Selective Encryption Algorithm for 3D Printing Model Based on Clustering and DCT Domain

Giao N. Pham; Ki-Ryong Kwon; Eung-Joo Lee; Suk-Hwan Lee

doi:10.5626/JCSE.2017.11.4.152

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저널정보

한국정보과학회
Journal of Computing Science and Engineering 학술저널
Journal of Computing Science and Engineering Vol.11 No.4
2017.12 152 - 159 (8page)
DOI : 10.5626/JCSE.2017.11.4.152

저자정보

Giao N. Pham (Pukyong National University)
Ki-Ryong Kwon (Pukyong National University)
Eung-Joo Lee (Tongmyong University)
Suk-Hwan Lee (Tongmyong University)

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초록·키워드

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Three-dimensional (3D) printing is applied to many areas of life, but 3D printing models are stolen by pirates and distributed without any permission from the original providers. Moreover, some special models and anti-weapon models in 3D printing must be secured from the unauthorized user. Therefore, 3D printing models must be encrypted before being stored and transmitted to ensure access and to prevent illegal copying. This paper presents a selective encryption algorithm for 3D printing models based on clustering and the frequency domain of discrete cosine transform. All facets are extracted from 3D printing model, divided into groups by the clustering algorithm, and all vertices of facets in each group are transformed to the frequency domain of a discrete cosine transform. The proposed algorithm is based on encrypting the selected coefficients in the frequency domain of discrete cosine transform to generate the encrypted 3D printing model. Experimental results verified that the proposed algorithm is very effective for 3D printing models. The entire 3D printing model is altered after the encryption process. The decrypting error is approximated to be zero. The proposed algorithm provides a better method and more security than previous methods.

#3D printing data #3D printing security #Selective encryption #DCT #Clustering