Projects per year
Abstract
Edge computing brings data computation and storage closer to the mobile device to save response time for decision making. After being processed at the edge, commonly, the data will be uploaded to the cloud for further enriched analysis. For privacy concerns, local devices may encrypt the collected data before sending it to the cloud server. However, this treatment increases the servers processing time and makes it hard to pick out the desired data. In this paper, to address this problem, we design an encrypted data validation scheme, which enables the edge to clean the encrypted data to be uploaded. Because edge computing encompasses numerous edge devices from different service providers, we explore the public-key cryptographic mechanism to implement our secure data validation scheme. Considering potential risks from quantum computers, we propose to leverage ideal lattice to realize our protocol, which reaches better performance in both time and storage for edge devices. Extensive evaluation results show that our proposed proposal achieves considerable performance improvements in terms of communication and computation aspects. Particularly, compared to prior work, nearly 123x-238x speed up is achieved in our key derivation procedure and the storage cost of the secret key is reduced from 547MB to 1.7MB.
| Original language | English |
|---|---|
| Pages (from-to) | 656-669 |
| Journal | IEEE Transactions on Services Computing |
| Volume | 16 |
| Issue number | 1 |
| Online published | 9 Sept 2021 |
| DOIs | |
| Publication status | Published - Jan 2023 |
Research Keywords
- Cloud computing
- Data validation
- edge computing
- Encryption
- Lattices
- Logic gates
- Performance evaluation
- practical post-quantum security
- public key cryptographic mechanism
- Quantum computing
Fingerprint
Dive into the research topics of 'Towards Efficient Cryptographic Data Validation Service in Edge Computing'. Together they form a unique fingerprint.-
RIF-ExtU-Lead: Enabling Secure and Efficient Cross-Silo Federated Learning at Scale
Li, B. (Main Project Coordinator [External]) & WANG, C. (Principal Investigator / Project Coordinator)
1/02/21 → …
Project: Research
-
GRF: Towards Full Accounting for Leakage Exploitation and Mitigation in Encrypted Databases
WANG, C. (Principal Investigator / Project Coordinator)
1/01/21 → 31/12/24
Project: Research
-
ITF: Building Trustworthy and Secure Data Aggregation Services on Blockchain Platforms
WANG, C. (Principal Investigator / Project Coordinator)
1/03/20 → 31/08/21
Project: Research
Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver