Evidence map›Paper›PMID 42230779›Full record

ArticleScientific reports2026

Blockchain-enabled secure authentication and privacy-preserving information sharing in VANETs using adaptive echo state networks and dual trapdoor homomorphic encryption.

Poonguzhali Ilango, Nagarajan Sivarajan, M P Rajakumar, Sumanth Venugopal

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Poonguzhali IlangoDepartment of Electronics and Communication Engineering, Panimalar Engineering College, Chennai, Tamil Nadu, 600123, India. dripoonguzhali@panimalar.ac.in.
Nagarajan SivarajanDepartment of Electronics and Communication Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, Tamil Nadu, 600089, India.
M P RajakumarDepartment of Artificial Intelligence and Data Science, St.Joseph's College of Engineering, Old Mamallapuram Road, Chennai, Tamil Nadu, 600 119, India.
Sumanth VenugopalManipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India. sumanth.v@manipal.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A blockchain-driven approach is presented to ensure robust authentication and private data distribution in Vehicular Ad Hoc Networks (VANETs). A primary objective to develop a robust authentication procedure using an Adaptive Echo State Network (AESNet) and a dual trapdoor homomorphic encryption method (DTHE-OMK) to enhance secure data transmission in VANETs. This work employs a combination of optimization strategies, including the Position Updated Enhanced Frilled Lizard Optimization (PUE-FLO) algorithm, to fine-tune the parameters of the AESNet for node authentication. The authentication analysis on accuracy provided results in the range of 6.323% of CWO-AESNet, 5.828% of TOT-AESNet, 8.353% of WOA-AESNet, 6.323% of FLO-AESNet for the optimization algorithms and 7.838% of DNN, 4.729% of LSTM, 4.248% of GRU, and 4.729% of ESNet for various literature models, respectively. This work concludes that the developed approach improves both integrity and safety of information shared across VANETs.

Indexed as

Adaptive blockchain-based authentication procedureAdaptive echo state networkDual trapdoor homomorphic encryption with optimal multi-keyPosition updated enhanced frilled lizard optimizationVANET

Identifiers

PMID42230779
PMCPMC13469664

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.