关键词: GNSS detection methods jamming machine learning models software-defined radio spoofing

来  源:   DOI:10.3390/s24134210   PDF(Pubmed)

Abstract:
Increased interest in the development and integration of navigation and positioning services into a wide range of receivers makes them susceptible to a variety of security attacks such as Global Navigation Satellite Systems (GNSS) jamming and spoofing attacks. The availability of low-cost devices including software-defined radios (SDRs) provides a wide accessibility of affordable platforms that can be used to perform these attacks. Early detection of jamming and spoofing interferences is essential for mitigation and avoidance of service degradation. For these reasons, the development of efficient detection methods has become an important research topic and a number of effective methods has been reported in the literature. This survey offers the reader a comprehensive and systematic review of methods for detection of GNSS jamming and spoofing interferences. The categorization and classification of selected methods according to specific parameters and features is provided with a focus on recent advances in the field. Although many different detection methods have been reported, significant research efforts toward developing new and more efficient methods remain ongoing. These efforts are driven by the rapid development and increased number of attacks that pose high-security risks. The presented review of GNSS jamming and spoofing detection methods may be used for the selection of the most appropriate solution for specific purposes and constraints and also to provide a reference for future research.
摘要:
对导航和定位服务的开发和集成到广泛的接收机中的兴趣增加,使得它们容易受到各种安全攻击,诸如全球导航卫星系统(GNSS)干扰和欺骗攻击。包括软件定义无线电(SDR)在内的低成本设备的可用性提供了可用于执行这些攻击的可负担得起的平台的广泛可访问性。干扰和欺骗干扰的早期检测对于缓解和避免服务降级至关重要。由于这些原因,发展高效的检测方法已经成为一个重要的研究课题,文献中已经报道了许多有效的检测方法。本调查为读者提供了对GNSS干扰和欺骗干扰检测方法的全面和系统的审查。根据特定参数和特征对所选方法进行分类和分类,重点是该领域的最新进展。尽管已经报道了许多不同的检测方法,为开发新的和更有效的方法而进行的重大研究工作仍在进行中。这些努力是由快速发展和造成高安全风险的攻击数量增加推动的。本文对GNSS干扰和欺骗检测方法进行了综述,可用于针对特定目的和约束条件选择最合适的解决方案,并为以后的研究提供参考。
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