kb, and 512kb, the execution times in milliseconds were 38, 711, and 378 respectively. This validates the NCS as a Non-Deterministic Cryptographic Algorithm. The study findings hence are in support of the argument that data size does not determine the execution.

화이트 박스 블록 암호에 대한 최신 암호분석 기술 동향 연구 (Recent Trends in Cryptanalysis Techniques for White-box Block Ciphers)

  • 오채린;임우상;김현일;서창호
    • 스마트미디어저널
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    • 제12권9호
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    • pp.9-18
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    • 2023
  • 블랙박스 암호는 하드웨어로 구성된 암호화 장치를 기반으로 '디바이스와 사용자는 신뢰할 수 있다'는 가정하에 동작하는 암호이다. 그러나 공격자에게 내부 구조가 공개되는 순간 키 추출 등의 다양한 공격이 존재함과 동시에 최근 들어 신뢰할 수 없는 개방형 플랫폼에서 암호 알고리즘을 적용하는 경우가 증가하여 블랙 박스 암호 시스템에 대한 위협은 더욱 커져가고 있다. 그로 인해, 개방형 플랫폼에서 암호 알고리즘을 안전하게 동작하고자 암호화 과정에서 암호 키를 숨김으로써 공격자의 키 유출을 어렵게 하는 화이트 박스 암호화 기술이 제안되었다. 하지만, 이러한 화이트 박스 기반 암호는 기존의 암호와는 다르게 정해진 규격이 존재하지 않아 구조적 안전성을 검증하는 것이 어렵다. 이에 CHES에서는 보다 안전한 화이트 박스 암호 활용을 위해 The WhibOx Contest를 주기적으로 개최하여, 다양한 화이트 박스 암호에 대한 안전성 분석이 수행 되었다. 이 중 2016년 Bos가 제안한 Differential Computation Analysis(DCA) 공격법은 현재까지도 안전성 분석에 널리 활용되고 있는 강력한 화이트 박스 블록 암호에 대한 공격 기술에 해당한다. 이에 본 논문은 화이트 박스 암호에 대한 동향을 분석하고, 화이트 박스 블록 암호에 대한 부채널 정보 기반 암호분석 기술인 DCA, HODCA 공격 분석 및 관련 대응 기술 동향을 정리한다.

Power-based Side-Channel Analysis Against AES Implementations: Evaluation and Comparison

  • Benhadjyoussef, Noura;Karmani, Mouna;Machhout, Mohsen
    • International Journal of Computer Science & Network Security
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    • 제21권4호
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    • pp.264-271
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    • 2021
  • From an information security perspective, protecting sensitive data requires utilizing algorithms which resist theoretical attacks. However, treating an algorithm in a purely mathematical fashion or in other words abstracting away from its physical (hardware or software) implementation opens the door to various real-world security threats. In the modern age of electronics, cryptanalysis attempts to reveal secret information based on cryptosystem physical properties, rather than exploiting the theoretical weaknesses in the implemented cryptographic algorithm. The correlation power attack (CPA) is a Side-Channel Analysis attack used to reveal sensitive information based on the power leakages of a device. In this paper, we present a power Hacking technique to demonstrate how a power analysis can be exploited to reveal the secret information in AES crypto-core. In the proposed case study, we explain the main techniques that can break the security of the considered crypto-core by using CPA attack. Using two cryptographic devices, FPGA and 8051 microcontrollers, the experimental attack procedure shows that the AES hardware implementation has better resistance against power attack compared to the software one. On the other hand, we remark that the efficiency of CPA attack depends statistically on the implementation and the power model used for the power prediction.

패딩 오라클 공격에 따른 다양한 패딩방법의 안전성 분석 (Safety Analysis of Various Padding Techniques on Padding Oracle Attack)

  • 김기문;박명서;김종성;이창훈;문덕재;홍석희
    • 정보보호학회논문지
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    • 제25권2호
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    • pp.271-278
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    • 2015
  • 인터넷 뱅킹이나 전자상거래 같은 응용 환경에서 개인정보 및 민감한 정보를 보호하기 위해서 다양한 암호 알고리즘들을 사용한다. 하지만 안전성이 검증된 암호 알고리즘을 사용하여 중요 정보를 암호화 하더라도 운영모드, 패딩방법등 암호화를 적용하는 방법이 올바르지 못하면 암호화된 중요 정보들이 노출 된다는 연구결과와 방법들이 소개되고 있다. 이러한 공격방법 중 대표적인 사례가 패딩 오라클 공격(Padding Oracle Attack)이다. 본 논문에서는 블록암호의 CBC(Cipher Block Chainning) 운영모드에 적용 가능한 12가지 패딩방법에 대하여 패딩오라클 공격의 가능성을 분석하였다. 그 결과, 3가지의 안전한 패딩방법과 9가지의 안전하지 않은 패딩방법으로 분류할 수 있다. 3가지의 안전한 패딩방법 분석을 통해 패딩 오라클 공격에 내성을 가질 수 있도록 안전한 패딩방법 설계 시 고려해야 할 5가지 사항에 대하여 제안하고자 한다.

AND 게이트에 대한 2차 G-equivariant 로직 게이트 및 AES 구현에의 응용 (Second-Order G-equivariant Logic Gate for AND Gate and its Application to Secure AES Implementation)

  • 백유진;최두호
    • 정보보호학회논문지
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    • 제24권1호
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    • pp.221-227
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    • 2014
  • 스마트카드 등과 같은 모바일 기기에 구현된 암호 알고리즘은 수학적 안전성뿐만 아니라 부채널 공격에 대한 안전성도 함께 고려되어야 한다. 부채널 공격이란 구현된 암호 알고리즘의 연산 과정 중에 발생하는 부채널 정보를 이용해서 비밀 정보를 알아내는 공격 방법이다. 특히 전력분석 공격은 암호 연산 수행시 발생하는 전력 소비량의 변화를 측정함으로써 암호 기기 내부의 비밀 정보를 알아내는 공격법으로 이에 대한 여러 가지 대응 방법이 제안되었다. 본 논문에서는 블록 암호 알고리즘 구현시 전력분석 공격 및 글리치 공격을 방어할 수 있는 게이트 레벨 기법을 새롭게 제안한다. 또한 본 논문에서 제안한 방법을 이용하여 AES 블록 암호 알고리즘을 전력분석 공격 및 글리치 공격에 안전하게 구현할 수 있는 방법을 제시한다.

Design and Analysis of Lightweight Trust Mechanism for Accessing Data in MANETs

  • Kumar, Adarsh;Gopal, Krishna;Aggarwal, Alok
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권3호
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    • pp.1119-1143
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    • 2014
  • Lightweight trust mechanism with lightweight cryptographic primitives has emerged as an important mechanism in resource constraint wireless sensor based mobile devices. In this work, outlier detection in lightweight Mobile Ad-hoc NETworks (MANETs) is extended to create the space of reliable trust cycle with anomaly detection mechanism and minimum energy losses [1]. Further, system is tested against outliers through detection ratios and anomaly scores before incorporating virtual programmable nodes to increase the efficiency. Security in proposed system is verified through ProVerif automated toolkit and mathematical analysis shows that it is strong against bad mouthing and on-off attacks. Performance of proposed technique is analyzed over different MANET routing protocols with variations in number of nodes and it is observed that system provide good amount of throughput with maximum of 20% increase in delay on increase of maximum of 100 nodes. System is reflecting good amount of scalability, optimization of resources and security. Lightweight modeling and policy analysis with lightweight cryptographic primitives shows that the intruders can be detection in few milliseconds without any conflicts in access rights.

Improve the Performance of Semi-Supervised Side-channel Analysis Using HWFilter Method

  • Hong Zhang;Lang Li;Di Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권3호
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    • pp.738-754
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    • 2024
  • Side-channel analysis (SCA) is a cryptanalytic technique that exploits physical leakages, such as power consumption or electromagnetic emanations, from cryptographic devices to extract secret keys used in cryptographic algorithms. Recent studies have shown that training SCA models with semi-supervised learning can effectively overcome the problem of few labeled power traces. However, the process of training SCA models using semi-supervised learning generates many pseudo-labels. The performance of the SCA model can be reduced by some of these pseudo-labels. To solve this issue, we propose the HWFilter method to improve semi-supervised SCA. This method uses a Hamming Weight Pseudo-label Filter (HWPF) to filter the pseudo-labels generated by the semi-supervised SCA model, which enhances the model's performance. Furthermore, we introduce a normal distribution method for constructing the HWPF. In the normal distribution method, the Hamming weights (HWs) of power traces can be obtained from the normal distribution of power points. These HWs are filtered and combined into a HWPF. The HWFilter was tested using the ASCADv1 database and the AES_HD dataset. The experimental results demonstrate that the HWFilter method can significantly enhance the performance of semi-supervised SCA models. In the ASCADv1 database, the model with HWFilter requires only 33 power traces to recover the key. In the AES_HD dataset, the model with HWFilter outperforms the current best semi-supervised SCA model by 12%.

홍채 코드 기반 생체 고유키 추출에 관한 연구 (Invariant Biometric Key Extraction based on Iris Code)

  • 이연주;이형구;박강령;김재희
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2005년도 추계종합학술대회
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    • pp.1011-1014
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    • 2005
  • In this paper, we propose a method that extracts an invariant biometric key in order to apply this biometric key to the crypto-biometric system. This system is a new authentication architecture which can improve the security of current cryptographic system and solve the problem of stored template protection in conventional biometric system, also. To use biometric information as a cryptographic key in crypto-biometric system, same key should be generated from the same person. However, it is difficult to obtain such an invariant biometric key because biometric data is sensitive to surrounding environments. The proposed method solves this problem by clustering Iris Codes obtained by using independent component analysis (ICA).

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