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Operation efficiency in cyber physical system (CPS) has been significantly improved by digitalization of industrial control systems (ICS). However, digitalization exposes ICS to cyber attacks. Of particular concern are cyber attacks that trigger ICS failure. To determine how cyber attacks can trigger failures and thereby improve the resiliency posture of CPS, this study presents the Resiliency Graph (RG) framework that integrates Attack Graphs (AG) and Fault Trees (FT). RG uses AI planning to establish associations between vulnerabilities and system failures thereby enabling operators to evaluate and manage system resiliency. Our deterministic approach represents both system failures and cyber attacks as a structured set of prerequisites and outcomes using a novel AI planning language. AI planning is then used to chain together the causes and the consequences. Empirical evaluations on various ICS network configurations validate the framework’s effectiveness in capturing how cyber attacks trigger failures and the framework’s scalability. 

When a computing device, such as a server, workstation, laptop, tablet, etc. is shipped from one site to another (for example, from a vendor to a customer or from one branch location of an organization to another) it can potentially be subjected to unauthorized firmware modifications. The industry has sought to partially address this issue by focusing on securing the boot process. Secure boot provides attestation methods by a hardware root-of-trust to confirm the integrity of the device’s BIOS/UEFI firmware. However, once a device boots up, it is relatively easy for a malicious adversary to tamper with the firmware. In this paper, we address this problem by preventing a secure boot unless done by an authorized user. We extend a hardware root of trust (HRoT) processor’s ability to perform secure attestation by implementing a new functionality to securely lock and unlock the BIOS/UEFI or the BMC (Baseboard Management Controller) and implementing an authentication mechanism in the HRoT for determining authorized users. This ensures that the secure boot process won’t commence unless authorized appropriately and provides a robust mechanism for securing the device’s firmware during transit. The proposed PIT-Cerberus framework (PIT = Protection In Transit) leverages strong cryptographic techniques and has been implemented within a trusted microcontroller. We have contributed the PIT-Cerberus framework’s libraries to Project Cerberus, an open-source project that offers a security platform for server hardware. 

The adoption of digital technology in industrial control systems (ICS) enables improved control over operation, ease of system diagnostics and reduction in cost of maintenance of cyber physical systems (CPS). However, digital systems expose CPS to cyber-attacks. The problem is grave since these cyber-attacks can lead to cascading failures affecting safety in CPS. Unfortunately, the relationship between safety events and cyber-attacks in ICS is ill-understood and how cyber-attacks can lead to cascading failures affecting safety. Consequently, CPS operators are ill-prepared to handle cyber-attacks on their systems. In this work, we envision adopting Explainable AI to assist CPS oper-ators in analyzing how a cyber-attack can trigger safety events in CPS and then interactively determining potential approaches to mitigate those threats. We outline the design of a formal framework, which is based on the notion of transition systems, and the associated toolsets for this purpose. The transition system is represented as an AI Planning problem and adopts the causal formalism of human reasoning to asssit CPS operators in their analyses. We discuss some of the research challenges that need to be addressed to bring this vision to fruition. 

We have been witnessing an unprecedented increase in the aging population in human history. It is nontrivial to ensure the health and safety of seniors living alone. The prohibitive human labor cost necessitates more sustainable, technology oriented approaches instead of labor-intensive solutions. The raising digital healthcare services (DHS) leveraging the Internet of Medical Things (IoMT), Digital Twins (DT), and advanced fifth-generation and beyond (B5G) wireless communication technology, are widely recognized as promising solutions. By enabling a seamless interwoven of the physical world and cyberspace, Metaverse makes an ideal home for the next generation of DHS. Thanks to characteristics of decentralization, traceability, and unalterability, Blockchain is envisioned to enhance security properties in Metaverse. This paper proposes MetaSafe, a DHS architecture for seniors’ safety monitoring in Metaverse. Based on monitoring data collected by sensors, the activities and status of seniors, who are considered as the physical objects (PO), are mirrored to corresponding logical objects (LO) in a virtual community in the Metaverse, where activity recognition, potential risk prediction, and alert generation are realized. By leveraging Non-Fungible Token (NFT) technology to tokenize identities (POs and LOs) and data streams of the DHS on the blockchain, an NFT-based authentication fabric allows for verifiable ownership and traceable transferability during the data-sharing process. Specifically, an instant alerting system is introduced in this work that leverages a hybrid algorithm combining the singular spectrum analysis (SSA) approach with the long-short-term memory (LSTM) networks. Through an extensive experimental study, MetaSafe is validated as a feasible and promising approach to protect seniors living alone.