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The researchers tested their algorithm on a replica of a US Army combat ground vehicle and found it was 99% effective in preventing a malicious attack.Get a daily digest of the latest news in tech, science, and technology, delivered right to your mailbox. Subscribe now.
According to Professor Finn, an autonomous systems researcher at UniSA, the robot operating system is prone to cyberattacks because it is highly networked. He explained that Industry 4, characterized by advancements in robotics, automation, and the Internet of Things, requires robots to work together, where sensors, actuators, and controllers communicate and share information via cloud services. He added that this makes them very vulnerable to cyberattacks.
Dr Santoso, an artificial intelligence and cyber futures expert at Charles Sturt University, said the robot operating system needs adequate security measures in its coding scheme due to encrypted network traffic data and limited integrity-checking capability. He stated that their intrusion detection framework, which leverages the benefits of deep learning, is robust and highly accurate.
The researchers plan to test their algorithm on other robotic platforms, such as drones, which have faster and more complex dynamics than a ground robot.Safe and secure operations of robotic systems are of paramount importance. Aiming for achieving the trusted operation of a military robotic vehicle under contested environments, we introduce a new cyber-physical system based on the concepts of deep learning convolutional neural networks .
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