How to buy time following a flooding incident : intelligent quantification of emergency response measures

Increasing vessel size and complexity creates high uncertainty in flooding situations, and it is challenging for the crew to obtain a complete overview and make fully informed decisions. Time is of the essence, and to optimise decision making and ensure decisions are made on time, we propose adopting the concept of Dynamic Barrier Management through increased use of sensors and analytics. Focus will be placed on emergency responses as their impact on safety has not been quantified in terms of risk reduction to the same extent as for passive design barriers. Based on the idea of increased use of advanced analytics and sensors, particularly flooding sensors, this paper aims to present current research ideas and planned development of a method in which active mitigation measures such as emergency response actions can be quantified in terms of effective risk reduction based on real-time measurements and simulations during an accident, i.e. intelligent quantification of emergency response measures

Delayed-Bang Approach Towards More Sustainable Critical Infrastructure Risk Management

This article describes the Delayed Bang Approach for determining the value of risk management alternatives in critical infrastructure security. The discussion includes (1) the need for sustainable risk management (2) the importance of time valuation in evaluating competing loss prevention and loss reduction alternatives, (3) the convergence of deterministic engineering economics, survivability analysis, and probabilistic analysis, and (4) hypothetical examples of the Delayed-Bang Approach and significance towards more sustainable risk management

Development and demonstration of an on-board mission planner for helicopters

Mission management tasks can be distributed within a planning hierarchy, where each level of the hierarchy addresses a scope of action, and associated time scale or planning horizon, and requirements for plan generation response time. The current work is focused on the far-field planning subproblem, with a scope and planning horizon encompassing the entire mission and with a response time required to be about two minutes. The far-feld planning problem is posed as a constrained optimization problem and algorithms and structural organizations are proposed for the solution. Algorithms are implemented in a developmental environment, and performance is assessed with respect to optimality and feasibility for the intended application and in comparison with alternative algorithms. This is done for the three major components of far-field planning: goal planning, waypoint path planning, and timeline management. It appears feasible to meet performance requirements on a 10 Mips flyable processor (dedicated to far-field planning) using a heuristically-guided simulated annealing technique for the goal planner, a modified A* search for the waypoint path planner, and a speed scheduling technique developed for this project

Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

Multiple-objective sensor management and optimisation

One of the key challenges associated with exploiting modern Autonomous Vehicle technology for military surveillance tasks is the development of Sensor Management strategies which maximise the performance of the on-board Data-Fusion systems. The focus of this thesis is the development of Sensor Management algorithms which aim to optimise target tracking processes. Three principal theoretical and analytical contributions are presented which are related to the manner in which such problems are formulated and subsequently solved.Firstly, the trade-offs between optimising target tracking and other system-level objectives relating to expected operating lifetime are explored in an autonomous ground sensor scenario. This is achieved by modelling the observer trajectory control design as a probabilistic, information-theoretic, multiple-objective optimisation problem. This novel approach explores the relationships between the changes in sensor-target geometry that are induced by tracking performance measures and those relating to power consumption. This culminates in a novel observer trajectory control algorithm based onthe minimax approach.The second contribution is an analysis of the propagation of error through a limited-lookahead sensor control feedback loop. In the last decade, it has been shown that the use of such non-myopic (multiple-step) planning strategies can lead to superior performance in many Sensor Management scenarios. However, relatively little is known about the performance of strategies which use different horizon lengths. It is shown that, in the general case, planning performance is a function of the length of the horizon over which the optimisation is performed. While increasing the horizon maximises the chances of achieving global optimality, by revealing information about the substructureof the decision space, it also increases the impact of any prediction error, approximations, or unforeseen risk present within the scenario. These competing mechanisms aredemonstrated using an example tracking problem. This provides the motivation for a novel sensor control methodology that employs an adaptive length optimisation horizon. A route to selecting the optimal horizon size is proposed, based on a new non-myopic risk equilibrium which identifies the point where the two competing mechanisms are balanced.The third area of contribution concerns the development of a number of novel optimisation algorithms aimed at solving the resulting sequential decision making problems. These problems are typically solved using stochastic search methods such as Genetic Algorithms or Simulated Annealing. The techniques presented in this thesis are extensions of the recently proposed Repeated Weighted Boosting Search algorithm. In its originalform, it is only applicable to continuous, single-objective, ptimisation problems. The extensions facilitate application to mixed search spaces and Pareto multiple-objective problems. The resulting algorithms have performance comparable with Genetic Algorithm variants, and offer a number of advantages such as ease of implementation and limited tuning requirements

LOGISTICS IN CONTESTED ENVIRONMENTS

This report examines the transport and delivery of logistics in contested environments within the context of great-power competition (GPC). Across the Department of Defense (DOD), it is believed that GPC will strain our current supply lines beyond their capacity to maintain required warfighting capability. Current DOD efforts are underway to determine an appropriate range of platforms, platform quantities, and delivery tactics to meet the projected logistics demand in future conflicts. This report explores the effectiveness of various platforms and delivery methods through analysis in developed survivability, circulation, and network optimization models. Among other factors, platforms are discriminated by their radar cross-section (RCS), noise level, speed, cargo capacity, and self-defense capability. To maximize supply delivered and minimize the cost of losses, the results of this analysis indicate preference for utilization of well-defended convoys on supply routes where bulk supply is appropriate and smaller, and widely dispersed assets on shorter, more contested routes with less demand. Sensitivity analysis on these results indicates system survivability can be improved by applying RCS and noise-reduction measures to logistics assets.Director, Warfare Integration (OPNAV N9I)Major, Israel Defence ForcesCivilian, Singapore Technologies Engineering Ltd, SingaporeCommander, Republic of Singapore NavyCommander, United States NavyCaptain, Singapore ArmyLieutenant, United States NavyLieutenant, United States NavyMajor, Republic of Singapore Air ForceCaptain, United States Marine CorpsLieutenant, United States NavyLieutenant, United States NavyLieutenant, United States NavyLieutenant, United States NavyLieutenant, United States NavyCaptain, Singapore ArmyLieutenant Junior Grade, United States NavyCaptain, Singapore ArmyLieutenant Colonel, Republic of Singapore Air ForceApproved for public release. distribution is unlimite

Privacy, security, and trust issues in smart environments

Recent advances in networking, handheld computing and sensor technologies have driven forward research towards the realisation of Mark Weiser's dream of calm and ubiquitous computing (variously called pervasive computing, ambient computing, active spaces, the disappearing computer or context-aware computing). In turn, this has led to the emergence of smart environments as one significant facet of research in this domain. A smart environment, or space, is a region of the real world that is extensively equipped with sensors, actuators and computing components [1]. In effect the smart space becomes a part of a larger information system: with all actions within the space potentially affecting the underlying computer applications, which may themselves affect the space through the actuators. Such smart environments have tremendous potential within many application areas to improve the utility of a space. Consider the potential offered by a smart environment that prolongs the time an elderly or infirm person can live an independent life or the potential offered by a smart environment that supports vicarious learning

Multi-Attribute Tradespace Exploration for Survivability

Multi-Attribute Tradespace Exploration for Survivability is a system design and analysis methodology that incorporates survivability considerations into the tradespace exploration process (i.e., a solution-generating and decision-making framework that applies decision theory to model-based design). During the concept generation phase of tradespace exploration, the methodology applies seventeen empirically validated survivability design principles spanning susceptibility reduction, vulnerability reduction, and resilience enhancement. During subsequent concept evaluation, the methodology adds value-based survivability metrics to traditional architectural evaluation criteria of mission utility and lifecycle cost. Applied to a satellite radar mission, the methodology allowed operational survivability to be statistically evaluated across representative distributions of naturally occurring disturbances in the space environment and for survivability to be incorporated as a decision factor earlier in the design process. Constellations in the illustrative example are shown to be the most survivable, mitigating disturbances architecturally, rather than through additive features.Massachusetts Institute of Technology (Systems Engineering Advancement Research Initiative (SEAri))Massachusetts Institute of Technology. Program on Emerging Technologie

Integrated helicopter survivability

A high level of survivability is important to protect military personnel and equipment and is central to UK defence policy. Integrated Survivability is the systems engineering methodology to achieve optimum survivability at an affordable cost, enabling a mission to be completed successfully in the face of a hostile environment. “Integrated Helicopter Survivability” is an emerging discipline that is applying this systems engineering approach within the helicopter domain. Philosophically the overall survivability objective is ‘zero attrition’, even though this is unobtainable in practice. The research question was: “How can helicopter survivability be assessed in an integrated way so that the best possible level of survivability can be achieved within the constraints and how will the associated methods support the acquisition process?” The research found that principles from safety management could be applied to the survivability problem, in particular reducing survivability risk to as low as reasonably practicable (ALARP). A survivability assessment process was developed to support this approach and was linked into the military helicopter life cycle. This process positioned the survivability assessment methods and associated input data derivation activities. The system influence diagram method was effective at defining the problem and capturing the wider survivability interactions, including those with the defence lines of development (DLOD). Influence diagrams and Quality Function Deployment (QFD) methods were effective visual tools to elicit stakeholder requirements and improve communication across organisational and domain boundaries. The semi-quantitative nature of the QFD method leads to numbers that are not real. These results are suitable for helping to prioritise requirements early in the helicopter life cycle, but they cannot provide the quantifiable estimate of risk needed to demonstrate ALARP. The probabilistic approach implemented within the Integrated Survivability Assessment Model (ISAM) was developed to provide a quantitative estimate of ‘risk’ to support the approach of reducing survivability risks to ALARP. Limitations in available input data for the rate of encountering threats leads to a probability of survival that is not a real number that can be used to assess actual loss rates. However, the method does support an assessment across platform options, provided that the ‘test environment’ remains consistent throughout the assessment. The survivability assessment process and ISAM have been applied to an acquisition programme, where they have been tested to support the survivability decision making and design process. The survivability ‘test environment’ is an essential element of the survivability assessment process and is required by integrated survivability tools such as ISAM. This test environment, comprising of threatening situations that span the complete spectrum of helicopter operations requires further development. The ‘test environment’ would be used throughout the helicopter life cycle from selection of design concepts through to test and evaluation of delivered solutions. It would be updated as part of the through life capability management (TLCM) process. A framework of survivability analysis tools requires development that can provide probabilistic input data into ISAM and allow derivation of confidence limits. This systems level framework would be capable of informing more detailed survivability design work later in the life cycle and could be enabled through a MATLAB® based approach. Survivability is an emerging system property that influences the whole system capability. There is a need for holistic capability level analysis tools that quantify survivability along with other influencing capabilities such as: mobility (payload / range), lethality, situational awareness, sustainability and other mission capabilities. It is recommended that an investigation of capability level analysis methods across defence should be undertaken to ensure a coherent and compliant approach to systems engineering that adopts best practice from across the domains. Systems dynamics techniques should be considered for further use by Dstl and the wider MOD, particularly within the survivability and operational analysis domains. This would improve understanding of the problem space, promote a more holistic approach and enable a better balance of capability, within which survivability is one essential element. There would be value in considering accidental losses within a more comprehensive ‘survivability’ analysis. This approach would enable a better balance to be struck between safety and survivability risk mitigations and would lead to an improved, more integrated overall design