As the Industrial Internet of Things (IIoT) becomes more ubiquitous in critical application domains, such as smart water-distribution and transportation systems, providing security and resilience against cyber-attacks grows into an issue of utmost importance. Cyber-attacks against critical infrastructure pose significant threats to public health and safety, and they have proven to be detrimental in recent years. To alleviate the severity of these threats, various security techniques—including redundancy, diversity, and hardening—are available, which strengthen different security aspects of a system. However, no single technique can address the whole spectrum of cyber-attacks that may be launched by a determined and resourceful attacker. In light of this, we consider a multi-pronged approach, which integrates redundancy, diversity, and hardening techniques, for designing secure and resilient IIoT systems. In this context, redundancy means deploying additional components and devices; diversity means using multiple implementation variants of the same component; and hardening means reinforcing individual components. We introduce a framework for quantifying cyber-security risks and optimizing IIoT design by determining security investments in redundancy, diversity, and hardening. We show that finding optimal security investments is an NP-hard problem, and then present an efficient meta-heuristic design algorithm that finds near optimal designs in practice. To demonstrate the applicability of our framework, we present two case studies in water-distribution and transportation systems. Our numerical evaluation shows that integrating redundancy, diversity, and hardening can lead to reduced security risk at the same cost.