TY - GEN
T1 - The privacy-preserving data publishing in medical application
T2 - 2nd International Cognitive Cities Conference, IC3 2019
AU - Chuang, Chieh Lin
AU - Wang, Pang Chieh
AU - Wang, Ming Shi
AU - Lai, Chin Feng
N1 - Publisher Copyright:
© Springer Nature Singapore Pte Ltd 2020.
PY - 2020
Y1 - 2020
N2 - As the time goes by and the development of science and technology, medical issues are becoming part of everyone’s life. People are paying much more attention to their own rights. When people transfer from one hospital to another for treatment, they may need to repeat multiple examinations, resulting unnecessary expenses and waste of medical resources. The Ministry of Health and Welfare promotes a system that uploads all patients’ medical files to an online database allowing them to check their own medical information and share it also, but it probably makes some privacy problem. In this paper, we found several methods that might be useful for image encryption, including, privacy-preserving data publishing (PPDP), scale invariant feature transform (SIFT), convolutional neural network (CNN), explored their algorithms and compare their strengths and weaknesses in the field of medical imaging encryption. Hoping to find a method for people to use the system without doubt.
AB - As the time goes by and the development of science and technology, medical issues are becoming part of everyone’s life. People are paying much more attention to their own rights. When people transfer from one hospital to another for treatment, they may need to repeat multiple examinations, resulting unnecessary expenses and waste of medical resources. The Ministry of Health and Welfare promotes a system that uploads all patients’ medical files to an online database allowing them to check their own medical information and share it also, but it probably makes some privacy problem. In this paper, we found several methods that might be useful for image encryption, including, privacy-preserving data publishing (PPDP), scale invariant feature transform (SIFT), convolutional neural network (CNN), explored their algorithms and compare their strengths and weaknesses in the field of medical imaging encryption. Hoping to find a method for people to use the system without doubt.
UR - http://www.scopus.com/inward/record.url?scp=85087280242&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85087280242&partnerID=8YFLogxK
U2 - 10.1007/978-981-15-6113-9_49
DO - 10.1007/978-981-15-6113-9_49
M3 - Conference contribution
AN - SCOPUS:85087280242
SN - 9789811561122
T3 - Communications in Computer and Information Science
SP - 438
EP - 447
BT - Cognitive Cities - 2nd International Conference, IC3 2019, Revised Selected Papers
A2 - Shen, Jian
A2 - Chang, Yao-Chung
A2 - Su, Yu-Sheng
A2 - Ogata, Hiroaki
PB - Springer
Y2 - 3 September 2019 through 6 September 2019
ER -