Quick Navigation
Topics
Quantum Machine Learning
Quantum Simulation
A Four-Party Quantum Secret-Sharing Scheme based on Grover's Search Algorithm
arXiv
Authors: Deepa Rathi, Farhan Musanna, Sanjeev Kumar
Year
2021
Paper ID
6771
Status
Preprint
Abstract Read
~2 min
Abstract Words
116
Citations
N/A
Abstract
The work presents an amalgam of quantum search algorithm (QSA) and quantum secret sharing (QSS). The proposed QSS scheme utilizes Grover's three-particle quantum state. In this scheme, the dealer prepares an encoded state by encoding the classical information as a marked state and shares the states' qubits between three participants. The participants combine their qubits and find the marked state as a measurement result of the three-qubit state. The security analysis shows the scheme is stringent against malicious participants or eavesdroppers. In comparison to the existing schemes, our protocol fairs pretty well and has a high encoding capacity. The simulation analysis is done on the cloud platform IBM-QE thereby showing the practical feasibility of the scheme.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2021 reference point for readers tracking recent quantum research.
- The work presents an amalgam of quantum search algorithm (QSA) and quantum secret sharing (QSS).
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.