Francesco Ardizzon;Laura Crosara;Stefano Tomasin;Nicola Laurenti
{"title":"Enhancing Spreading Code Authentication in GNSS: A Statistical Multisignal Approach","authors":"Francesco Ardizzon;Laura Crosara;Stefano Tomasin;Nicola Laurenti","doi":"10.1109/JISPIN.2025.3564896","DOIUrl":null,"url":null,"abstract":"The threat of signal spoofing against global navigation satellite system has grown in recent years and has motivated the study of antispoofing techniques. This article addresses the challenge of verifying the authenticity of signals protected by spreading code authentication. Conventional methods rely on either the correlation or cross-energy checks between the received signal and a local replica of the transmitted signal generated by the verifier using the authentic code. However, these methods are vulnerable to specific attacks. In particular, we show how to forge an effective spoofing signal just by using publicly available information. As a countermeasure, we propose a two-step authentication protocol leveraging the statistical independence of legitimate signals. First, we define a <italic>reliability metric</i> based on the generalized likelihood ratio for each signal, with higher values indicating greater signal reliability. In the second step, we select the most reliable signals to compute the position, velocity, and time (PVT) and perform a multisignal authentication check, combining the reliability metrics to validate the authenticity of the final PVT solution. Its robustness is proved by testing it against a wide class of attacks. Among others, these include the optimal attack against the cross-energy check and the attack that will be proven to be statistically optimal against the proposed check itself. Finally, we also test the performance of the scheme in a scenario where only a subset of the signals has been spoofed.","PeriodicalId":100621,"journal":{"name":"IEEE Journal of Indoor and Seamless Positioning and Navigation","volume":"3 ","pages":"128-141"},"PeriodicalIF":0.0000,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10979356","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Indoor and Seamless Positioning and Navigation","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10979356/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The threat of signal spoofing against global navigation satellite system has grown in recent years and has motivated the study of antispoofing techniques. This article addresses the challenge of verifying the authenticity of signals protected by spreading code authentication. Conventional methods rely on either the correlation or cross-energy checks between the received signal and a local replica of the transmitted signal generated by the verifier using the authentic code. However, these methods are vulnerable to specific attacks. In particular, we show how to forge an effective spoofing signal just by using publicly available information. As a countermeasure, we propose a two-step authentication protocol leveraging the statistical independence of legitimate signals. First, we define a reliability metric based on the generalized likelihood ratio for each signal, with higher values indicating greater signal reliability. In the second step, we select the most reliable signals to compute the position, velocity, and time (PVT) and perform a multisignal authentication check, combining the reliability metrics to validate the authenticity of the final PVT solution. Its robustness is proved by testing it against a wide class of attacks. Among others, these include the optimal attack against the cross-energy check and the attack that will be proven to be statistically optimal against the proposed check itself. Finally, we also test the performance of the scheme in a scenario where only a subset of the signals has been spoofed.