  With the growth of embedded systems, VLSI design phases complexity and cost
factors across the globe and has become outsourced. Modern computing ICs are
now using system-on-chip for better on-chip processing and communication. In
the era of Internet-of-Things (IoT), security has become one of the most
crucial parts of a System-on-Chip (SoC). Malicious activities generate abnormal
traffic patterns which affect the operation of the system and its performance
which cannot be afforded in a computation hungry world. SoCs have a chance of
functionality failure, leakage of information, even a denial of services (DoS),
Hardware Trojan Horses and many more factors which are categorized as security
threats. In this paper, we aim to compare and describe different types of
malicious security threats and how neural networks can be used to prevent those
attacks. Spiking Neural Networks (SNN), Runtime Neural Architecture (RTNA) are
some of the neural networks which prevent SoCs from attacks. Finally, the
development trends in SoC security are also highlighted.

Cryptography and Security