A self-healing cybersecurity mechanism for cyberattacks targeting artificial neural network-based human brain implants controlling smart homes

Abstract

Brain computer interfaces (BCIs) are considered cyber-physical systems (CPSs) capable of computation, communication, and decision-making progress. The cybernetic capabilities are implanted in the brain for the purpose of reading and writing on neurons of the brain. While current applications of the human brain implant are for neurogenetics disorders such as Alzheimer's, there are futuristic applications of the human brain implant for communication between the brains of humans and computer-based devices. Despite the outstanding advantages of cyber-physical technology, new techniques are required to control in/external devices, and the system is vulnerable to cyber threats. This paper presents 1) an artificial neural network (ANN) technique to control the smart home devices via the brain implants, 2) different cyberattacks (i.e., Flooding, Scanning, False Data Injection, and Jamming) on the human brain implant, 3) a recovery technique to mitigate the impact of the proposed cyberattacks on the human brain implant. The results demonstrate the effectiveness of the proposed cybersecurity/self-healing technique to mitigate the well-known cyberattacks imposing the brain implant.