• Title/Summary/Keyword: Format preserving encryption

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An Efficient New Format-Preserving Encryption Algorithm to encrypt the Personal Information (개인정보암호화에 효율적인 새로운 형태보존암호화 알고리즘)

  • Song, Kyung-Hwan;Kang, Hyung-Chul;Sung, Jae-Chul
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.24 no.4
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    • pp.753-763
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    • 2014
  • Recently financial institutions and large retailers have a large amount of personal information leakage accident occurred one after another, and the damage is a trend of increasing day by day. Regulation such as enforcing the encryption of the personal identification information are strengthened. Efficient technology to encrypt personal information is Format-preserving encryption. Typical encryption expand output data length than input data length and change a format. Format Preserving Encryption is an efficient method to minimize database and application modification, because it makes preserve length and format of input data. In this paper, to encrypt personal information efficiently, we propose newly Format Preserving Encryption using Block cipher mode of operation.

Optimal Implementation of Format Preserving Encryption Algorithm FEA in Various Environments (다양한 환경에서의 형태보존 암호 FEA에 대한 최적 구현)

  • Park, Cheolhee;Jeong, Sooyong;Hong, Dowon;Seo, Changho
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.1
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    • pp.41-51
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    • 2018
  • Format preserving encryption(FPE) performs encryption with preserving the size and format of plain-text. Therefore, it is possible to minimize the structural change of the database before and after the encryption. For example, when encrypting data such as credit card number or social security number, it is possible to maintain the existing database structure because FPE outputs the same form of cipher-text as plain-text. Currently, the National Institute of Standards and Technology (NIST) recommends FF1 and FF3 as standards for FPE. Recently, in Korea, FEA, which is a very efficient FPE algorithm, has been adopted as the standard of FPE. In this paper, we analyze FEA and measure the performance of FEA by optimizing it in various environments.

Ransomware Prevention and Steganography Security Enhancement Technology Using Format Preserving Encryption (형태보존암호화를 이용한 랜섬웨어 방지 및 스테가노그래피 보안강화기술)

  • Lim, Ji-hwan;Na, Gwan-Woo;Woo, Jae-Min;Seo, Hwa-joeng
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.5
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    • pp.805-811
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    • 2018
  • Recently, Format-Preserving-Encryption (FEA) was suggested by the National Security Research institute (NSR) as an encryption method while maintaining the format without a distortion to the intended information to be encrypted. In this paper, we propose a scheme to solve conventional cyber security problems by using FEA scheme. First, we present the method to encrypt signatures and extensions with FEA in order to effectively defend against Ransomeware attacks. This technique can mitigate the exposure to the Ransomeware by encrypting the minimum information. Second, in order to reduce the secret information for Steganography, we introduce a new way to minimize the secret information with FEA. Finally, we compare the operation speed by encryption with FEA and Lightweight Encryption Algorithm (LEA), furthermore when we optimize FEA we want to compare with the performance improvement accompanying with it.

Secure Format-Preserving Encryption for Message Recovery Attack (메시지 복구 공격에 안전한 형태보존암호)

  • Jeong, Sooyong;Hong, Dowon;Seo, Changho
    • Journal of KIISE
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    • v.44 no.8
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    • pp.860-869
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    • 2017
  • Recently, due to the personal information security act, the encryption of personal information has attracted attention. However, if the conventional encryption scheme is used directly, the database schema must be changed because the conventional encryption scheme does not preserve the format of the data, which can yield a large cost. Therefore, the Format-Preserving Encryption(FPE) has emerged as an important technique that ensures the confidentiality of the data and maintains the database schema naturally. Accordingly, National Institute of Standards and Technology(NIST) recently published the FF1 and FF3 as standards for FPE, although problems have been found in the security of FF1 and FF3 against message recovery attacks. In this paper, we study and analyze FF1 and FF3 as the standards of FPE, as well as the message recovery attack on these schemes. We also study a secure FPE against message recovery attack and verify the efficiency by implementing standardized FF1 and FF3.

Utilization and Optimized Implementation of Format Preserving Encryption Algorithm for IoT and BLE Communications (IoT와 BLE 통신상의 형태보존암호 활용 및 최적화 구현 기법)

  • Lim, Ji-hwan;Kwon, Hyuk-dong;Woo, Jae-min;An, Kyu-hwang;Kim, Do-young;Seo, Hwa-jeong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.6
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    • pp.1371-1378
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    • 2018
  • Bluetooth is the key technology in the wireless connection of many Internet of Things (IoT) devices, especially focused on smartphones today. In addition, Bluetooth communication between the IoT device and the user is mainly performed via Bluetooth Low Energy (BLE), but as the Bluetooth technology gradually develops, the security vulnerability of the existing BLE is more prominent. Research on Bluetooth accessibility has been conducted steadily so far, but there is lack of research for data protection in Bluetooth communication. Therefore, in this paper, when sending and receiving data in BLE communication between IoT and users, we propose effective methods for communicating with each other through the Format Preserving Encryption Algorithm (FEA), not the plain text, and measures performance of FEA which is optimized in Arduino and PC.

New Text Steganography Technique Based on Part-of-Speech Tagging and Format-Preserving Encryption

  • Mohammed Abdul Majeed;Rossilawati Sulaiman;Zarina Shukur
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.1
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    • pp.170-191
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    • 2024
  • The transmission of confidential data using cover media is called steganography. The three requirements of any effective steganography system are high embedding capacity, security, and imperceptibility. The text file's structure, which makes syntax and grammar more visually obvious than in other media, contributes to its poor imperceptibility. Text steganography is regarded as the most challenging carrier to hide secret data because of its insufficient redundant data compared to other digital objects. Unicode characters, especially non-printing or invisible, are employed for hiding data by mapping a specific amount of secret data bits in each character and inserting the character into cover text spaces. These characters are known with limited spaces to embed secret data. Current studies that used Unicode characters in text steganography focused on increasing the data hiding capacity with insufficient redundant data in a text file. A sequential embedding pattern is often selected and included in all available positions in the cover text. This embedding pattern negatively affects the text steganography system's imperceptibility and security. Thus, this study attempts to solve these limitations using the Part-of-speech (POS) tagging technique combined with the randomization concept in data hiding. Combining these two techniques allows inserting the Unicode characters in randomized patterns with specific positions in the cover text to increase data hiding capacity with minimum effects on imperceptibility and security. Format-preserving encryption (FPE) is also used to encrypt a secret message without changing its size before the embedding processes. By comparing the proposed technique to already existing ones, the results demonstrate that it fulfils the cover file's capacity, imperceptibility, and security requirements.

Deep Learning-Based Neural Distinguisher for NIST Standard Format-Preserving Encryption (NIST 표준 형태 보존 암호에 대한 딥러닝 기반의 신경망 구별자)

  • Duk-young Kim;Hyun-Ji Kim;Kyung-Bae Jang;Se-Young Yoon;Hwa-jeong Seo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.175-178
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    • 2023
  • 차분 분석은 암호 분석기법 중 하나이며, 차분 공격을 위해 랜덤 데이터들로부터 차분 특성 (입/출력차분)을 만족하는 데이터를 구별해 내는 것을 구별자 공격이라 한다. Neural distinguisher는 구별자에 딥러닝을 적용한 것이다. 본 논문에서는 NIST 표준 형태보존암호인 FF1, FF3-1을 위한 단일 차분을 사용한 최초의 신경 구별자를 제안하였다. FF1은 차분으로 0F를 사용할 때, 숫자 및 소문자 도메인에서 차분 데이터 구별에 성공하였다 (정확도는 각각 0.85 및 0.52). FF3-1에서는 08을 사용할 때, 숫자 및 소문자 도메인에서 차분 데이터 구별에 성공하였다 (정확도는 각각 0.98 및 0.55).