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Research on WGAN models with Rényi Differential Privacy
Sujin Lee, Cheolhee Park, Dowon Hong, Jae-kum Kim
http://doi.org/10.5626/JOK.2021.48.1.128
Personal data is collected through various services and managers extract values from the collected data and provide individually customized services by analyzing the results. However, data that contains sensitive information, such as medical data, must be protected from privacy breaches. Accordingly, to mitigate privacy invasion, Generative Adversarial Network(GAN) is widely used as a model for generating synthetic data. Still, privacy vulnerabilities exist because GAN models can learn not only the characteristics of the original data but also the sensitive information contained in the original data. Hence, many studies have been conducted to protect the privacy of GAN models. In particular, research has been actively conducted in the field of differential privacy, which is a strict privacy notion. But it is insufficient to apply it to real environments in terms of the usefulness of the data. In this paper, we studied GAN models with Rényi differential privacy, which preserve the utility of the original data while ensuring privacy protection. Specifically, we focused on WGAN and WGAN-GP models, compared synthetic data generated from non-private and differentially private models, and analyzed data utility in each scenario.
Research for Speed Improvement Method of Lightweight Block Cipher CHAM using NEON SIMD
Sujin Lee, Junyoung Kang, Dowon Hong, Changho Seo
http://doi.org/10.5626/JOK.2019.46.5.485
As embedded devices and IoT devices are being developed, lightweight block ciphers have been proposed to achieve confidentiality on low-end devices. Recently, a lightweight block cipher algorithm, called CHAM, with 4-branch Feistel structure was proposed in Korea. It is consists of CHAM-64/128, CHAM-128/128, and CHAM-128/256 depending on the size of plaintext and secret key. CHAM, which is based on ‘stateless on the fly’ key schedule and ARX operations, is efficient on embedded devices, especially on low-end devices. In this paper, we analyze the lightweight block cipher CHAM and study an optimization method on a high-end IoT device. We implemented a serial code by independently generating round keys and leveraging 4-branch Feistel structure, and optimized CHAM using NEON-SIMD on ARM Cortex-A53.
Practically Secure Key Exchange Scheme based on Neural Network
Sooyong Jeong, Dowon Hong, Changho Seo
http://doi.org/10.5626/JOK.2019.46.2.208
Key exchange is one of the major aspects in cryptography. Recently, compared to the existing key exchange schemes, more efficient key exchange schemes have been proposed based on neural network learning. After the first key exchange scheme based on neural network was proposed, various attack models have been suggested in security analysis. Hebbian learning rule is vulnerable to majority attack which is the most powerful attack. Anti Hebbian learning rule is secure against majority attack has a limitation in efficiency, so we can only use key exchange scheme based on random walk learning rule which is more secure and efficient than the others. However, if we use random walk learning rule, the efficiency which is advantage about neural cryptography is reduced than the other learning rules. In this paper we analyze random walk and neural cryptography, and we propose new learning rule which is more efficient than existing random walk learning rule. Also, we theoretically analyze about key exchange scheme which is uses new learning rule and verify the efficiency and security by implementing majority attack model.
Secure Format-Preserving Encryption for Message Recovery Attack
Sooyong Jeong, Dowon Hong, Changho Seo
http://doi.org/10.5626/JOK.2017.44.8.860
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.
A Secure and Practical Encrypted Data De-duplication with Proof of Ownership in Cloud Storage
Cheolhee Park, Dowon Hong, Changho Seo
In cloud storage environment, deduplication enables efficient use of the storage. Also, in order to save network bandwidth, cloud storage service provider has introduced client-side deduplication. Cloud storage service users want to upload encrypted data to ensure confidentiality. However, common encryption method cannot be combined with deduplication, because each user uses a different private key. Also, client-side deduplication can be vulnerable to security threats because file tag replaces the entire file. Recently, proof of ownership schemes have suggested to remedy the vulnerabilities of client-side deduplication. Nevertheless, client-side deduplication over encrypted data still causes problems in efficiency and security. In this paper, we propose a secure and practical client-side encrypted data deduplication scheme that has resilience to brute force attack and performs proof of ownership over encrypted data.
Encrypted Data Deduplication Using Key Issuing Server
Hyun-il Kim, Cheolhee Park, Dowon Hong, Changho Seo
Data deduplication is an important technique for cloud storage savings. These techniques are especially important for encrypted data because data deduplication over plaintext is basically vulnerable for data confidentiality. We examined encrypted data deduplication with the aid of a key issuing server and compared Convergent Encryption with a technique created by M.Bellare et al. In addition, we implemented this technique over not only Dropbox but also an open cloud storage service, Openstack Swift. We measured the performance for this technique over Dropbox and Openstack Swift. According to our results, we verified that the encrypted data deduplication technique with the aid of a key issuing server is a feasible and versatile method.
An Implementation of an SHA-3 Hash Function Validation Program and Hash Algorithm on 16bit-UICC
Hee-Woong Lee, Dowon Hong, Hyun-il Kim, ChangHo Seo, Kishik Park
A hash function is an essential cryptographic algorithm primitive that is used to provide integrity to many applications such as message authentication codes and digital signatures. In this paper, we introduce a concept and test method for a Cryptographic Algorithm Validation Program (CAVP). Also, we design an SHA-3 CAVP program and implement an SHA-3 algorithm in 16bit-UICC. Finally, we compare the efficiency of SHA-3 with SHA-2 and evaluate the exellence of the SHA-3 algorithm.
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