  Standard security protocols like SSL, TLS, IPSec etc. have high memory and
processor consumption which makes all these security protocols unsuitable for
resource constrained platforms such as Internet of Things (IoT). Blockchain
(BC) finds its efficient application in IoT platform to preserve the five basic
cryptographic primitives, such as confidentiality, authenticity, integrity,
availability and non-repudiation. Conventional adoption of BC in IoT platform
causes high energy consumption, delay and computational overhead which are not
appropriate for various resource constrained IoT devices. This work proposes a
machine learning (ML) based smart access control framework in a public and a
private BC for a smart city application which makes it more efficient as
compared to the existing IoT applications. The proposed IoT based smart city
architecture adopts BC technology for preserving all the cryptographic security
and privacy issues. Moreover, BC has very minimal overhead on IoT platform as
well. This work investigates the existing threat models and critical access
control issues which handle multiple permissions of various nodes and detects
relevant inconsistencies to notify the corresponding nodes. Comparison in terms
of all security issues with existing literature shows that the proposed
architecture is competitively efficient in terms of security access control.
