Carding 4 Carders
Professional
What prevented autonomous systems from opposing the "man in the middle" and how will everything change now?
Researchers in Australia have developed an algorithm that can instantly detect and block man-in-the-middle hacker attacks on unmanned military robots.
A ground-based GVT-BOT model was chosen for the experiment. Experts from Charles Sturt University and the University of South Australia have applied deep learning techniques to mimic the workings of the human brain. The program demonstrated 99% efficiency in countering malicious activity. At the same time, less than 2% of false positives were detected.
Professor Anthony Finn, an expert in autonomous systems, said that their method of detecting cyber attacks is superior to other techniques known to the world. He focused on the shortcomings of the robot operating system (ROS) and its complex network structure: "In the era of Industry 4.0, as robotics and the Internet of Things spread, robots are increasingly interacting with each other. They exchange data through cloud services, which increases their vulnerability."
GVT-BOT is no exception. Because of its high network integration, it always remains a potential target, because active traffic processing makes it difficult to detect anomalies.
Industry 4.0 is a term that refers to a new stage in the industrial revolution. Automation, cloud technologies and artificial intelligence play a big role in it.
At the same time, Finn emphasizes that the development of computing technologies also does not stand still and allows you to create more advanced security mechanisms. The new algorithm, according to the scientist, has high accuracy and is able to process large amounts of data, which makes it ideal for protecting such complex systems as ROS.
In the future, the researchers plan to test their development on other robotic devices, for example, on drones - their dynamics are much more complex compared to ground robots.
Researchers in Australia have developed an algorithm that can instantly detect and block man-in-the-middle hacker attacks on unmanned military robots.
A ground-based GVT-BOT model was chosen for the experiment. Experts from Charles Sturt University and the University of South Australia have applied deep learning techniques to mimic the workings of the human brain. The program demonstrated 99% efficiency in countering malicious activity. At the same time, less than 2% of false positives were detected.
Professor Anthony Finn, an expert in autonomous systems, said that their method of detecting cyber attacks is superior to other techniques known to the world. He focused on the shortcomings of the robot operating system (ROS) and its complex network structure: "In the era of Industry 4.0, as robotics and the Internet of Things spread, robots are increasingly interacting with each other. They exchange data through cloud services, which increases their vulnerability."
GVT-BOT is no exception. Because of its high network integration, it always remains a potential target, because active traffic processing makes it difficult to detect anomalies.
Industry 4.0 is a term that refers to a new stage in the industrial revolution. Automation, cloud technologies and artificial intelligence play a big role in it.
At the same time, Finn emphasizes that the development of computing technologies also does not stand still and allows you to create more advanced security mechanisms. The new algorithm, according to the scientist, has high accuracy and is able to process large amounts of data, which makes it ideal for protecting such complex systems as ROS.
In the future, the researchers plan to test their development on other robotic devices, for example, on drones - their dynamics are much more complex compared to ground robots.
