In the event of a pandemic, AI can also help the pharmaceutical industry
research new medications.

  * •

The use of robots in surgery has gained favour as intelligent agent-based
robotics has advanced. However, the usage of robots in this capacity creates
security issues. AI method is based on algorithms like XGBoost plus Blockchain
integration where the Blockchain-based approach complements the AI-based EHR
data storage mechanism, in which AI maintains system security and Blockchain
cryptographically manages EHR data [216].

####  5.2.9 Role of AI and Smart IIoT to Mitigate the 6G challenges

The wireless communication system is moving toward automation, which can be
accomplished via AI-based smart technologies. However, with many advancements
come new obstacles. The most important of them is intrusion detection and
mitigation in a 6G system. The use of AI in maintaining privacy and security.
Sub-networks in 6G, which can be thought of as an extension of local 5G
networks outside vertical domains, may derive assistance from training-based
security solutions both within and across sub-networks. Other sub-networks’
behavior can be captured, and malicious traffic can be detected using ML-based
algorithms placed at the perimeter. Massive data transfers between sub-
networks may be ineffective because these networks are typically self-
contained. For communication efficiency, a sub-network can solely communicate
the learned security information with another. A second sub-network can take
the collaborative data, input it into its machine learning models, and apply
dynamic policies to other networks’ hostile traffic.
In contrast to current centralized cloud-based AI systems, 6G will rely
heavily on edge intelligence. In the vast device and data regime [259], the
dispersed nature facilitates the implementation of edge-based FL for network
safety, ensuring communication efficiency. 6G design envisions connected
intelligence and employs artificial intelligence at many levels of the network
structure [260]. At the cellular level, artificial intelligence has the
ability to prevent DoS attacks on cloud networks. The ability of a device to
enable multiple connections in a mesh network enables numerous base stations
to analyze the behavior of equipment using AI classification programs and
coordinately make decisions on the verification with the use of weighted
average techniques, as described in [261]. AI-powered predictive analytics can
identify attacks, such as 51 percent attacks on Blockchain, before they
happen. A quantum computer could put asymmetric key cryptography in jeopardy.
They can, however, give exponential speedups for AI/ML systems, allowing them
to complete previously impossible jobs considerably faster. In 6G, multi-
connectivity mesh networks with tiny cells enable devices to communicate
simultaneously via numerous base stations. Edge-based machine learning models
might be used to dynamically discover privacy-preserving routes, rate them,
and enable devices to transfer data via those routes based on the ranking. In
contrast to cloud-based centralized learning, federated learning keeps data
close to the user, enhancing data and location confidentiality. The 6G
subnetwork level AI maintains confidentiality within the subnetwork and only
shares learned data with the outside world to reduce security threats. AI-
based services privacy-preserving policy updates [262] have the ability to
provide wholly automated 6G networks while maintaining privacy.

##  6 Conclusion

In this survey, the authors provided a piece of state-of-the-art information
regarding Blockchain, AI, and smart IIoT on the basis of the current world
demand. This article offers excellent integration of these (BC-AI-IIoT)
techniques. Moreover, this survey efficiently discusses different
issues–security, privacy, confidentiality, and so on based on these
technologies. Then, it also presents the various tabular analyses regarding
the vast areas. A significant number of solutions, tools, and techniques have
been extensively analyzed in this survey. Additionally, some open issues and
opportunities have been discussed in this research. Although this research can
provide current and innovative information on the basis of BC, AI, and IIoT
technologies, this article still needs to cover extra information that can
properly mitigate the various problems and challenges in the different
domains. In the future, the authors suggest some taxonomies with proper groups
and apply these technologies in the other fields, such as smart cities,
innovative healthcare, smart vehicle management, etc.

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