• Title/Summary/Keyword: Security-Vulnerability

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Reversible Sub-Feature Retrieval: Toward Robust Coverless Image Steganography for Geometric Attacks Resistance

  • Liu, Qiang;Xiang, Xuyu;Qin, Jiaohua;Tan, Yun;Zhang, Qin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.1078-1099
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    • 2021
  • Traditional image steganography hides secret information by embedding, which inevitably leaves modification traces and is easy to be detected by steganography analysis tools. Since coverless steganography can effectively resist steganalysis, it has become a hotspot in information hiding research recently. Most coverless image steganography (CIS) methods are based on mapping rules, which not only exposes the vulnerability to geometric attacks, but also are less secure due to the revelation of mapping rules. To address the above issues, we introduced camouflage images for steganography instead of directly sending stego-image, which further improves the security performance and information hiding ability of steganography scheme. In particular, based on the different sub-features of stego-image and potential camouflage images, we try to find a larger similarity between them so as to achieve the reversible steganography. Specifically, based on the existing CIS mapping algorithm, we first can establish the correlation between stego-image and secret information and then transmit the camouflage images, which are obtained by reversible sub-feature retrieval algorithm. The received camouflage image can be used to reverse retrieve the stego-image in a public image database. Finally, we can use the same mapping rules to restore secret information. Extensive experimental results demonstrate the better robustness and security of the proposed approach in comparison to state-of-art CIS methods, especially in the robustness of geometric attacks.

Detection of Levee Displacement and Estimation of Vulnerability of Levee Using Remote Sening (원격탐사를 이용한 하천 제방 변위량 측정과 취약지점 선별)

  • Bang, Young Jun;Jung, Hyo Jun;Lee, Seung Oh
    • Journal of Korean Society of Disaster and Security
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    • v.14 no.1
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    • pp.41-50
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    • 2021
  • As a method of predicting the displacement of river levee in advance, Differential Interferometry (D-InSAR) kind of InSAR techniques was used to identify weak points in the area of the levee collapes near Gumgok Bridge (Somjin River) in Namwon City, which occurred in the summer of 2020. As a result of analyzing the displacement using five images each in the spring and summer of 2020, the Variation Index (V) of area where the collapse occurred was larger than that of the other areas, so the prognostic sysmptoms was detected. If the levee monitoring system is realized by analyzing the correlations with displacement results and hydrometeorological factors, it will overcome the existing limitations of system and advance ultra-precise, automated river levee maintenance technology and improve national disaster management.

A Study on Key Protection Method based on WhiteBox Cipher in Block Chain Environment (블록체인 환경에서 화이트박스 암호기반 키 보호 기법에 관한 연구)

  • Choi, Do-Hyeon;Hong, Chan-Ki
    • Journal of Convergence for Information Technology
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    • v.9 no.10
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    • pp.9-15
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    • 2019
  • Recently, in the field of next-generation e-commerce and finance, interest in blockchain-based technologies such as Bitcoin and Ethereum is great. Although the security of blockchain technology is known to be secure, hacking incidents / accidents related to cryptocurrencies are being issued. The main causes were vulnerabilities in the external environment, such as taking over login sessions on cryptocurrency wallets, exposing private keys due to malware infection, and using simple passwords. However, private key management recommends general methods such as utilizing a dedicated application or local backup and physical archiving through document printing. In this paper, we propose a white box password-based private key protection scheme. As a result of safety and performance analysis, we strengthened the security against vulnerability of private key exposure and proved the processing efficiency of existing protocol.

New Analysis of Reduced-Version of Piccolo in the Single-Key Scenario

  • Liu, Ya;Cheng, Liang;Zhao, Fengyu;Su, Chunhua;Liu, Zhiqiang;Li, Wei;Gu, Dawu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.9
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    • pp.4727-4741
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    • 2019
  • The lightweight block cipher Piccolo adopts Generalized Feistel Network structure with 64 bits of block size. Its key supports 80 bits or 128 bits, expressed by Piccolo-80 or Piccolo-128, respectively. In this paper, we exploit the security of reduced version of Piccolo from the first round with the pre-whitening layer, which shows the vulnerability of original Piccolo. As a matter of fact, we first study some linear relations among the round subkeys and the properties of linear layer. Based on them, we evaluate the security of Piccolo-80/128 against the meet-in-the-middle attack. Finally, we attack 13 rounds of Piccolo-80 by applying a 5-round distinguisher, which requires $2^{44}$ chosen plaintexts, $2^{67.39}$ encryptions and $2^{64.91}$ blocks, respectively. Moreover, we also attack 17 rounds of Piccolo-128 by using a 7-round distinguisher, which requires $2^{44}$ chosen plaintexts, $2^{126}$ encryptions and $2^{125.49}$ blocks, respectively. Compared with the previous cryptanalytic results, our results are the currently best ones if considering Piccolo from the first round with the pre-whitening layer.

A Strong RFID Authentication Protocol Based on Synchronized Secret Information (비밀정보 동기화에 기반한 Strong RFID 인증)

  • Ha, Jae-Cheol;Ha, Jung-Hoon;Park, Jea-Hoon;Moon, Sang-Jae;Kim, Hwan-Koo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.17 no.5
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    • pp.99-109
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    • 2007
  • Lee et al. recently proposed an RFID mutual authentication scheme based on synchronized secret information. However, we found that their protocol is vulnerable to a spoofing attack in which an adversary can impersonate a legal tag to the reader by sending a malicious random number. To remedy this vulnerability, we propose two RFID authentication protocols which are secure against all possible threats including backward and forward traceability. Furthermore, one of the two proposed protocols requires only three hash operations(but, $[m/2]{\cdot}2+3$ operations in resynchronization state, m is the number of tags) in the database to authenticate a tag, hence it is well suitable fur large scale RFID systems.

Correlation Power Analysis Attacks on the Software based Salsa20/12 Stream Cipher (소프트웨어 기반 스트림 암호 Salsa20/12에 대한 상관도 전력분석 공격)

  • Park, Young-Goo;Bae, Ki-Seok;Moon, Sang-Jae;Lee, Hoon-Jae;Ha, Jae-Cheul;Ahn, Mahn-Ki
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.21 no.5
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    • pp.35-45
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    • 2011
  • The Salsa20/12 stream cipher selected for the final eSTREAM portfolio has a better performance than software implementation of AES using an 8-bit microprocessor with restricted memory space, In the theoretical approach, the evaluation of exploitable timing vulnerability was 'none' and the complexity of side-channel analysis was 'low', but there is no literature of the practical result of power analysis attack. Thus we propose the correlation power analysis attack method and prove the feasibility of our proposed method by practical experiments, We used an 8-bit RISC AVR microprocessor (ATmegal128L chip) to implement Salsa20/12 stream cipher without any countermeasures, and performed the experiments of power analysis based on Hamming weight model.

Extracting Neural Networks via Meltdown (멜트다운 취약점을 이용한 인공신경망 추출공격)

  • Jeong, Hoyong;Ryu, Dohyun;Hur, Junbeom
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.6
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    • pp.1031-1041
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    • 2020
  • Cloud computing technology plays an important role in the deep learning industry as deep learning services are deployed frequently on top of cloud infrastructures. In such cloud environment, virtualization technology provides logically independent and isolated computing space for each tenant. However, recent studies demonstrate that by leveraging vulnerabilities of virtualization techniques and shared processor architectures in the cloud system, various side-channels can be established between cloud tenants. In this paper, we propose a novel attack scenario that can steal internal information of deep learning models by exploiting the Meltdown vulnerability in a multi-tenant system environment. On the basis of our experiment, the proposed attack method could extract internal information of a TensorFlow deep-learning service with 92.875% accuracy and 1.325kB/s extraction speed.

TCST : A Technology for Verifying Control Flow Integrity for Smart Contracts within a Trusted Execution Environment (TCST : 신뢰실행환경 내에서 스마트 컨트랙트의 제어 흐름 무결성 검증을 위한 기술)

  • Park, Seonghwan;Kwon, Donghyun
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.32 no.6
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    • pp.1103-1112
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    • 2022
  • Blockchain technology is widespread in everyday life and various industry fields. It guarantees integrity and transparency between blockchain network participants through a distributed ledger. The smart contract is modifying and managing the distributed ledger, which is the most important component of guaranteeing integrity and transparency of blockchain network. Still, smart contracts are also a component of blockchain networks, it is disclosed to network participants transparently. For this reason, the vulnerability of smart contracts could be revealed easily. To mitigate this, various studies are leveraging TEE to guarantee the confidentiality of smart contracts. In existing studies, TEE provides confidentiality of smart contracts but guaranteeing the integrity of smart contracts is out of their scope. In this study, we provide not only the confidentiality of smart contracts but also their integrity, by guaranteeing the CFI of smart contracts within TEE.

A Study on the Lightweight Encryption Method for Secure MQTT Communication (안전한 MQTT 통신을 위한 경량 암호화 방법에 관한 연구)

  • Jeon, Yu-ran;Joo, Soyoung;Lee, Il-Gu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.82-84
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    • 2022
  • In recent years, research has been actively conducted to solve overhead problems caused by the increase in the number of IoT devices. MQTT, one of the IoT lightweight protocols for resolving performance degradation in IoT environments, is standardized to enable efficient operation in many-to-many communication environments, but there is a security vulnerability as it does not provide encryption by default. Although TLS communication technology can be applied to solve these problems, it is difficult to meet IoT's lightweight power-saving requirements. This paper introduces the latest MQTT communication encryption trends and analyzes IoT applicability by comparing TLS encryption and payload encryption methods.

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Study on the Vulnerabilities of Automatic Speech Recognition Models in Military Environments (군사적 환경에서 음성인식 모델의 취약성에 관한 연구)

  • Elim Won;Seongjung Na;Youngjin Ko
    • Convergence Security Journal
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    • v.24 no.2
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    • pp.201-207
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    • 2024
  • Voice is a critical element of human communication, and the development of speech recognition models is one of the significant achievements in artificial intelligence, which has recently been applied in various aspects of human life. The application of speech recognition models in the military field is also inevitable. However, before artificial intelligence models can be applied in the military, it is necessary to research their vulnerabilities. In this study, we evaluates the military applicability of the multilingual speech recognition model "Whisper" by examining its vulnerabilities to battlefield noise, white noise, and adversarial attacks. In experiments involving battlefield noise, Whisper showed significant performance degradation with an average Character Error Rate (CER) of 72.4%, indicating difficulties in military applications. In experiments with white noise, Whisper was robust to low-intensity noise but showed performance degradation under high-intensity noise. Adversarial attack experiments revealed vulnerabilities at specific epsilon values. Therefore, the Whisper model requires improvements through fine-tuning, adversarial training, and other methods.