Cloud-Based Data Collaboration: Balanced Anonymity and Monitoring

Over the last few years there has been an increased interest in group data transmission inside cloud systems. The rise in the use of computing via the cloud has made more visible an obvious fact: sharing data among computations running concurrently or on different dates but that are trying to solve part of a single scientific challenge is essential. Another problem in the reporting of cloud-based data exhibits is how to ensure both anonymity and traceability. We aim to provide a robust method for secure sharing and storage of potentially sensitive anonymous cloud data with some target entity by no more than one individual or legal corporation. The proposed solution in this regard is group signature along with key arrangement to introduce an effective traceable approach for sharing data among a group of users, their cooperation can remain anonymous on public clouds. Members can communicate anonymously with respect to the group signature when necessary, and optionally reveal their true identity. In addition, a shared teleconference key is created by Key Agreement to allow the group members secure data interchange and storage. Importantly, the grunt work to find a common conference key among participants is greatly reduced when an asymmetric-balancing unfinished block design approach for generating keys. Theoretical and experimental studies show that the method is safe and effective in group data sharing for cloud computing.

Authors

Institutions

Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/i3ceet61722.2024.10993851
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cloud-Based Data Collaboration: Balanced Anonymity and Monitoring

Suman Devi, Radhakrishna Dodmane, Charvi Vij, Monika Labana et al.
Big Data and Business Intelligence
article

Cloud-Based Data Collaboration: Balanced Anonymity and Monitoring

Suman Devi, Radhakrishna Dodmane, Charvi Vij, Monika Labana, Vinodh Gunnam, Govinda Rajulu. G
article en

Abstract

Over the last few years there has been an increased interest in group data transmission inside cloud systems. The rise in the use of computing via the cloud has made more visible an obvious fact: sharing data among computations running concurrently or on different dates but that are trying to solve part of a single scientific challenge is essential. Another problem in the reporting of cloud-based data exhibits is how to ensure both anonymity and traceability. We aim to provide a robust method for secure sharing and storage of potentially sensitive anonymous cloud data with some target entity by no more than one individual or legal corporation. The proposed solution in this regard is group signature along with key arrangement to introduce an effective traceable approach for sharing data among a group of users, their cooperation can remain anonymous on public clouds. Members can communicate anonymously with respect to the group signature when necessary, and optionally reveal their true identity. In addition, a shared teleconference key is created by Key Agreement to allow the group members secure data interchange and storage. Importantly, the grunt work to find a common conference key among participants is greatly reduced when an asymmetric-balancing unfinished block design approach for generating keys. Theoretical and experimental studies show that the method is safe and effective in group data sharing for cloud computing.

Small Business Administration (US), Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN), Shree Guru Gobind Singh Tricentenary University (IN), Parul University (IN)
Openalex Percentile: Top 52%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.