PhD in Packet Spoofing Attack Against UAV System

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PhD in Packet Spoofing Attack Against UAV System

Spoofing is one of the important threats to be faced on GPS receivers. In this attack unknown users transmits fake signals to the GPS receiver on UAS. This type of fake signals may misguides the flight controls to get malfunction. Even sometimes road traffic signals may get changed due these type of malicious user’s fake transmitted signal. For that it needs a high-level security by classifying the signals received. Thus finally the efficiency of network results to provide a high probability of detection and low probability of false alarm through Packet spoofing attack UAV system.

RESEARCH APPROACH:

The extracted different parameters from different received GPS signal to develop the input features for the neural network. Next step is to apply specific clustering algorithm for dividing partition and hierarchical clustering which provide dendrogram based clustering results with various partitions. The predictive of random algorithm is the lowest and it has not made use of any data. Item based CF with PCC performs it much better to analyze the impact on the results. Let each cases are implemented certain typical CF algorithm and then it compares their performance in predictive accuracy with metric of MAE. Based on the Packet spoofing attack UAV system

PhD in Packet Spoofing Attack Against UAV System

LATEST ISSUES:

  • Due to absence of prior knowledge the evaluation of Bayesian decision is getting highly risky factor.
  • In certain cases that the multiple MAs are highly complicated due to usage of UAV is under the control of the GCS antenna.
  • The selection of similarity measures becomes crucial in certain specific mathematical models.
  • In some parameters of CF it have significant impacts on the predictive accuracy.
  • The public GPS receivers are not secure because of the unencrypted signals of satellite.
PhD in Packet Spoofing Attack Against UAV System

PROPOSED SOLUTION:

  • To minimize cost function and find the optimal weight and bias values by employing back-propagation algorithm.
  • Based on artificial neural network,supervised machine learning helps to receive GPS fake signals and which are fed to algorithm and make decisions.
  • On the basis of dendrogram various clustering results with different numbers of partitions are obtained easily in Packet spoofing attack UAV system

FUTURE PROPOSAL:

  • The “CF Algorithm” is utilized in this proposal Packet spoofing attack UAV system for employed in mobile applications.
  • In future there is a need to improve the processing capacity and time consumption based on developing algorithm for distributed computing system.

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