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http://hdl.handle.net/10603/477727
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DC Field | Value | Language |
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dc.coverage.spatial | An investigation of multilevel security approach for medical images in healthcare applications | |
dc.date.accessioned | 2023-04-20T09:32:31Z | - |
dc.date.available | 2023-04-20T09:32:31Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/477727 | - |
dc.description.abstract | In the past few decades, telemedicine has flourished with the advancements in communication technologies. Medical images are important tool for diagnostic procedure. Now they can be easily transmitted through communication channels around the globe. However, transmission over public network is prone to infringement of security, confidentiality, copyright and integrity. Loss or tampering of medical data can lead to wrong diagnosis. Thus security, confidentiality and integrity are of prime concern during transmission of medical images. One of the efficient methodologies for the security of information from medical images is by combing the encryption and watermarking method. The main objective of this research work is to introduce an efficient watermarking and encryption approaches for improving the security and authenticity of medical images in E-healthcare application. In this first work designed an efficient image encryption scheme for medical image security. Initially, medical images are taken as an input. The images are scrambled using Combined Linear Congruential Generator (CLCG) with Bit Rotation Operation (BRO) and the bit planes will be generated. From the generated bit planes, DNA encoding will be done which will resultant with the DNA sequences. After DNA sequence generation, decoding will be performed which will result with the recombines bit planes. These regenerated bit planes will be processed using XOR operation to generate the encrypted images. Decryption process is done by reverse process of encryption. Experimentation results showed that correlation among pixels is reduced while maximizing entropy. In second research work, designed a robust method of hiding patient secrete data using hybridization of Arnold transform and LSB technique for medical image At first, medical image segmentation is performed by using Fuzzy C Means (FCM) clustering. The Secret Patient Information (SPI) is encrypted using AES algorithm and inserted to cover medical image (ROI) to get a secure watermarked medical image. | |
dc.format.extent | xx,131p. | |
dc.language | English | |
dc.relation | p.121-130 | |
dc.rights | university | |
dc.title | An investigation of multilevel security approach for medical images in healthcare applications | |
dc.title.alternative | ||
dc.creator.researcher | Shankar, A | |
dc.subject.keyword | Engineering and Technology | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Imaging Science and Photographic Technology | |
dc.subject.keyword | Healthcare applications | |
dc.description.note | ||
dc.contributor.guide | Kannammal, A | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Information and Communication Engineering | |
dc.date.registered | ||
dc.date.completed | 2022 | |
dc.date.awarded | 2022 | |
dc.format.dimensions | 21cm. | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 25.12 kB | Adobe PDF | View/Open |
02_prelim_pages.pdf | 962.4 kB | Adobe PDF | View/Open | |
03_contents.pdf | 365.62 kB | Adobe PDF | View/Open | |
04_abstracts.pdf | 8.23 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 414.23 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 342.02 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 810.12 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 459.75 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 601.34 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 29.12 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 266.05 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 162.86 kB | Adobe PDF | View/Open |
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