TY - GEN
T1 - EyeEncrypt
T2 - 13th International Conference on Applications and Techniques in Information Security, ATIS 2022
AU - Hegde, Govardhan
AU - Gupta, Shourya
AU - Prabhu, Gautham Manuru
AU - Bhandary, Sulatha V.
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - Concerns in information and data security are addressed based on implementing practices to enhance data security mechanisms and feedbacks. Recent medical data breaches across the globe and rising cybersecurity threats from cyber warfare make research into data privacy more crucial in the system’s overall design. The advent of telemedicine and research in the applications of artificial intelligence in the medical domain makes a case for integrating enhanced image analysis inside a secure framework. The proposed modality implements critical principles of “authentication, authorization data integrity, data confidentiality, and the Principle of Least Privilege.” The use case chosen for this paper is on a retinal image DRIVE dataset. Retinal images have several applications in the field of medicine, which include the early detection of various diseases such as glaucoma. Characteristics intrinsic to retinal images make the vessel detection process difficult. Our proposed framework EyeEncrypt, aids in effective medical image segmentation on a secure integrated framework.
AB - Concerns in information and data security are addressed based on implementing practices to enhance data security mechanisms and feedbacks. Recent medical data breaches across the globe and rising cybersecurity threats from cyber warfare make research into data privacy more crucial in the system’s overall design. The advent of telemedicine and research in the applications of artificial intelligence in the medical domain makes a case for integrating enhanced image analysis inside a secure framework. The proposed modality implements critical principles of “authentication, authorization data integrity, data confidentiality, and the Principle of Least Privilege.” The use case chosen for this paper is on a retinal image DRIVE dataset. Retinal images have several applications in the field of medicine, which include the early detection of various diseases such as glaucoma. Characteristics intrinsic to retinal images make the vessel detection process difficult. Our proposed framework EyeEncrypt, aids in effective medical image segmentation on a secure integrated framework.
UR - http://www.scopus.com/inward/record.url?scp=85161091009&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85161091009&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-2264-2_9
DO - 10.1007/978-981-99-2264-2_9
M3 - Conference contribution
AN - SCOPUS:85161091009
SN - 9789819922635
T3 - Communications in Computer and Information Science
SP - 109
EP - 120
BT - Applications and Techniques in Information Security - 13th International Conference, ATIS 2022, Revised Selected Papers
A2 - Prabhu, Srikanth
A2 - Pokhrel, Shiva Raj
A2 - Li, Gang
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 30 December 2022 through 31 December 2022
ER -
