scholarly journals Crypt-OR:A privacy-preserving system for exemplar-based object-removal over the cloud

2020 ◽  
Author(s):  
Vishesh Kumar Tanwar ◽  
Balasubramanian Raman ◽  
Rama Bhargava
Keyword(s):  
Low Cost ◽  
Privacy Preserving ◽  
Input Image ◽  
Cloud Services ◽  
Pixel Intensity ◽  
Object Removal ◽  
Correlation Attack ◽  
Cloud Server ◽  
Unbiased Manner ◽  
Shamir Secret Sharing Scheme

<div>Object removal is a technique for removing the undesired object(s) and then fill-in the empty region(s) in an image such that the modified image is visually plausible. The existing algorithms are unable to provide promising results when the region to be removed - has varying textured-neighborhood, is small in size and the depth of the image and, is of specific geometric shapes such as triangle</div><div>and rectangle. In this paper, we proposed a new algorithm by incorporating the merits of partial differential equations (PDEs) and exemplar-based schemes to address these challenges. The data term, which measures the continuity of</div><div>isophotes in exemplar-based methods, is modified by incorporating a regularizer term and partial derivatives up to second order of the input image. This regularizer enhances the strength of isophotes striking the boundary and boosts</div><div>the information propagation in an unbiased manner, in terms of pixel intensity values. Additionally, the low-cost, agility, and accessing flexibility benefits of cloud services have attracted user’s attention today. Besides, users are concerned about utilizing them for their data, as they are supported by untrusted third parties. Addressing these privacy concerns for object-removal in an image over the cloud server, we extended and modified our algorithm to make it compatible for (T; N)-threshold Shamir secret sharing scheme (SSS). This privacy-preserving system is an end-to-end system for object-removal in the ED over the cloud server namely Crypt-OR. Crypt-OR is evaluated by removing synthetically imposed objects in real-images. Further, Crypt-OR has proved to be secure under various pixel-based cryptographic attacks such as frequency-known attack and pixel-correlation attack. </div>

scholarly journals Crypt-OR:A privacy-preserving system for exemplar-based object-removal over the cloud

2020 ◽  
Author(s):  
Vishesh Kumar Tanwar ◽  
Balasubramanian Raman ◽  
Rama Bhargava
Keyword(s):  
Low Cost ◽  
Privacy Preserving ◽  
Input Image ◽  
Cloud Services ◽  
Pixel Intensity ◽  
Object Removal ◽  
Correlation Attack ◽  
Cloud Server ◽  
Unbiased Manner ◽  
Shamir Secret Sharing Scheme

<div>Object removal is a technique for removing the undesired object(s) and then fill-in the empty region(s) in an image such that the modified image is visually plausible. The existing algorithms are unable to provide promising results when the region to be removed - has varying textured-neighborhood, is small in size and the depth of the image and, is of specific geometric shapes such as triangle</div><div>and rectangle. In this paper, we proposed a new algorithm by incorporating the merits of partial differential equations (PDEs) and exemplar-based schemes to address these challenges. The data term, which measures the continuity of</div><div>isophotes in exemplar-based methods, is modified by incorporating a regularizer term and partial derivatives up to second order of the input image. This regularizer enhances the strength of isophotes striking the boundary and boosts</div><div>the information propagation in an unbiased manner, in terms of pixel intensity values. Additionally, the low-cost, agility, and accessing flexibility benefits of cloud services have attracted user’s attention today. Besides, users are concerned about utilizing them for their data, as they are supported by untrusted third parties. Addressing these privacy concerns for object-removal in an image over the cloud server, we extended and modified our algorithm to make it compatible for (T; N)-threshold Shamir secret sharing scheme (SSS). This privacy-preserving system is an end-to-end system for object-removal in the ED over the cloud server namely Crypt-OR. Crypt-OR is evaluated by removing synthetically imposed objects in real-images. Further, Crypt-OR has proved to be secure under various pixel-based cryptographic attacks such as frequency-known attack and pixel-correlation attack. </div>

scholarly journals SecureDL: A privacy preserving deep learning model for image recognition over cloud

2021 ◽  
Author(s):  
Vishesh Kumar Tanwar ◽  
Balasubramanian Raman ◽  
Amitesh Singh Rajput ◽  
Rama Bhargava
Keyword(s):  
Deep Learning ◽  
Image Recognition ◽  
Visual Information ◽  
Low Cost ◽  
Number System ◽  
Privacy Preserving ◽  
Cloud Services ◽  
Binary Number ◽  
Encryption Scheme ◽  
Encrypted Data

<div>The key benefits of cloud services, such as low cost, access flexibility, and mobility, have attracted users worldwide to utilize the deep learning algorithms for developing computer vision tasks. Untrusted third parties maintain these cloud servers, and users are always concerned about sharing their confidential data with them. In this paper, we addressed these concerns for by developing SecureDL, a privacy-preserving image recognition model for encrypted data over cloud. Additionally, we proposed a block-based image encryption scheme to protect images’ visual information. The scheme constitutes an order-preserving permutation ordered binary number system and pseudo-random matrices. The encryption scheme is proved to be secure in a probabilistic viewpoint and through various cryptographic attacks. Experiments are performed for several image recognition datasets, and the achieved recognition accuracy for encrypted data is close with non-encrypted data. SecureDL overcomes the storage, and computational overheads occurred in fully-homomorphic and multi-party computations based secure recognition schemes. </div>

scholarly journals Outsourcing Set Intersection Computation Based on Bloom Filter for Privacy Preservation in Multimedia Processing

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Hongliang Zhu ◽  
Meiqi Chen ◽  
Maohua Sun ◽  
Xin Liao ◽  
Lei Hu
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Low Cost ◽  
Bloom Filter ◽  
Privacy Preserving ◽  
Cloud Services ◽  
Multimedia Application ◽  
Computation Method ◽  
Multimedia Processing ◽  
Set Intersection

With the development of cloud computing, the advantages of low cost and high computation ability meet the demands of complicated computation of multimedia processing. Outsourcing computation of cloud could enable users with limited computing resources to store and process distributed multimedia application data without installing multimedia application software in local computer terminals, but the main problem is how to protect the security of user data in untrusted public cloud services. In recent years, the privacy-preserving outsourcing computation is one of the most common methods to solve the security problems of cloud computing. However, the existing computation cannot meet the needs for the large number of nodes and the dynamic topologies. In this paper, we introduce a novel privacy-preserving outsourcing computation method which combines GM homomorphic encryption scheme and Bloom filter together to solve this problem and propose a new privacy-preserving outsourcing set intersection computation protocol. Results show that the new protocol resolves the privacy-preserving outsourcing set intersection computation problem without increasing the complexity and the false positive probability. Besides, the number of participants, the size of input secret sets, and the online time of participants are not limited.

scholarly journals SecureDL: A privacy preserving deep learning model for image recognition over cloud

2021 ◽  
Author(s):  
Vishesh Kumar Tanwar ◽  
Balasubramanian Raman ◽  
Amitesh Singh Rajput ◽  
Rama Bhargava
Keyword(s):  
Deep Learning ◽  
Image Recognition ◽  
Visual Information ◽  
Low Cost ◽  
Number System ◽  
Privacy Preserving ◽  
Cloud Services ◽  
Binary Number ◽  
Encryption Scheme ◽  
Encrypted Data

<div>The key benefits of cloud services, such as low cost, access flexibility, and mobility, have attracted users worldwide to utilize the deep learning algorithms for developing computer vision tasks. Untrusted third parties maintain these cloud servers, and users are always concerned about sharing their confidential data with them. In this paper, we addressed these concerns for by developing SecureDL, a privacy-preserving image recognition model for encrypted data over cloud. Additionally, we proposed a block-based image encryption scheme to protect images’ visual information. The scheme constitutes an order-preserving permutation ordered binary number system and pseudo-random matrices. The encryption scheme is proved to be secure in a probabilistic viewpoint and through various cryptographic attacks. Experiments are performed for several image recognition datasets, and the achieved recognition accuracy for encrypted data is close with non-encrypted data. SecureDL overcomes the storage, and computational overheads occurred in fully-homomorphic and multi-party computations based secure recognition schemes. </div>

IoT based e-Healthcare System to Enable Remote Patient Care based on Cloud Server

2017 ◽  
Vol 7 (7) ◽  
pp. 36
Author(s):  
P.Venu Gopala Rao ◽  
Eslavath Raja ◽  
Ramakrishna Gandi ◽  
G. Ravi Kumar
Keyword(s):  
Low Cost ◽  
Vital Signs ◽  
Smart Phone ◽  
Medical Professional ◽  
Design Parameters ◽  
Cloud Server ◽  
Significant Area ◽  
Efficient Data ◽  
System Data ◽  
Remote Patient

IoT (Internet of Things) has become most significant area of research to design an efficient data enabled services with the help of sensors. In this paper, a low-cost system design for e-healthcare service to process the sensitive health data is presented. Vital signs of the human body are measured from the patient location and shared with a registered medical professional for consultation. Temperature and heart rate are the major signals obtained from a patient for the initial build of the system. Data is sent to a cloud server where processing and analysis is provided for the medical professional to analyze. Secure transmission and dissemination of data through the cloud server is provided with an authentication system and the patient could be able to track his data through a smart phone on connecting to the cloud server. A prototype of the system along with its design parameters has been discussed.

Resource Allocation in Cloud using Multi Bidding Model with User Centric Behavior Analysis

2020 ◽  
Vol 13 (5) ◽  
pp. 1008-1019
Author(s):  
N. Vijayaraj ◽  
T. Senthil Murugan
Keyword(s):  
Resource Allocation ◽  
Behavior Analysis ◽  
User Behavior ◽  
Low Cost ◽  
Cloud Services ◽  
Online Auction ◽  
Analysis Model ◽  
Efficient Resource ◽  
User Centric ◽  
Cloud Resources

Background: Number of resource allocation and bidding schemes had been enormously arrived for on demand supply scheme of cloud services. But accessing and presenting the Cloud services depending on the reputation would not produce fair result in cloud computing. Since the cloud users not only looking for the efficient services but in major they look towards the cost. So here there is a way of introducing the bidding option system that includes efficient user centric behavior analysis model to render the cloud services and resource allocation with low cost. Objective: The allocation of resources is not flexible and dynamic for the users in the recent days. This gave me the key idea and generated as a problem statement for my proposed work. Methods: An online auction framework that ensures multi bidding mechanism which utilizes user centric behavioral analysis to produce the efficient and reliable usage of cloud resources according to the user choice. Results: we implement Efficient Resource Allocation using Multi Bidding Model with User Centric Behavior Analysis. Thus the algorithm is implemented and system is designed in such a way to provide better allocation of cloud resources which ensures bidding and user behavior. Conclusion: Thus the algorithm Efficient Resource Allocation using Multi Bidding Model with User Centric Behavior Analysis is implemented & system is designed in such a way to provide better allocation of cloud resources which ensures bidding, user behavior. The user bid data is trained accordingly such that to produce efficient resource utilization. Further the work can be taken towards data analytics and prediction of user behavior while allocating the cloud resources.

scholarly journals Attribute-based pseudonymity for privacy-preserving authentication in cloud services

2021 ◽  
pp. 1-1
Author(s):  
Victor Sucasas ◽  
Georgios Mantas ◽  
Maria Papaioannou ◽  
Jonathan Rodriguez
Keyword(s):  
Privacy Preserving ◽  
Cloud Services

scholarly journals Privacy-preserving security solution for cloud services

2015 ◽  
Vol 13 (1) ◽  
pp. 20-31 ◽  
Author(s):  
L. Malina ◽  
J. Hajny ◽  
P. Dzurenda ◽  
V. Zeman
Keyword(s):  
Privacy Preserving ◽  
Cloud Services

scholarly journals An analysis of Approaches for Desktop Virtualization and Challenges

2021 ◽  
pp. 600-612
Author(s):  
Rupesh Kumar ◽  
Arun Kumar Yadav ◽  
H N Verma
Keyword(s):  
Computer System ◽  
Service Providers ◽  
Low Cost ◽  
New Technology ◽  
End Users ◽  
Cloud Services ◽  
Personal Computers ◽  
Small Organizations ◽  
Desktop Virtualization ◽  
Virtual Desktop

In the Information Technology world, cloud computing technology offering unlimited amount of IT resources and services to end users over the internet on pay-per-use basis. End users are accessing the cloud services on their mobile or personal computers. Service providers are upgrading their services very frequently to enhance the services, and to use their upgraded services, end users are also required to update the specification of their devices. But it will be very costly for the end users to upgrade their devices for high specification to use the enhanced services. Desktop Virtualization is an extensive technology of cloud services. It is the new concept, in which users can access the virtual desktop of required specifications, software and operating system on their old devices anytime and anywhere. With the help of desktop virtualization, users will be benefited by avoiding the cost of frequent upgradation of mobile or personal computer system. Desktop virtualization technology is proving to be a boon for large and small organizations who have to upgrade their computer system with new technology, which is a very costly and challenging process. Desktop virtualization avoids upgrading the hardware of the client machine repeatedly. It allows us to access all applications and data at a low cost on our old machine. This paper presents the comparative analysis of various approaches for desktop virtualization and various challenges which required the solution. Analysis presented in paper has been done based on various performance parameters which will provide the end users low-cost cloud services and best performance on their mobile or personal computers.

scholarly journals New Approaches of Cloud Services Access using Tonido Cloud Server for Real-Time Applications

2020 ◽  
Vol 26 (8) ◽  
pp. 83-99
Author(s):  
Sarah Haider Abdulredah ◽  
Dheyaa Jasim Kadhim
Keyword(s):  
Real Time ◽  
Video Streaming ◽  
Wireless Lan ◽  
Cloud Services ◽  
Heavy Load ◽  
Live Video ◽  
Live Video Streaming ◽  
Internet Connection ◽  
Cloud Server ◽  
Real Time Applications

A Tonido cloud server provides a private cloud storage solution and synchronizes customers and employees with the required cloud services over the enterprise. Generally, access to any cloud services by users is via the Internet connection, which can face some problems, and then users may encounter in accessing these services due to a weak Internet connection or heavy load sometimes especially with live video streaming applications overcloud. In this work, flexible and inexpensive proposed accessing methods are submitted and implemented concerning real-time applications that enable users to access cloud services locally and regionally. Practically, to simulate our network connection, we proposed to use the Raspberry-pi3 model B+ as a router wireless LAN (WLAN) that enables users to have the cloud services using different access approaches such as wireless and wireline connections. As a case study for a real-time application over the cloud server, it is suggested to do a live video streaming using an IP webcam and IVIDEON cloud where the streaming video can be accessed via the cloud server at any time with different users taking into account the proposed practical connections. Practical experiments showed and proved that accessing real-time applications of cloud services via wireline and wireless connections is improved by using Tonido cloud server's facilities.

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