SYSTEMS AND METHODS TO DETECT GPS SPOOFING ATTACKS

Abstract: a method for detecting gps spoofing attacks includes providing a trained deep learning (dl) model based on neural networks, feeding gps signals into the trained dl model, using asymmetric shapley values (asvs) to calculate feature contributions, using the asvs to assign a non-uniform distribution over an ordering of features, obtaining causal structures among the features, applying the asvs to causal shapley additive explanation to obtain shapley attributions, incorporating the shapley attributions and the causal structures, and detecting gps spoofing attacks by running the trained dl model and using the causal structures, non-uniform distribution, feature contributions, and shapley attributions.

Inventor(s): Xin TIAN, Zhengyang FAN, Khanh PHAM, Erik BLASCH, Sixiao WEI, Dan SHEN, Genshe CHEN

CPC Classification: H04W12/121 (Wireless intrusion detection systems [WIDS]; Wireless intrusion prevention systems [WIPS])

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