Smart Home Cyber Insurance Pricing

TL;DR

The paper tackles the lack of principled evaluation of smart home cyber insurance by proposing a four‑step framework to price premiums and deductibles while ensuring insurer profitability and homeowner affordability. It models cyber risk with a vulnerability graph and a Bayesian Attack Graph to capture entry points and attack paths, then simulates per‑line losses ${\sf L}_m$ and total loss ${\sf TL}$ to evaluate premiums under four pricing principles: $\rho_1(X_m)=(1+\theta)E(X_m)$, $\rho_2(X_m)=E(X_m)+\theta\sqrt{Var(X_m)}$, $\rho_3(X_m)=E(X_m)+\theta E(|X_{m1}-X_{m2}|)$, and $\rho_4(X_m)=E(X_m|X_m\ge VaR_\beta)$. Case studies with a 9‑device smart home show that current policies either overcharge deductibles or are unprofitable, while the framework can produce competent policies with smaller deductibles and premiums. The work provides actionable, risk‑based pricing guidance for insurers and highlights practical paths toward a sustainable smart home cyber insurance market, while acknowledging data and validation limitations and suggesting future extensions such as systemic risk and real‑world claim calibration.

Abstract

Our homes are increasingly employing various kinds of Internet of Things (IoT) devices, leading to the notion of smart homes. While this trend brings convenience to our daily life, it also introduces cyber risks. To mitigate such risks, the demand for smart home cyber insurance has been growing rapidly. However, there are no studies on analyzing the competency of smart home cyber insurance policies offered by cyber insurance vendors (i.e., insurers), where `competency' means the insurer is profitable and smart home owners are not overly charged with premiums and/or deductibles. In this paper, we propose a novel framework for pricing smart home cyber insurance, which can be adopted by insurers in practice. Our case studies show, among other things, that insurers are over charging smart home owners in terms of premiums and deductibles.

Figures (2)

• Figure 1: Illustration of a smart home with 9 devices (excluding cloud server).
• Figure 2: Graph-theoretic representation of vulnerabilities and attacks in a smart home. (a) Attack steps represented as arcs. (b) BAG with exploitation probabilities, such as $\Pr(S_7=1)=.9$ and $\Pr(S_5=1|S_7=1)=.01$.