Abstract
Unmanned aerial vehicles (UAVs) can be used for a variety of illegal activities (e.g., industrial espionage, smuggling, terrorism). Given their growing popularity and availability, and advances in communications technology, more sophisticated ways to disable these vehicles must be sought. Various forms of jamming are used to disable drones, but more advanced techniques such as deception and UAV takeover are considerably difficult to implement, and there is a large research gap in this area. Currently, machine and deep learning techniques are popular and are also used in various drone-related applications. However, no detailed research has been conducted so far on the use of these techniques for jamming and deception of UAVs. This paper focuses on exploring the current techniques in the area of jamming and deception. A survey on the use of machine or deep learning specifically in UAV-related applications is also conducted. The paper provides insight into the issues described and encourages more detailed research in this area.
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Cited by
1 articles.
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1. Attacks, Detection, and Prevention on Commercial Drones: A Review;2024 International Conference on Image Processing and Robotics (ICIPRoB);2024-03-09