Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Impact of Target Tracking Module in GPS Spoofer Design for Stealthy GPS Spoofing(Institute of Electrical and Electronics Engineers Inc., 2020) Pardhasaradhi, P.; Srihari, S.; Aparna., P.This paper presents six different filtering algorithms (Kalman Filter (KF), Reduced State filter (RSF), Separate Covariance filter (SCF), Autonomous Multiple Model (AMM), Generalized Pseudo Bayesian (GPB1 and GPB2), Interactive Multiple Model (IMM)) and its performances to evaluate the impact of target tracking module on GPS spoofing. GPS spoofers are famous for misleading the GPS receivers by imposing mimic GPS signals. The spoofer incorporates the external delays to the captured authentic satellite signals and retransmits towards the GPS receiver to accomplish spoofing. The external delay is a function of the distance between the spoofer and GPS receiver. Therefore, there is a need to estimate the time-varying dynamics of the target by employing a target tracking module to enhance the spoofer performance. In this paper, a comprehensive Simulation study has been carried out to evaluate the performance of various target tracking filters. Simulation results reveals that the multiple model based filters giving good performance for the linear and maneuvering target compared to single model filters. Further, it is evident that the IMM filter gives superior performance in tracking a target and computationally efficient compared to AMM, GPB1, and GPB2 filters. The suggested IMM with KF and EKF configuration provides improved performance (in terms of computational complexity by 43.5%, in tracking position root mean square error (PRMSE) by 26%, and in spoofing PRMSE by 29.6%) compared to two KF filters GPB2 technique. Furthermore, the results also reveals the deployment of IMM based filters into the spoofer module substantially enriches the spoofing efficiency. © 2020 IEEE.Item Stealthy GPS Spoofing: Spoofer Systems, Spoofing Techniques and Strategies(Institute of Electrical and Electronics Engineers Inc., 2020) Pardhasaradhi, P.; Srihari, S.; Aparna., P.Global Positioning System (GPS) and its counterparts are popular for its position, velocity, and time (PVT) information. GPS is vulnerable to spoofing attacks. A comprehensive understanding of GPS spoofing attack requirements, impacts, type of target, and success rates are required to develop anti-spoofing algorithms. This paper aims to provide an understanding regarding the selection of spoofer type, operating location of the spoofer, the impact of spoofing, spoofing techniques, and strategies for performing stealthy GPS spoofing for various applications. This work proposes four novel spoofing techniques (persistent false target, persistent walking target, persistent pull-off target, and persistent walking pull-off target models) and their mathematical realization. Further, it provides efficient spoofing strategies (static pull-off, dynamic pull-off, walking position, and stationary position) for various civilian and military applications. Moreover, various types of targets and their GPS spoofing vulnerabilities have been incorporated (yacht, aircraft, trucks, trains, security tagged criminals, and mobile phones). © 2020 IEEE.Item Robust Positioning and Grubbs Outlier Test for Navigation in GPS Spoofing Environment(Institute of Electrical and Electronics Engineers Inc., 2022) Pardhasaradhi, B.; Lingadevaru, P.; Bn, B.R.; Srihari, P.; Cenkarmaddi, L.R.Global positioning system (GPS) is favored to provide the position, velocity, and time (PVT) details across the globe. This paper proposes an epoch-by-epoch robust positioning algorithm followed by the Grubbs outlier test to address the GPS spoofing problem. We propose to accept both authentic and spoofed GPS signals to compute the robust positions. The robust positioning considers all possible combinations of measurements and generates several position estimates, which contain actual position, spoof position, and biased positions. In this case, the positions evolved due to spoof pseudorange measurements must be removed. Hence, we model eliminating spoof locations as an outlier problem and is addressed using Grubbs outlier test. The median of the processed data after the Grubbs test is the positional information at that epoch. Moreover, this problem is also extended to the Kalman filter's (KF) framework to address the time-varying kinematics of the target. Simulations are carried out for various numbers of actual and spoofed pseudorange measurements. In order to illustrate the robustness of the proposed technique, position root mean square error (PRMSE) is taken as a metric. © 2022 IEEE.