scholarly journals Quantum Encrypted Data Transfers in GRID

10.5772/14365 ◽  
2011 ◽  
Author(s):  
M. Dima ◽  
M. Dulea ◽  
A. Dima ◽  
M. Stoica ◽  
M. Udre
Keyword(s):  
Encrypted Data ◽  
Data Transfers

scholarly journals SINGLE HOP AUTHENTIC BROADCASTING IN SOCIAL MOBILE NETWORKS USING BLUETOOTH

2021 ◽  
Vol 4 (3) ◽  
pp. 30-38
Author(s):  
Basma A. Qasim ◽  
Emad H. Al-Hemiary
Keyword(s):  
Mobile Networks ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Text Messages ◽  
Power Supplies ◽  
Encrypted Data ◽  
Successful Communication ◽  
High Bandwidth ◽  
Data Transfers ◽  
Google Play

This paper aims to create infrastructure-free networking capabilities for people in need such as when inadequate infrastructure including mobile cell towers and power supplies are damaged or when all communication means are restricted. In general, this means finding a way to communicate without mobile cell towers, repeaters, or Wi-Fi hotspots on mobile devices. This paper focuses on introducing an ad-hoc network based on Bluetooth where users can communicate without barriers. The proposed network implementation uses Google’s API Nearby Connection which is one of Google Play Services that can provide high bandwidth, low latency, encrypted data transfers between nearby devices in a fully-offline P2P mode. Kotlin language was used to program an application called BlueEmergency installed on Android devices to broadcast data as bytes payloads in a form of text messages from one node to all nodes in proximity using Bluetooth only. The test and verification of the system are performed showed that successful communication is achieved with the latest versions of both the Android operating system and Bluetooth. Finally, the designed network can be extended to cover large geographical areas by multi-hopping the messages between devices to make the system more efficient to use in the time of need.

An Efficient Privacy-Preserving Rank Query over Encrypted Data in Cloud Computing

2012 ◽  
Vol 35 (11) ◽  
pp. 2215 ◽  
Author(s):  
Fang-Quan CHENG ◽  
Zhi-Yong PENG ◽  
Wei SONG ◽  
Shu-Lin WANG ◽  
Yi-Hui CUI
Keyword(s):  
Cloud Computing ◽  
Privacy Preserving ◽  
Encrypted Data

Research and design of querying approach for XML encrypted data

2010 ◽  
Vol 30 (4) ◽  
pp. 1099-1102
Author(s):  
Yu-yi KE ◽  
Shi-xiong XIA ◽  
Chu-jiao WANG
Keyword(s):  
Encrypted Data ◽  
Research And Design

A New User-controlled and Efficient Encrypted Data Sharing Model in Cloud Storage

2019 ◽  
Vol 13 (4) ◽  
pp. 356-363
Author(s):  
Yuezhong Wu ◽  
Wei Chen ◽  
Shuhong Chen ◽  
Guojun Wang ◽  
Changyun Li
Keyword(s):  
Data Sharing ◽  
Data Security ◽  
Cloud Storage ◽  
Screening Program ◽  
Original Data ◽  
Third Party ◽  
Active System ◽  
Encrypted Data ◽  
Active User ◽  
User Data

Background: Cloud storage is generally used to provide on-demand services with sufficient scalability in an efficient network environment, and various encryption algorithms are typically applied to protect the data in the cloud. However, it is non-trivial to obtain the original data after encryption and efficient methods are needed to access the original data. Methods: In this paper, we propose a new user-controlled and efficient encrypted data sharing model in cloud storage. It preprocesses user data to ensure the confidentiality and integrity based on triple encryption scheme of CP-ABE ciphertext access control mechanism and integrity verification. Moreover, it adopts secondary screening program to achieve efficient ciphertext retrieval by using distributed Lucene technology and fine-grained decision tree. In this way, when a trustworthy third party is introduced, the security and reliability of data sharing can be guaranteed. To provide data security and efficient retrieval, we also combine active user with active system. Results: Experimental results show that the proposed model can ensure data security in cloud storage services platform as well as enhance the operational performance of data sharing. Conclusion: The proposed security sharing mechanism works well in an actual cloud storage environment.

scholarly journals Cryptosystem Conversion, Packing and Matrix Processing of Homomorphically Encrypted Data: Application to IOT Devices

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 28302-28316
Author(s):  
Maxime Pistono ◽  
Reda Bellafqira ◽  
Gouenou Coatrieux
Keyword(s):  
Encrypted Data ◽  
Data Application ◽  
Iot Devices

scholarly journals What If Keys Are Leaked? towards Practical and Secure Re-Encryption in Deduplication-Based Cloud Storage

Information ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 142
Author(s):  
Weijing You ◽  
Lei Lei ◽  
Bo Chen ◽  
Limin Liu
Keyword(s):  
Experimental Evaluation ◽  
Cloud Storage ◽  
Security Analysis ◽  
Encrypted Data ◽  
Cloud Data ◽  
Storage Cost ◽  
Outsourced Data ◽  
Proof Of Ownership ◽  
Client Side ◽  
Over Time

By only storing a unique copy of duplicate data possessed by different data owners, deduplication can significantly reduce storage cost, and hence is used broadly in public clouds. When combining with confidentiality, deduplication will become problematic as encryption performed by different data owners may differentiate identical data which may then become not deduplicable. The Message-Locked Encryption (MLE) is thus utilized to derive the same encryption key for the identical data, by which the encrypted data are still deduplicable after being encrypted by different data owners. As keys may be leaked over time, re-encrypting outsourced data is of paramount importance to ensure continuous confidentiality, which, however, has not been well addressed in the literature. In this paper, we design SEDER, a SEcure client-side Deduplication system enabling Efficient Re-encryption for cloud storage by (1) leveraging all-or-nothing transform (AONT), (2) designing a new delegated re-encryption (DRE), and (3) proposing a new proof of ownership scheme for encrypted cloud data (PoWC). Security analysis and experimental evaluation validate security and efficiency of SEDER, respectively.

scholarly journals Privacy-Preserving Deep Neural Network Methods: Computational and Perceptual Methods—An Overview

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1367
Author(s):  
Raghida El El Saj ◽  
Ehsan Sedgh Sedgh Gooya ◽  
Ayman Alfalou ◽  
Mohamad Khalil
Keyword(s):  
Neural Networks ◽  
Classification Accuracy ◽  
Deep Neural Networks ◽  
Privacy Preserving ◽  
Sensitive Data ◽  
Encrypted Data ◽  
High Classification Accuracy ◽  
Hide Information ◽  
Network Methods ◽  
Cloud Environments

Privacy-preserving deep neural networks have become essential and have attracted the attention of many researchers due to the need to maintain the privacy and the confidentiality of personal and sensitive data. The importance of privacy-preserving networks has increased with the widespread use of neural networks as a service in unsecured cloud environments. Different methods have been proposed and developed to solve the privacy-preserving problem using deep neural networks on encrypted data. In this article, we reviewed some of the most relevant and well-known computational and perceptual image encryption methods. These methods as well as their results have been presented, compared, and the conditions of their use, the durability and robustness of some of them against attacks, have been discussed. Some of the mentioned methods have demonstrated an ability to hide information and make it difficult for adversaries to retrieve it while maintaining high classification accuracy. Based on the obtained results, it was suggested to develop and use some of the cited privacy-preserving methods in applications other than classification.

scholarly journals The CMS monitoring infrastructure and applications

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Christian Ariza-Porras ◽  
Valentin Kuznetsov ◽  
Federica Legger
Keyword(s):  
Distributed Computing ◽  
Compact Muon Solenoid ◽  
Hadron Collider ◽  
Efficient Operation ◽  
Workload Management ◽  
Future Developments ◽  
Cms Experiment ◽  
Data Transfers ◽  
Monitoring Architecture ◽  
Globally Distributed

AbstractThe globally distributed computing infrastructure required to cope with the multi-petabyte datasets produced by the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) at CERN comprises several subsystems, such as workload management, data management, data transfers, and submission of users’ and centrally managed production requests. To guarantee the efficient operation of the whole infrastructure, CMS monitors all subsystems according to their performance and status. Moreover, we track key metrics to evaluate and study the system performance over time. The CMS monitoring architecture allows both real-time and historical monitoring of a variety of data sources. It relies on scalable and open source solutions tailored to satisfy the experiment’s monitoring needs. We present the monitoring data flow and software architecture for the CMS distributed computing applications. We discuss the challenges, components, current achievements, and future developments of the CMS monitoring infrastructure.

Sign in / Sign up

Export Citation Format

Share Document