  The proliferation of IoT devices in smart homes, hospitals, and enterprise
networks is widespread and continuing to increase in a superlinear manner. With
this unprecedented growth, how can one assess the security of an IoT network
holistically? In this article, we explore two dimensions of security
assessment, using vulnerability information of IoT devices and their underlying
components ($\textit{compositional security scores}$) and SIEM logs captured
from the communications and operations of such devices in a network
($\textit{dynamic activity metrics}$) to propose the notion of an
$\textit{attack circuit}$. These measures are used to evaluate the security of
IoT devices and the overall IoT network, demonstrating the effectiveness of
attack circuits as practical tools for computing security metrics
(exploitability, impact, and risk to confidentiality, integrity, and
availability) of heterogeneous networks. We propose methods for generating
attack circuits with input/output pairs constructed from CVEs using natural
language processing (NLP) and with weights computed using standard security
scoring procedures, as well as efficient optimization methods for evaluating
attack circuits. Our system provides insight into possible attack paths an
adversary may utilize based on their exploitability, impact, or overall risk.
We have performed experiments on IoT networks to demonstrate the efficacy of
the proposed techniques.
