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Fang Ren, Xuan Shi, Enya Tang and Mengmeng Zeng
To protect the security of medical images and to improve the embedding ability of data in encrypted medical images, this paper proposes a permutation ordered binary (POB) number system-based hiding and authentication scheme for medical images, which incl...
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Woonghee Lee and Younghoon Kim
This study introduces a deep-learning-based framework for detecting adversarial attacks in CT image segmentation within medical imaging. The proposed methodology includes analyzing features from various layers, particularly focusing on the first layer, a...
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Jih-Ching Chiu, Guan-Yi Lee, Chih-Yang Hsieh and Qing-You Lin
In computer vision and image processing, the shift from traditional cameras to emerging sensing tools, such as gesture recognition and object detection, addresses privacy concerns. This study navigates the Integrated Sensing and Communication (ISAC) era,...
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Manjur Kolhar and Sultan Mesfer Aldossary
Deep learning (DL) algorithms can improve healthcare applications. DL has improved medical imaging diagnosis, therapy, and illness management. The use of deep learning algorithms on sensitive medical images presents privacy and data security problems. Im...
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Ammar Odeh, Anas Abu Taleb, Tareq Alhajahjeh and Francisco Navarro
Securing medical imaging poses a significant challenge in preserving the confidentiality of healthcare data. Numerous research efforts have focused on fortifying these images, with encryption emerging as a primary solution for maintaining data integrity ...
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Rui-Hua Liu and Quan Zhou
With the increasing requirements for the security of medical data, military data, and other data transmission, data hiding technology has gradually developed from only protecting the security of secret data to all transmission data. As a necessary techni...
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Jiafu Liu, Zhiyuan Yao, Shirui Guo, Hongjun Xie and Genke Yang
Image classification is widely used in industrial defect detection, medical diagnosis, social welfare, and other fields, in which privacy and security of models and data must be involved. For example, in diamond synthesis, the diamond substrate image ann...
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Kazuki Koga and Kazuhiro Takemoto
Universal adversarial attacks, which hinder most deep neural network (DNN) tasks using only a single perturbation called universal adversarial perturbation (UAP), are a realistic security threat to the practical application of a DNN for medical imaging. ...
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Andreea Bianca Popescu, Ioana Antonia Taca, Anamaria Vizitiu, Cosmin Ioan Nita, Constantin Suciu, Lucian Mihai Itu and Alexandru Scafa-Udriste
Deep learning (DL)-based algorithms have demonstrated remarkable results in potentially improving the performance and the efficiency of healthcare applications. Since the data typically needs to leave the healthcare facility for performing model training...
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Yuqiang Dou and Ming Li
Security of image communication is more and more important in many applications such as the transmission of military and medical images. To meet the requirement, a new color image encryption algorithm using a new one-dimension (1D) chaotic map was propos...
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