Affiliations: [a] School of Computer Science and Technology, Wuhan University, Wuhan, Hubei, China | [b] Faculty of Engineering, Environment and Computing, Coventry University, Coventry, UK
Correspondence:
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Corresponding author: W.D. Li, Faculty of Engineering, Environment and Computing, Coventry University, Coventry, UK. Tel.: +44 7557425332; E-mail:weidong.li@coventry.ac.uk
Abstract: When a Computer Aided Design (CAD) model is shared in
cloud for collaboration, it is a challenge to encrypt the confidential
design features of the model for effective knowledge protection. This paper
presents a novel encryption approach, which is based on geometric
transformation encryption mechanisms on feature-based CAD models in
supporting cloud-enabled collaboration. The innovation of the approach is
centered on an Enhanced Encryption Transformation Matrix (EETM), which is
characterized parametric, randomized and self-adaptive for feature
encryption. Controllable parameters for transforming features in terms of
zoom and deformation are defined in the EETM to facilitate users to conduct
encryption transformation flexibly. A random probability mechanism is
embedded into the parameters of the EETM in order to guarantee the security
of the encrypted model. Furthermore, the parameters in the EETM are further
enhanced to be self-adaptive to ensure the geometric validity of the
encrypted model. The approach has been validated via a number of complex
models to demonstrate the applicability and effectiveness for industrial
applications.
