Real-Time Image Privacy Preservation using AES with Salt key and Gaussian Blur Algorithms with the application of Data Perturbation in Cloud
S. Sambath Kumar1, S. Devi2
1S. Sambath Kumar*, Department of Computer Science and Engineering, PRIST Deemed to be University, Thanjavur, India.
2S.Devi, Department of Electronics and Communication Engineering, PRIST Deemed to be University, Thanjavur, India.
Manuscript received on December 16, 2019. | Revised Manuscript received on December 22, 2019. | Manuscript published on January 10, 2020. | PP: 729-735 | Volume-9 Issue-3, January 2020. | Retrieval Number: B7176129219/2020©BEIESP | DOI: 10.35940/ijitee.B7176.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Rapid increase in image data produced by individuals and companies provoke privacy hitches such as unauthorized revelation of personal data and person’s individuality stealing, but it can be used to protect privacy of the user and also personal information. Data provider and Cloud Administrator are two types of users who have privilege and access. However, there is absence of research examining the effectiveness of implementing techniques to images as a technology that protects privacy. The Advanced Encryption Standard (AES) algorithm is selected for the login authentication process, which ensures the protection of information from unauthorized access and is proposed to create a random key generation. Data perturbation is used to add noise in databases, and Gaussian blur is done to introduce some degree of degradation in the original image. The obtained test results show that an AES with salt key can be randomly generated. In this process, security authentication is reinforced in the ciphertext changes that make up the key words for each encryption process. The result shows that the model is relatively fast with a time average of 0.034 s occupying less than 100kB of memory space.
Keywords: Lung Cancer Detection, CT Scan Image, Cancer, Image Processing.
Scope of the Article: Image Processing and Pattern Recognition