Blockchain Papers

Gurkan Akalin, Birsen Karpak, Y. İlker Topçu, Emel Aktaş

Purpose The pandemic, disruptions to transportation networks, geopolitical conflicts and trade restrictions over the past five years have intensified attention to supply chain resilience (SCRes) from both academia and industry. At the same time, rapid digitalisation is transforming traditional supply chains. Although numerous studies have examined digital technologies or SCRes independently, limited attention has been given to the reciprocal interrelationships among digital technologies and SCRes dimensions. Given the interconnected nature of digital technologies and the multidimensional characteristics of SCRes, examining these reciprocal interrelationships is essential for capturing their collective influence. Therefore, this study aims to identify the digital technologies that influence SCRes and examine their interrelationships with the dimensions of SCRes, thereby clarifying the relative roles and influence of both digital technologies and SCRes dimensions in strengthening more resilient and sustainable supply chains. Design/methodology/approach We conducted a structured literature review (SLR) and consulted a hybrid panel of seven academic and industry experts to identify the key dimensions of SCRes and the digital technologies influencing them. We then worked with experts to prioritise these factors using the analytic network process (ANP), an extension of the analytic hierarchy process (AHP) that is well-suited to modelling the strong interdependencies and feedback relationships among digital technologies and SCRes dimensions. Data were collected in both 2023 and 2025 from the same experts to capture the changes in expert judgements over time. Findings We found that collaboration and Internet-of-Things (IoT) have exerted the strongest relative influence on SCRes. In particular, collaboration becomes the highest priority factor overall, whereas IoT is the highest priority digital technology within the proposed decision framework. Visibility and velocity follow as the next most influential resilience dimensions, while AI and blockchain, although lower ranked, exhibit increasing relative influence across the two assessment periods. We also argue that no single digital technology on its own is sufficient to achieve supply chain resilience. Successful adoption and implementation require an understanding of how these technologies mutually interact with SCRes dimensions. By explicitly accounting for these interdependencies, the proposed decision framework prioritises both digital technologies and SCRes dimensions according to their relative influence on supply chain resilience, providing practical guidance for organisations seeking to strengthen resilience. Originality/value This study advances the SCRes literature by proposing an integrated ANP-based framework that models the interdependencies and feedback relationships between digital technologies and SCRes dimensions. Unlike prior studies that examine technologies in isolation or treat resilience dimensions as independent constructs, the present study evaluates both the combined and individual influence of digital technologies within a multidimensional resilience framework. The study further contributes by organising the literature around digital technologies and SCRes dimensions, revealing their interplay through expert judgement and providing a temporal comparison of evolving priorities between 2023 and 2025. The findings further demonstrate that SCRes emerges through reciprocal interdependencies between digital technologies and multiple resilience dimensions rather than through isolated technological effects.

Shinde SM

This study proposes a unified framework integrating AI, Blockchain, IoT, Digital Twins, quantum computing, and FKF spectral analysis for sustainable, transparent, and resilient supply chains. AI enables prediction and optimization; Blockchain ensures trusted traceability; IoT provides real-time sensing; Digital Twins support simulation; and quantum annealing addresses complex logistics optimization. FKF analysis captures temporal shifts, modulation, multiscale dynamics, and lead-time variations for AI-based spectral intelligence. The resulting sensing–analysis–intelligence–simulation–optimization architecture provides an adaptive pathway for efficient and resilient next-generation logistics Keywords— Artificial Intelligence; Sustainable Logistics; Green Supply Chain; Blockchain; Digital Twins; Internet of Things; Quantum Computing; Quantum Annealing; FKF Transform; Supply Chain Resilience.

Shinde SM

Supply-chain resilience requires coordinated sensing, intelligence, simulation, trusted data, and optimization. This study proposes an integrated architecture combining IoT, AI, Blockchain, Digital Twins, quantum computing, and FKF spectral analysis. IoT captures operational conditions, AI supports prediction, Blockchain strengthens traceability, and Digital Twins evaluate disruption scenarios. Quantum annealing addresses complex logistics decisions, while FKF analysis identifies temporal, spectral, and multiscale patterns. The proposed convergence provides a compact framework for adaptive, sustainable, and resilient logistics management. Keywords— Artificial Intelligence; Blockchain Integration; Supply Chain Transparency; Traceability; Supply Chain Resilience; Smart Logistics; IoT; Digital Twins; Quantum Optimization; FKF Spectral Analysis.

Dr. V. A. Sharma

The Karhunen–Loève (KL) expansion provides an optimal orthogonal series representation of second-order stochastic processes and random fields. This paper presents a complete mathematical formulation of the KL theory using native Office Math Markup Language (OMML) equations, covering the governing Fredholm integral eigenvalue problem, the expansion and its coefficients, truncation error bounds, and the normalized representation. Building upon this theoretical foundation, we systematically explore practical applications of the KL expansion in contemporary supply-chain research themes: quantum-inspired optimization and uncertainty quantification in logistics networks; construction of resilient and adaptive digital twins for global supply chains; stochastic modelling supporting artificial-intelligence and blockchain integration for transparency, traceability and resilience; and uncertainty-aware modelling in sustainable and green logistics. The KL expansion emerges as a rigorous, computationally tractable tool for dimensionality reduction, random-field generation and risk quantification across these domains, thereby bridging classical stochastic process theory with the emerging requirements of Industry 4.0 and quantum-era logistics systems. Keywords— Karhunen–Loève expansion; stochastic processes; uncertainty quantification; digital twin; supply chain resilience; quantum logistics; green logistics; AI–blockchain integration.

Aleksandr Rozenfeld

Economic Guarantees of Security (EGS), Internal Resistance Series, Working Paper No. 4 Work in Progress —August, 2026 Affiliation: International Institute of Political Philosophy (Kyiv, Ukraine) Author: Prof. Aleksandr Rozenfeld Contact: aleksrozenfeld2021@gmail.com Abstract This paper is part of the research series Internal Economic Resistance within the broader research program Economic Guarantees of Security (EGS). It develops the concept of business economic resistance as an endogenous constraint on military aggression and examines its role within a two-loop model of deterrence. Unlike conventional approaches that regard business primarily as a passive object of wartime mobilization, this study conceptualizes business as a decentralized network of autonomous economic agents possessing independent objectives, assets, contractual obligations, and decision-making authority. The paper argues that the principal source of business resistance lies not merely in expected financial losses but in the anticipated erosion of entrepreneurial freedom, property rights, contractual stability, market access, and institutional predictability. These institutional threats generate rational behavioral responses, including reduced investment, capital flight, production adjustment, contract restructuring, market reallocation, informal economic activity, and business exit. Although these responses rarely take the form of organized political protest, their diffusion through production, financial, contractual, and logistical networks gradually reduces the fiscal, technological, and organizational capacity of the state. The paper introduces the concept of an economic mobilization limit, defined as the point beyond which additional state pressure no longer increases, but instead diminishes, the effective resources available for military mobilization. Particular attention is devoted to the anticipatory nature of business behavior. Economic resistance frequently begins before the outbreak of war, as firms respond to expected sanctions, mobilization measures, regulatory restrictions, and institutional uncertainty. Consequently, well-designed systems of Economic Guarantees of Security can influence expectations at the decision-making stage, activating endogenous economic constraints before military aggression occurs. The proposed framework extends traditional deterrence theory by integrating external economic measures with internally generated behavioral responses of business. It demonstrates how decentralized economic decisions can complement international sanctions and other preventive mechanisms, thereby strengthening both the prevention of aggression and the conditions for its termination. One of the key conclusions of this work is that military aggression can be not only prevented but even stopped not only by external pressure measures but also by the economic behavior of businesses. The work presents and expands on a two-loop deterrence model that links international pressure measures with the internal disobedience of economic agents.

Rahman Mustafizur

This study develops and validates an ecological economics framework integrating green logistics practices to enhance supply chain resilience in Southeast Asia's automotive sector. Using mixed-methods analysis of 272 firms across Thailand, Indonesia, and Malaysia, structural equation modelling confirms three hypotheses: green logistics adoption significantly predicts resilience (β=0.38, p 4.0 thresholds flipping green logistics from cost to profit centre. Findings advance dynamic capabilities theory with biophysical limits, resolve triple bottom line tensions, and deliver managerial roadmaps (rail pilots→FCA training→blockchain Scope 3) plus ASEAN policy blueprints (CBAM harmonisation, $500M capacity fund). The framework positions the ASEAN automotive sector for regenerative leadership, converting natural capital from externality to competitive asset amid global decarbonisation pressures. These findings offer actionable insights for managers, investors, and policymakers seeking to align profitability with ecological resilience in emerging economies.

Sanidhay Arora, Yingjiu Li, Yebo Feng, Jiahua Xu

Decentralized Finance (DeFi) offers open and permissionless financial services, but its core infrastructure remains exposed to serious security failures. Representative infrastructure classes such as decentralized exchanges (DEXs), protocols for loanable funds (PLFs), and cross-chain bridges matter because failures can propagate widely. This work presents a layered and empirically grounded framework for DeFi vulnerability prioritization. We analyze 558 exploit incidents from 2021–2025 and trace their mechanisms, vulnerabilities, and threat vectors across representative DeFi infrastructure classes. We introduce three complementary components: (1) a Risk Priority Number (RPN) used as an interpretable FMEA-style baseline for attack ranking, (2) an Adversarial Feasibility Score (AFS) that captures exploit feasibility from mapped adversarial-trait prevalence and accessibility, and (3) a Vulnerability-Centric Risk Score (VRS) defined as a structured priority ranking combining empirical likelihood, absolute economic severity, and attacker feasibility. The main validated model uses median per-incident USD loss as a consistent severity signal across the full incident dataset. Temporal validation shows that the structured vulnerability-priority model outperforms the multiplicative baseline and improves on the empirical base rank across both temporal holdouts and both future targets. The resulting framework provides an auditable remediation ordering for protocol developers, auditors, and risk managers.

Shan Jiang, Wenxin You, Shichang Xuan, Jiaxing Shen

Decentralized finance (DeFi) has emerged as a transformative paradigm, leveraging programmable blockchains to innovate upon traditional financial services without centralized intermediaries. However, DeFi introduces a unique and highly adversarial security landscape characterized by immutable transactions, complex protocol composability, and transparent execution environments. This survey provides a comprehensive systematization of DeFi security, categorizing vulnerabilities across three distinct layers: technical and code layer, economic and protocol layer, and infrastructure and cross-chain layer. Furthermore, we structure the defense mechanisms according to the protocol lifecycle, including pre-deployment prevention strategies, runtime mitigation techniques, and post-incident response and recovery mechanisms. We also delve into specific phenomena such as maximal extractable value, analyzing its dual role as both a market efficiency tool and a security vector. By synthesizing existing literature and incident reports, this survey establishes a holistic framework for understanding the interplay between code and finance. Finally, we identify critical open challenges and propose future research directions aimed at maturing the discipline of DeFi security and mitigating systemic risks.

Satoshi Kawauchi

This paper proposes a novel framework to resolve nuclear deterrence (MAD) by embedding probabilistic lifetimes and economic constraints into strategic assets. By synchronizing assets with a distributed ledger and enforcing entropy-like decay through taxation and quantum-verified signals, the system drives autonomous disarmament, shifting risk control from political intent to physical and mathematical inevitability.

Vishal Chaudhary

The emergence of coordinated, multi-agent offensive systems in cyberspace—variously manifesting as distributed reconnaissance campaigns, AI-assisted vulnerability discovery pipelines, adaptive lateral movement swarms, and cross-domain settlement attacks—has outpaced the formal theoretical treatment necessary for principled defence. This monograph addresses that gap with five primary contributions. First, we model swarm versus counter- swarm interaction as a two-player partially observable stochastic game (POSG) and derive equilibrium conditions under asymmetric information. A sufficient condition is established, via Fano’s inequality, under which an ambiguity-preserving offensive policy becomes dominant on the induced information set; the general exact-solution problem is shown to be intractable unless P = NEXP, because the POSG family strictly contains finite-horizon decentralised partially observable Markov decision processes as a special case. Second, we introduce a formal taxonomy of five autonomous cyber swarm attack classes—distributed reconnaissance, adaptive lateral movement, threshold-splitting exfiltration, semantic service exhaustion, and cross-domain settlement—each coupled to an exact detection decision problem with a worst- case complexity lower bound, an information-theoretic defender error floor, and a formal evasion condition. Third, we propose AEGIS-MESH (Attested Evidence-Gated Interdiction System for Multi-domain Event-Synchronized HotStuff), a new counter-swarm architecture specified as a process-algebraic state machine family, with Byzantine fault tolerance for committees of n ≥ 3f + 1 replicas and five temporal-logic safety invariants enforcing evidence gating, mandatory human approval for destructive actions, and causal auditability. Fourth, we prove that the swarm attribution problem is NP-complete by reduction from Subgraph Isomorphism and derive a closed-form sensor-density lower bound required to guarantee attribution error at most δ. Fifth, we conduct a parametric numerical analysis of the dominance condition, a systematic capability evaluation of contemporary autonomous defence systems against a proposed reproducibility and external-validity framework, and a formal treatment of three Web3 security problems—bridge validator-threshold compromise, blind signing, and TWAP oracle manipulation—before closing with treaty-grade draft governance language and an auditable definition of meaningful human control.

Kent Douglas Lambert, Tom Bradley, John M. Borky, Steve Simske · 6 authors

This research identifies a set of practical solutions to the uncontrolled growth of malicious cross-industry cybersecurity threats. Given the presence of the behaviors and negative effects of cyber threats, the research seeks to understand the effects of three eco-system-wide strategies for cyber defense: Defense-in-Depth (DiD), Zero-Trust Architectures (ZTA), and secure cryptographic key provisioning. These strategies are developed using the BlockFrame, Inc., Eco-Secure Provisioning™ (ESP™) Framework, blockchain-assisted digital logistics management and governance, and the application of Emergence Theory and Uniformity. The research addresses five specific questions to organize the approach, with practical translations of this research to selected industrial use cases.

Collin Arnold Kabwama, Osorachukwu Maurice Ayozie, Justin Njimgou Zeyeum, Adeniran Oluwatoyosi Awe · 6 authors

As Critical National Infrastructure (CNI) becomes increasingly digitized, traditional reactive security assessments are failing to keep pace with automated threats. This paper proposes an autonomous framework integrating Generative Adversarial Networks (GANs) and Distributed Ledger Technology (DLT) for proactive vulnerability discovery and immutable infrastructure hardening. We utilize a Physics-Aware Wasserstein GAN to synthesize protocol-specific attack vectors that identify "zero-day" weaknesses in Industrial Control Systems (ICS) by exploring the operational state space of protocols like DNP3 and Modbus. Discovered vulnerabilities are committed to an Immutable Knowledge Base (IKB) on a sharded, permissioned blockchain, providing a "Single Source of Truth" for cross-sector threat intelligence. To automate mitigation, Smart Contracts orchestrate infrastructure hardening by validating patches through digital twin simulations before network-wide deployment. Experimental results using HELICS and NS-3 demonstrate that this architecture reduces the Mean Time to Remediate (MTTR) from days to sub-second intervals. Finally, we address long-term security by incorporating Post-Quantum Cryptography (PQC) to protect the ledger against emerging quantum threats.

Ejielo Ogbuefi, Stephen Ehilenomen Aifuwa, Jennifer Olatunde-Thorpe, David Akokodaripon

Resilience in critical infrastructures (CIs) has emerged as a pressing global concern, as societies become increasingly dependent on tightly interconnected systems that support communication, energy, finance, and healthcare. These infrastructures, once considered largely independent, now operate within a convergent ecosystem where disruptions in one domain can propagate rapidly across others, leading to cascading failures with severe societal and economic consequences. Conceptual frameworks addressing resilience in such interdependent systems emphasize the need to move beyond traditional robustness toward adaptive, absorptive, and restorative capacities that account for dynamic risks, systemic vulnerabilities, and emergent behaviors. The convergence of communication technologies with energy, financial, and healthcare services introduces both opportunities and challenges. While digital integration enhances efficiency, situational awareness, and service delivery, it also amplifies exposure to cyber threats, systemic shocks, and supply chain fragilities. For instance, a cyberattack on a power grid can simultaneously disrupt healthcare delivery and financial transactions, while communication failures may impede crisis coordination. To address these risks, resilience frameworks increasingly adopt network-centric, socio-technical, and complex adaptive systems perspectives, highlighting interdependencies and the need for multi-level governance. Key strategies include embedding redundancy and decentralization in communication systems, deploying microgrids and storage in energy infrastructures, integrating distributed ledgers and systemic risk monitoring in finance, and strengthening telemedicine and emergency preparedness in healthcare. At a broader level, resilience planning requires cross-sector interoperability standards, public–private collaboration, and ethical prioritization of vulnerable populations. Emerging tools such as AI-driven predictive analytics and digital twins offer promising avenues for resilience assessment and proactive adaptation. Ultimately, resilience in convergent critical infrastructures demands an integrated, multidisciplinary approach that bridges engineering, policy, and social dimensions. By adopting conceptual frameworks that embrace interdependency, adaptability, and inclusivity, societies can enhance preparedness, mitigate cascading risks, and ensure continuity of vital services under conditions of uncertainty.

Eusebiu Volostiuc

Decentralized Finance (DeFi) protocols face significant security challenges, with over $500 million lost to exploits in 2024. While technical vulnerabilities are well-studied, the security implications of novel governance mechanisms remain underexplored, particularly for protocols using competitive dynamics rather than traditional voting. This thesis presents the first comprehensive security analysis of the Foresight Protocol, a DeFi system that optimizes reserve composition through competitive game-theoretic mechanisms. The research adapts traditional threat modeling for blockchain by extending STRIDE with three DeFispecific categories: Governance Vulnerabilities (G), Parameter Interaction Vulnerabilities (P), and Systemic Risks (SR). The analysis reveals that Foresight’s economic design effectively eliminates traditional attack vectors including flash loans, MEV exploitation, and bank runs through stake requirements and extended evaluation periods. However, critical vulnerabilities emerge from the protocol’s governance complexity. The reliance on decentralized decision-making introduces social and educational requirements that actors could exploit through identity spoofing, economic bribery, or information asymmetries. Additionally, the mathematical sophistication of competition parameters creates opportunities for manipulation disguised as optimization, while distinguishing genuine value from market manipulation remains an inherent challenge. Key findings indicate that while economic incentives can provide robust security, governance mechanisms introduce attack surfaces just as significant as technical vulnerabilities. The extended threat modeling framework offers a reusable methodology for analyzing innovative DeFi protocols. The research demonstrates that next-generation DeFi protocols can achieve security through economic design, but success requires sophisticated community capabilities and ongoing empirical validation. This work emphasizes the importance of threat modeling starting from the design phase to ensure comprehensive security in novel DeFi systems.

Daniil Krizhanovskyi

No abstract is available for this record.

I. R. Solomka, B. B. Liubinskyi, B. O. Peniak

Proof-of-Stake (PoS) blockchains often select committees in direct proportion to stake, which makes security sensitive to large validators and stake concentration. In such settings, a purely stake-based lottery can sometimes produce committees whose adversarial share crosses the safety threshold, even if the global adversarial stake remains below one third. This paper introduces a simple mixed-weight rule that combines stake with a bounded baseline distribution through a single mixing parameter λ. The rule leaves committee size, rewards, and VRF-based sortition unchanged, but pulls weight away from highly concentrated positions. Proved that, whenever the adversary is more concentrated than the baseline, the expected adversarial seats fall linearly in λ, while standard concentration bounds show an exponential drop in committee-capture probability. While the mechanism relies on entity-level attribution (or high-cost identities) to prevent Sybil attacks, experiments on ten production PoS networks indicate that modest mixing (around λ=0.3) reduces expected adversarial seats by about one quarter and tightens worst-case guarantees by orders of magnitude.

Enis Karaarslan, Arzu Özkan, Cemal Dak, Umutcan Korkmaz

The necessity for an efficient resource management system during and postdisaster is underscored by the prevalent coordination and resource management challenges faced by various organizations, including non-governmental organizations (NGOs) and government units. To address these problems, our system proposal introduces NGO-RMSD, a blockchain-based decentralized system designed to enhance collaborative efforts during and after disasters. Utilizing the Quorum framework for its energy efficiency, NGO-RMSD enables seamless transactions and updates across parties, eliminating intermediaries and fostering a trusted environment for resource management. This paper details the development of this decentralized system, incorporating smart contracts for autonomous operation. Decentralized systems provide superior security, transparency, and immutability, making them fundamentally more robust and efficient than centralized systems for managing complex, multi-stakeholder scenarios like dis-aster response. This decentralized model ensures transparency, eliminates intermediaries, and enables all parties to conduct transactions and updates reliably. These contracts effectively assess and prioritize the needs of affected individuals, ensuring timely and accurate resource allocation. A proof of concept has been implemented, demonstrating the practicality and potential impact of NGO-RMSD. Designed in alignment with NGO's field requirements and distributed under a free software license, this system promises to significantly improve coordination for disaster resource management. Possible improvements and future work for a more sustainable system is discussed. Looking forward, we aim to enhance the efficiency and effectiveness of disaster relief efforts by providing assistance to a larger number of affected individuals in a more organized and expeditious manner.

Amjad Mehmood, Gregory Epiphaniou, Carsten Maple, Nikolaos Ersotelos · 5 authors

Cyber threats and vulnerabilities present an increasing risk to the safe and frictionless execution of business operations. Bad actors ("hackers"), including state actors, are increasingly targeting the operational technologies (OTs) and industrial control systems (ICSs) used to protect critical national infrastructure (CNI). Minimisations of cyber risk, attack surfaces, data immutability, and interoperability of IoT are some of the main challenges of today's CNI. Cyber security risk assessment is one of the basic and most important activities to identify and quantify cyber security threats and vulnerabilities. This research presents a novel i-TRACE security-by-design CNI methodology that encompasses CNI key performance indicators (KPIs) and metrics to combat the growing vicarious nature of remote, well-planned, and well-executed cyber-attacks against CNI, as recently exemplified in the current Ukraine conflict (2014-present) on both sides. The proposed methodology offers a hybrid method that specifically identifies the steps required (typically undertaken by those responsible for detecting, deterring, and disrupting cyber attacks on CNI). Furthermore, we present a novel, advanced, and resilient approach that leverages digital twins and distributed ledger technologies for our chosen i-TRACE use cases of energy management and connected sites. The key steps required to achieve the desired level of interoperability and immutability of data are identified, thereby reducing the risk of CNI-specific cyber attacks and minimising the attack vectors and surfaces. Hence, this research aims to provide an extra level of safety for CNI and OT human operatives, i.e., those tasked with and responsible for detecting, deterring, disrupting, and mitigating these cyber-attacks. Our evaluations and comparisons clearly demonstrate that i-TRACE has significant intrinsic advantages compared to existing "state-of-the-art" mechanisms.

Kolawole Ogunsina, Daniel DeLaurentis

Airline disruption management traditionally seeks to address three problem dimensions: aircraft scheduling, crew scheduling, and passenger scheduling, in that order. However, current efforts have, at most, only addressed the first two problem dimensions concurrently and do not account for the propagative effects that uncertain scheduling outcomes in one dimension can have on another dimension. In addition, existing approaches for airline disruption management include human specialists who decide on necessary corrective actions for airline schedule disruptions on the day of operation. However, human specialists are limited in their ability to process copious amounts of information imperative for making robust decisions that simultaneously address all problem dimensions during disruption management. Therefore, there is a need to augment the decision-making capabilities of a human specialist with quantitative and qualitative tools that can rationalize complex interactions amongst all dimensions in airline disruption management, and provide objective insights to the specialists in the airline operations control center. To that effect, we provide a discussion and demonstration of an agnostic and systematic paradigm for enabling expeditious simultaneously-integrated recovery of all problem dimensions during airline disruption management, through an intelligent multi-agent system that employs principles from artificial intelligence and distributed ledger technology. Results indicate that our paradigm for simultaneously-integrated recovery executes in polynomial time and is effective when all the flights in the airline route network are disrupted.

Emanuele Vannucci, Andrea Jonathan Pagano, Francesco Romagnoli

Abstract This work aims to offer a contribution in the analysis and management, from an economic and financial point of view, of the flood risk, and extended to the hydrogeological risk, from the perspective of a public administration. As main responsible actor for containing the phenomenon through the maintenance of the territory, public administration is responsible for the cost of restoring of the services that have been damaged by this type of phenomenon. The assets of which the public administration must ensure the restoration are all public infrastructures (i.e. transportation, energy and water supply system, communication) together with the damage suffered by private property, if these affect services to be guaranteed to the population. In this work, the authors propose possible strategies that a public administration can put in place to deal with flood risk. Three main strategies are analysed: an absolute passivity that provides for the payment of damages as they occur (i.e. business-as-usual scenario), a classic insurance scheme, a resilient and innovative insurance scheme. The economic–financial profiles of these strategies proposed in this work put an emphasis on how the assumption of a time horizon can change the convenience of one strategy compared to the others. This study highlights the key role of the quantification of flood risk mitigation measure from an engineering perspective, and their potential issues to pursue these objectives in connection to the regulatory framework of the public administrations. This synergy is supported by the potential use of Blockchain-based tools. Within the paper is highlighted the key role that such platform IT data management platform could have within risk analysis and management schemes, both as a data collection tool and as certification of the various steps necessary to complete the process.

Vijay Mohan, Chris Berg, Marta Poblet

No abstract is available for this record.

Ross Guttromson, Stephen Verzi, Lon Andrew Dawson, Drew Levin · 10 authors

This project explored coupling modeling and analysis methods from multiple domains to address complex hybrid (cyber and physical) attacks on mission critical infrastructure. Robust methods to integrate these complex systems are necessary to enable large trade-space exploration including dynamic and evolving cyber threats and mitigations. Reinforcement learning employing deep neural networks, as in the AlphaGo Zero solution, was used to identify "best" (or approximately optimal) resilience strategies for operation of a cyber/physical grid model. A prototype platform was developed and the machine learning (ML) algorithm was made to play itself in a game of 'Hurt the Grid'. This proof of concept shows that machine learning optimization can help us understand and control complex, multi-dimensional grid space. A simple, yet high-fidelity model proves that the data have spatial correlation which is necessary for any optimization or control. Our prototype analysis showed that the reinforcement learning successfully improved adversary and defender knowledge to manipulate the grid. When expanded to more representative models, this exact type of machine learning will inform grid operations and defense - supporting mitigation development to defend the grid from complex cyber attacks! This same research can be expanded to similar complex domains.