IBM does it again: patent for security of drones based on Blockchain
IBM filed an application to patent a system that would use Blockchain technology to address issues of privacy and security of drones, according to a document published by the United States Patent and Trademark Office (USPTO) on September 20.
The computer giant first presented the patent in March 2017, detailing how Blockchain could be used to securely store data associated with unmanned aerial vehicles (UAVs), more commonly known as drones.
The patent states that a Blockchain system can provide "effective techniques for managing data related to a UAV ... particularly when it is considered that a level of security risk is relatively high".
According to the presentation, such data may include the location of the drone, its manufacturer and / or model, its flight behavior, the capabilities of the model such as the resolution of the camera, contextual information such as weather conditions and the proximity of the vehicle to areas of restricted or prohibited flights.
The presentation of the patent suggests that the transaction data could be added "more frequently" as a block to the chain if a level of risk is considered high.
In terms of managing privacy concerns, if an unmanned aircraft is equipped with a high-resolution sensor, for example, the presentation proposes that this could be recorded in the Blockchain, adding additional data transactions each time it is detected that the sensor is activated.
As such, according to the presentation, a shared and immutable ledger can allow multiple parties, which could include other drones, airspace controllers, regulatory bodies, etc; participate as peers in risk management.
Validating nodes within the network could also grant special permissions, using the stored data transparently to verify that a drone has the authorization to fly in a particular area.
The patent also proposes that intelligent contracts could be used to interact with the Blockchain system with additional information generated by machine learning models or other algorithms that compute historical data, both inside and outside the chain. Such out-of-chain data could comprise, for example, raw video transmission data that has been captured during the flight of the drone.