# A Survey on Satellite Communication System Security
## 5 Defense in Satellite Communication Systems
### Solutions for Integrity
#### 5.3.1 Physical Parameter Analysis Methods  
(i) Doppler Shift Analysis: The Doppler shift, also known as the Doppler effect, is a change in the frequency of a wave in relation to an observer who is moving relative to the wave source. In SCSs, the satellite usually moves at a high speed relative to the receiver, leading to the occurrence of the Doppler shift. This is observed as a change in the frequency of a wave in relation to an observer moving relative to the wave source. In this context, if the Doppler shift value transmitted from the actual satellite and the Doppler shift value of the received signal are consistent, it is considered a normal signal. However, if the received Doppler shift value exceeds a certain predefined limit, it may be indicative of a spoofing attack. The Doppler effect's role in combating GNSS spoofing attacks is highlighted in various research studies, each proposing unique methods to utilize this phenomenon. Paper [95] leverages Doppler offset detection (DOD) to differentiate between authentic and fake signals, relying on a model that highlights the necessity for a high level of resources for spoofers to match the Doppler offset of multiple satellite signals. In contrast, ref. [96] focuses on the Doppler effect's frequency changes due to the relative movement between the wave source and observer, especially in GNSS satellites. This study notes that spoofers, usually at a lower altitude, produce a larger Doppler shift, aiding in distinguishing between real and spoofed signals. Furthermore, the authors of [97] discuss the proportional relationship between the Doppler frequency and relative speed and its inverse proportionality to wavelength, leading to significant carrier frequency offsets in GNSS satellites. This paper emphasizes how, for static receivers, the Doppler shift changes slightly, whereas for moving receivers, these changes are more noticeable. This difference in Doppler shift changes between static and moving receivers helps in identifying authentic signals, as spoofed signals from a single spoofer will show uniform shift changes. Lastly, ref. [98] describes how the observed wave frequency differs from the transmitted frequency due to the relative velocity between the transmitter and receiver. This study advocates for monitoring the Doppler shifts of various GPS satellites to detect spoofing, as spoofed signals from the same platform exhibit identical Doppler shifts, unlike the varied shifts of authentic signals. (ii) Signal Parameter Analysis: GNSS spoofing detection using signal parameter analyses can be conducted in various ways, each utilizing different aspects of statistical signal analysis to enhance the accuracy and reliability of spoofing identification. In [99], phase-only analysis of variance (PANOVA) tests are introduced, focusing on detecting differences in the phases of sample groups to identify spoofed GNSS signals. This method effectively characterizes the spatial signature of GNSS signals, taking advantage of the difficulty experienced by spoofers when replicating certain signal features like correlation shapes and phase spatial signatures. In another approach, ref. [100] analyzes the sum-of-squares detector. This detector uses carrier phase measurements from two spatially separated GNSS receivers, formulating a decision statistic for real-time applications. The effectiveness of this method was proven through simulations and real GPS data experiments, demonstrating its practicality in revealing spoofing attacks. Ref. [101] proposes a new method based on the sequential probability ratio test (SPRT), emphasizing GNSS signals' vulnerability to jamming and spoofing. This method, suitable for the acquisition stage, compares various techniques for spoofing detection, including the correlation between two receivers and multi-antenna processing, acknowledging some practical limitations for civilian GNSS receivers. Ref.