A Secure Data Aggregation Algorithm Based on a Trust Mechanism.

data aggregation dynamic slicing trust mechanism underwater wireless sensor networks

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
04 Jul 2024
Historique:
received: 03 06 2024
revised: 29 06 2024
accepted: 03 07 2024
medline: 13 7 2024
pubmed: 13 7 2024
entrez: 13 7 2024
Statut: epublish

Résumé

Due to the uniqueness of the underwater environment, traditional data aggregation schemes face many challenges. Most existing data aggregation solutions do not fully consider node trustworthiness, which may result in the inclusion of falsified data sent by malicious nodes during the aggregation process, thereby affecting the accuracy of the aggregated results. Additionally, because of the dynamically changing nature of the underwater environment, current solutions often lack sufficient flexibility to handle situations such as node movement and network topology changes, significantly impacting the stability and reliability of data transmission. To address the aforementioned issues, this paper proposes a secure data aggregation algorithm based on a trust mechanism. By dynamically adjusting the number and size of node slices based on node trust values and transmission distances, the proposed algorithm effectively reduces network communication overhead and improves the accuracy of data aggregation. Due to the variability in the number of node slices, even if attackers intercept some slices, it is difficult for them to reconstruct the complete data, thereby ensuring data security.

Identifiants

pubmed: 39001131
pii: s24134352
doi: 10.3390/s24134352
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Natural Science Foundation of China
ID : 62162020

Auteurs

Changtao Liu (C)

School of Cyberspace Security, Hainan University, Haikou 570228, China.
Key Laboratory of Internet Information Retrieval of Hainan Province, Haikou 570228, China.

Jun Ye (J)

School of Cyberspace Security, Hainan University, Haikou 570228, China.
Key Laboratory of Internet Information Retrieval of Hainan Province, Haikou 570228, China.

Classifications MeSH