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Privacy-Preserving Cloud Computing: Ecosystem, Life Cycle, Layered Architecture and Future Roadmap
[article]
2022
arXiv
pre-print
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Privacy-Preserving Cloud Computing is an emerging technology with many applications in various fields. ...
This survey paper on privacy-preserving cloud computing can help pave the way for future research in related areas. ...
The cloud can then reconstruct the compressed images safely. -Image Denoising While image denoising can help to restore an image, [295] claims that it also raises security and privacy concerns. ...
arXiv:2204.11120v1
fatcat:tx75pckegjgqxg6tiibptiazbi
2021 Index IEEE Transactions on Dependable and Secure Computing Vol. 18
2022
IEEE Transactions on Dependable and Secure Computing
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-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021. ...
Wang, Z., +, TDSC May-June 2021 1474-1488 Image denoising Denoising in the Dark: Privacy-Preserving Deep Neural Network-Based Image Denoising. ...
Zhang, Y., +, TDSC March-April 2021 858-874 User Privacy from External Applications. ...
doi:10.1109/tdsc.2021.3129143
fatcat:iajg5t5wqrg2ricxbbllpgxaga
Privacy-Preserving Diffusion Model Using Homomorphic Encryption
[article]
2024
arXiv
pre-print
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2024 pre-print arXiv:2403.05794v1 fatcat:rpxewj5aovbupmhgrzzr32hcuu
In this paper, we introduce a privacy-preserving stable diffusion framework leveraging homomorphic encryption, called HE-Diffusion, which primarily focuses on protecting the denoising phase of the diffusion ...
Our approach marks a significant step towards integrating advanced cryptographic techniques with state-of-the-art generative models, paving the way for privacy-preserving and efficient image generation ...
A meticulous examination of the data flow within the forward and denoising stages reveals that the privacy of the intermediate image 𝑥 𝑖 is critical for the privacy-preserving framework. ...
arXiv:2403.05794v2
fatcat:3wkhrgmb6rgglfbaknldeif64y
Secure Object Detection Based on Deep Learning
2021
Journal of Information Processing Systems
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Privacy, integrity, and robustness for the extracted information are important security issues because deep learning enables object recognition in images and videos. ...
for images and videos. ...
Using GC, we protected the privacy of medical images from the external cloud database [36] , as shown in Fig. 10 . Fig. 9 . Vector matrix product in the convolution layer in CaRENets. ...
doi:10.3745/jips.03.0161
dblp:journals/jips/KimJ21
fatcat:hgrxur6kfbbirjo7b5dpgs4oim
A Cloud-based Framework to Secure Medical Image Processing
2018
Journal of Mobile Multimedia
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Regardless of its significant financial benefits, the transition to the cloud environment gives rise to security and privacy problems, especially in the healthcare domain. ...
In this case, healthcare professionals rely on remote applications delivered by an external provider to process patients' digital records. ...
This is achieved by using a combination of two cryptosystems: Paillier and privacy-preserving transform based on JL Transform. ...
doi:10.13052/jmm1550-4646.1434
fatcat:2sg23kygirbefhi4ef3fdrabhm
Replacement AutoEncoder: A Privacy-Preserving Algorithm for Sensory Data Analysis
2018
2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)
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In this paper, we propose a privacy-preserving sensing framework for managing access to time-series data in order to provide utility while protecting individuals' privacy. ...
We show that it can retain the recognition accuracy of state-of-the-art techniques while simultaneously preserving the privacy of sensitive information. ...
High-Level Architecture: a privacy-preserving mediator between cloud servers and data subject. ...
doi:10.1109/iotdi.2018.00025
dblp:conf/iotdi/MalekzadehCH18
fatcat:ib7y4xp64rcypbmjsydcmya4ja
An overview of Big Data in Healthcare: multiple angle analyses
2022
Journal of Smart Environments and Green Computing
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Additionally, we analyze the privacy of medical big data and summarize some methods and technologies to protect privacy. ...
In recent years, big data analytics by providing personalized medicine and regulation analysis, providing clinical risk intervention and forecast analysis, reducing waste and nursing patients with external ...
Additionally, Medical images in the cloud are often merged with images from other customers in a shared environment. ...
doi:10.20517/jsegc.2021.07
fatcat:kolcmsdmavafvpdxnva7yixppq
Advances of ECG Sensors from Hardware, Software and Format Interoperability Perspectives
2021
Electronics
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The software perspective describes various techniques (denoising, machine learning, deep learning, and privacy preservation) and other computer paradigms used in the software development and deployment ...
This article provides a comprehensive survey on ECG sensors from hardware, software and data format interoperability perspectives. ...
Finally, a study on the existing privacy preservation techniques utilized in the ECG monitoring system is presented.
Denoising Denoising refers to the removal of noise from an ECG signal. ...
doi:10.3390/electronics10020105
fatcat:l5eykpr3xncepbq6spoqjyit44
Tirtha – An Automated Platform to Crowdsource Images and Create 3D Models of Heritage Sites
[article]
2023
arXiv
pre-print
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Digital preservation of Cultural Heritage (CH) sites is crucial to protect them against damage from natural disasters or human activities. ...
Tirtha is accessible through a web interface at https://tirtha.niser.ac.in and can be deployed on-premise or in a cloud environment. ...
ACKNOWLEDGMENTS This project is funded by La fondation Dassault Systèmes, with support from Odisha State Archaeology. ...
arXiv:2308.01246v1
fatcat:ysxe3p3afrgmfmk4at5kgsiyq4
A Survey of Machine and Deep Learning Methods for Privacy Protection in the Internet of Things
2023
Sensors
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Consequently, it is crucial to preserve data privacy. This paper presents a comprehensive survey of recent Machine Learning (ML)- and Deep Learning (DL)-based solutions for privacy in IoT. ...
First, we present an in depth analysis of current privacy threats and attacks. Then, for each ML architecture proposed, we present the implementations, details, and the published results. ...
From reducing outsourcing to external services to parallel processing, from more efficient ML models to low-complexity algorithms, privacy protection research requires the effort of researchers in all ...
doi:10.3390/s23031252
pmid:36772292
pmcid:PMC9921397
fatcat:sfoc5s7zqfht7cmggxoaafgdmi
A Framework for Behavioral Biometric Authentication using Deep Metric Learning on Mobile Devices
[article]
2020
arXiv
pre-print
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When implemented on the mobile devices, they face new challenges from the behavioral dynamics, data privacy and side-channel leaks. ...
The experiments demonstrate authentication accuracy over 95% on three public datasets, a sheer 15% gain from multi-class classification with less data and robustness against brute-force and side-channel ...
Privacy Preserving and On-Device Learning Privacy preservation has been extensively studied recently in the machine learning community. The research takes three main directions. ...
arXiv:2005.12901v2
fatcat:efdfrjzhirfkzdd5o2ljrk4c6u
Fantômas: Understanding Face Anonymization Reversibility
[article]
2023
arXiv
pre-print
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2022 pre-print arXiv:2210.10651v1 fatcat:iajvdt55nze6bmmscedioz67g4
To mitigate this privacy risk, anonymizations employ transformations on clear images to obfuscate sensitive information, all while retaining some utility. ...
Face images are a rich source of information that can be used to identify individuals and infer private information about them. ...
The use case is the disruption of face recognition systems that may run on cloud hosted images while preserving enough utility so that the anonymized images might still be usable in the cloud environment ...
arXiv:2210.10651v2
fatcat:wayx5o6zobexxjhqgjv56ayqgu
Secure and Robust Machine Learning for Healthcare: A Survey
2020
IEEE Reviews in Biomedical Engineering
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In addition, we present potential methods to ensure secure and privacy-preserving ML for healthcare applications. ...
of cardiac arrest from one-dimensional heart signals to computer-aided diagnosis (CADx) using multi-dimensional medical images. ...
The idea of adding adequate noise in the database for preserving privacy was first introduced by C. Dwork in 2006 [153] . ...
doi:10.1109/rbme.2020.3013489
pmid:32746371
fatcat:wd2flezcjng4jjsn46t24c5yb4
Obfuscation Algorithm for Privacy-Preserving Deep Learning-Based Medical Image Analysis
2022
Applied Sciences
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., in a cloud based solution, privacy concerns have been raised. ...
As a result, the demand for privacy-preserving techniques that enable DL model training and inference on secured data has significantly grown. ...
Another privacy-preserving approach that has received increasing interest is image obfuscation. ...
doi:10.3390/app12083997
fatcat:tqsq3r6od5gdrmbm6hj6ml3cn4
Secure and Robust Machine Learning for Healthcare: A Survey
[article]
2020
arXiv
pre-print
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In addition, we present potential methods to ensure secure and privacy-preserving ML for healthcare applications. ...
of cardiac arrest from one-dimensional heart signals to computer-aided diagnosis (CADx) using multi-dimensional medical images. ...
The idea of adding adequate noise in the database for preserving privacy was first introduced by C. Dwork in 2006 [126] . ...
arXiv:2001.08103v1
fatcat:u6obszbeajcp5asciz5z5unmlq
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