Use of Supervised Machine Learning for GNSS Signal Spoofing Detection with Validation on Real-World...
Use of Supervised Machine Learning for GNSS Signal Spoofing Detection with Validation on Real-World Meaconing and Spoofing Data-Part I
About this item
Full title
Author / Creator
Publisher
Switzerland: MDPI
Journal title
Language
English
Formats
Publication information
Publisher
Switzerland: MDPI
Subjects
More information
Scope and Contents
Contents
The vulnerability of the Global Navigation Satellite System (GNSS) open service signals to spoofing and meaconing poses a risk to the users of safety-of-life applications. This risk consists of using manipulated GNSS data for generating a position-velocity-timing solution without the user's system being aware, resulting in presented hazardous misle...
Alternative Titles
Full title
Use of Supervised Machine Learning for GNSS Signal Spoofing Detection with Validation on Real-World Meaconing and Spoofing Data-Part I
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_1e0f36f1e399431ba367c3c77dbc10a5
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_1e0f36f1e399431ba367c3c77dbc10a5
Other Identifiers
ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s20041171
