Improved Multileader Optimization with Shadow Encryption for Medical Images in IoT Environment

Nowadays,security plays an important role in Internet of Things(IoT)environment especially in medical services’domains like disease prediction and medical data storage.In healthcare sector,huge volumes of data are generated on a daily basis,owing to the involvement of advanced health care devices.In general terms,health care images are highly sensitive to alterations due to which any modifications in its content can result in faulty diagnosis.At the same time,it is also significant to maintain the delicate contents of health care images during reconstruction stage.Therefore,an encryption system is required in order to raise the privacy and security of healthcare data by not leaking any sensitive data.The current study introduces Improved Multileader Optimization with Shadow Image Encryption for Medical Image Security(IMLOSIE-MIS)technique for IoT environment.The aim of the proposed IMLOSIE-MIS model is to accomplish security by generating shadows and encrypting them effectively.To do so,the presented IMLOSIE-MIS model initially generates a set of shadows for every input medical image.Besides,shadow image encryption process takes place with the help of Multileader Optimization(MLO)withHomomorphic Encryption(IMLO-HE)technique,where the optimal keys are generated with the help of MLO algorithm.On the receiver side,decryption process is initially carried out and shadow image reconstruction process is conducted.The experimentation analysis was carried out on medical images and the results inferred that the proposed IMLOSIE-MIS model is an excellent performer compared to other models.The comparison study outcomes demonstrate that IMLOSIE-MIS model is robust and offers high security in IoT-enabled healthcare environment.

Public key based bidirectional shadow image authentication without pixel expansion in image secret sharing

Image secret sharing(ISS)is gaining popularity due to the importance of digital images and its wide application to cloud-based distributed storage and multiparty secure computing.Shadow image authentication generally includes shadow image detection and identification,and plays an important role in ISS.However,traditional dealer-participatory methods,which suffer from significant pixel expansion or storing auxiliary information,authenticate the shadow image mainly during the decoding phase,also known as unidirectional authentication.The authentication of the shadow image in the distributing(encoding)phase is also important for the participant.In this study,we introduce a public key based bidirectional shadow image authentication method in ISS without pixel expansion for a(k,n)threshold.When the dealer distributes each shadow image to a corresponding participant,the participant can authenticate the received shadow image with his/her private key.In the decoding phase,the dealer can authenticate each received shadow image with a secret key;in addition,the dealer can losslessly decode the secret image with any k or more shadow images.The proposed method is validated using theoretical analyses,illustrations,and comparisons.