Sustainability within the built environment is increasingly important to our global community as it minimizes environmental impact whilst providing economic and social benefits. Governments recognize the importance of sustainability by providing economic incentives and tenants, particularly large enterprises seek facilities that align with their corporate social responsibility objectives. Claiming sustainability outcomes clearly has benefits for facility owners and facility occupants that have sustainability as part of their business objectives but there are also incentives to overstate the value delivered or only measure parts of the facility lifecycle that provide attractive results. Whilst there is a plethora of research on Building Information Management (BIM) systems within the construction industry there has been limited research on BIM in the facilities management \& sustainability fields. The significant contribution with this research is the integration of blockchain for the purposes of transaction assurance with development of a working model spanning BIM and blockchain underpinning phase one of this research. From an industry perspective the contribution of this paper is to articulate a path to integrate a wide range of mature and emerging technologies into solutions that deliver trusted results for government, facility owners, tenants and other directly impacted stakeholders to assess the sustainability impact.

Digitization expansion enables business transactions operating in distributed systems encompassing Internet- and Machine-to-Everything (M2X) economies. Distributed collaboration systems growth comes at a cost of rapidly rising numbers of machines, infrastructure, machine-infrastructure traffic, and consequently a significant augmentation of associated carbon emissions. In order to investigate M2X’s carbon footprint, we design an impact index application layer using blockchain technology of smart contracts to empower a sustainable management of distributed collaboration systems. The impact measurement methodology based on transparent liquid data secures trusted inter-organizational collaborations and supports traceable standardization of sustainability regulation.

Processor design and manufacturing is often done globally, involving multiple companies, some of which can be untrustworthy. This lack of trust leads to the threat of malicious modifications like Hardware Trojans. Hardware Trojans can cause drastic consequences and even endanger human lives. Hence, effective countermeasures against Hardware Trojans are urgently needed. To develop countermeasures, Hardware Trojans and their properties have to be understood well. For this reason, we describe and characterize Hardware Trojans in detail in this paper. We perform a theoretical analysis of Hardware Trojans for processors. Afterwards, we present a new classification of processor constituents, which can be used to derive several triggers and payloads and compare them with previously published Hardware Trojans. This shows in detail possible attack vectors for processors and gaps in existing processor Hardware Trojan landscape. No previous work presents such a detailed investigation of Hardware Trojans for processors. With this work, we intend to improve understanding of Hardware Trojans in processors, supporting the development of new countermeasures and prevention techniques.

Human-Centered Artificial Intelligence (AI) focuses on AI systems prioritizing user empowerment and ethical considerations. We explore the importance of usercentric design principles and ethical guidelines in creating AI technologies that enhance user experiences and align with human values. It emphasizes user empowerment through personalized experiences and explainable AI, fostering trust and user agency. Ethical considerations, including fairness, transparency, accountability, and privacy protection, are addressed to ensure AI systems respect human rights and avoid biases. Effective human AI collaboration is emphasized, promoting shared decision-making and user control. By involving interdisciplinary collaboration, this research contributes to advancing human-centered AI, providing practical recommendations for designing AI systems that enhance user experiences, promote user empowerment, and adhere to ethical standards. It emphasizes the harmonious coexistence between humans and AI, enhancing well-being and autonomy and creating a future where AI technologies benefit humanity. Overall, this research highlights the significance of human-centered AI in creating a positive impact. By centering on users needs and values, AI systems can be designed to empower individuals and enhance their experiences. Ethical considerations are crucial to ensure fairness and transparency. With effective collaboration between humans and AI, we can harness the potential of AI to create a future that aligns with human aspirations and promotes societal well-being.

Boolean network is a popular and well-established modelling framework for gene regulatory networks. The steady-state behaviour of Boolean networks can be described as attractors, which are hypothesised to characterise cellular phenotypes. In this work, we study the target control problem of Boolean networks, which has important applications for cellular reprogramming. More specifically, we want to reduce the total number of attractors of a Boolean network to a single target attractor. Different from existing approaches to solving control problems of Boolean networks with node perturbations, we aim to develop an approach utilising edgetic perturbations. Namely, our objective is to modify the update functions of a Boolean network such that there remains only one attractor. The design of our approach is inspired by Thomas’ first rule, and we primarily focus on the removal of cycles in the interaction graph of a Boolean network. We further use results in the literature to only remove positive cycles which are responsible for the appearance of multiple attractors. We apply our solution to a number of real-life biological networks modelled as Boolean networks, and the experimental results demonstrate its efficacy and efficiency.

Operational technology (OT) systems use hardware and software to monitor and control physical processes, devices, and infrastructure - often critical infrastructures. The convergence of information technology (IT) and OT has significantly heightened the cyber threats in OT systems. Although OT systems share many of the hardware and software components in IT systems, these components often operate under different expectations. In this work, several hardware root-of-trust architectures are surveyed and the attacks each one mitigates are compared. Attacks spanning the design, manufacturing, and deployment life cycle of safety-critical operational technology are considered. The survey examines architectures that provide a hardware root-of-trust as a peripheral component in a larger system, SoC architectures with an integrated hardware root-of-trust, and FPGA-based hardware root-of-trust systems. Each architecture is compared based on the attacks mitigated. The comparison demonstrates that protecting operational technology across its complete life cycle requires multiple solutions working in tandem.

For power grid enterprises in the development of power engineering infrastructure, line equipment operation and inspection and other production and management activities, often due to evidence collection is not timely, lack of effective evidence and other reasons lead to the inability to prove, weak defense of rights, to the legitimate rights and interests of power grid enterprises caused losses. In this context, this paper carries out the technical research on the whole life cycle management scheme of electronic evidence for power grid enterprises safety production, designs the architecture of electronic evidence credible storage and traceability application service system, and realizes the whole life cycle credible management of electronic evidence from collection, curing, transmission, sealing to checking and identification. Enhance the credibility of electronic evidence, access to evidence from the traditional "after the fact evidence" to "before the evidence" mode change, and promote the company s safety production management level.

Original Equipment Manufacturers (OEMs) need to collaborate within and outside their organizations to improve product quality and time to market. However, legacy systems built over decades using different technology stacks make information sharing and maintaining consistency challenging. Distributed ledger technologies (DLTs) can improve efficiency and provide trust, thus helping to achieve a more streamlined and unified collaboration infrastructure. However, most of the work done is theoretical or conceptual and lacks implementation. This paper elaborates on architecture and implementing a proof of concept (POC) of blockchain-based interoperability and data sharing system that allows OEMs to collaborate seamlessly and share information in real-time.

With the popularization of AIoT applications, every endpoint device is facing information security risks. Thus, how to ensure the security of the device becomes essential. Chip security is divided into software security and hardware security, both of which are indispensable and complement each other. Hardware security underpins the entire cybersecurity ecosystem by proving essential primitives, including key provisioning, hardware cryptographic engines, hardware unique key (HUK), and unique identification (UID). This establishes a Hardware Root of Trust (HRoT) with secure storage, secure operation, and a secure environment to provide a trustworthy foundation for chip security. Today s talk starts with how to use a Physical Unclonable Function (PUF) to generate a unique “fingerprint” (static random number) for the chip. Next, we will address using a static random number and dynamic entropy to design a high-performance true random number generator and achieve real anti-tampering HRoT by leveraging static and dynamic entropy. By integrating NISTstandard cryptographic engines, we have created an authentic PUF-based Hardware Root of Trust. The all-in-one integrated solution can handle all the necessary security functions throughout the product life cycle as well as maintaining a secure boundary to achieve the integrity of sensitive information or assets. Finally, as hardware-level protection extends to operating systems and applications, products and services become secure.

Industrial control systems (ICSs) and supervisory control and data acquisition (SCADA) are frequently used and are essential to the operation of vital infrastructure such as oil and gas pipelines, power plants, distribution grids, and airport control towers. However, these systems confront a number of obstacles and risks that can jeopardize their safety and reliability, including communication failures, cyber-attacks, environmental hazards, and human errors. How can ensure that SCADA systems are both effective and secure? The oil and gas industry literature needs to include an analysis of the underpinning design process. Available research fails to offer appropriate direction for a methodical technique or modeling language that enables trust-based study of ICS and SCADA systems. The most pressing challenges include attaining trust by design in ICS and SCADA, as well as methodically implementing trust design into the development process from the beginning of the system s life cycle. This paper presents the design of a modern ICS and SCADA system for the oil and gas industries utilizing model-based systems engineering (MBSE) approaches. ICS and SCADA concepts and definitions are presented, and ICS and SCADA are examined using comprehensive architectural artifacts. By extending the SysML diagrams to trust ICS, SCADA, and UML diagrams, we showcase the usefulness of the MBSE method.

Summary \& ConclusionsResilience, a system property merging the consideration of stochastic and malicious events focusing on mission success, motivates researchers and practitioners to develop methodologies to support holistic assessments. While established risk assessment methods exist for early and advanced analysis of complex systems, the dynamic nature of security is much more challenging for resilience analysis.The scientific contribution of this paper is a methodology called Trust Loss Effects Analysis (TLEA) for the systematic assessment of the risks to the mission emerging from compromised trust of humans who are part of or are interacting with the system. To make this work more understandable and applicable, the TLEA method follows the steps of Failure Mode, Effects \& Criticality Analysis (FMECA) with a difference in the steps related to the identification of security events. There, the TLEA method uses steps from the Spoofing, Tampering, Repudiation, Information disclosure, Denial of Service (DoS), Elevation of privilege (STRIDE) methodology.The TLEA is introduced using a generic example and is then demonstrated using a more realistic use case of a drone-based system on a reconnaissance mission. After the application of the TLEA method, it is possible to identify different risks related to the loss of trust and evaluate their impact on mission success.