A review of cyber threats and defence approaches in emergency management

Emergency planners, first responders and relief workers increasingly rely on computational and communication systems that support all aspects of emergency management, from mitigation and preparedness to response and recovery. Failure of these systems, whether accidental or because of malicious action, can have severe implications for emergency management. Accidental failures have been extensively documented in the past and significant effort has been put into the development and introduction of more resilient technologies. At the same time researchers have been raising concerns about the potential of cyber attacks to cause physical disasters or to maximise the impact of one by intentionally impeding the work of the emergency services. Here, we provide a review of current research on the cyber threats to communication, sensing, information management and vehicular technologies used in emergency management. We emphasise on open issues for research, which are the cyber threats that have the potential to affect emergency management severely and for which solutions have not yet been proposed in the literature

Modeling IoT-Based Solutions Using Human-Centric Wireless Sensor Networks

The Internet of Things (IoT) has inspired solutions that are already available for addressing problems in various application scenarios, such as healthcare, security, emergency support and tourism. However, there is no clear approach to modeling these systems and envisioning their capabilities at the design time. Therefore, the process of designing these systems is ad hoc and its real impact is evaluated once the solution is already implemented, which is risky and expensive. This paper proposes a modeling approach that uses  human-centric wireless sensor networks to specify and evaluate models of IoT-based systems at the time of design, avoiding the need to spend time and effort on early implementations of immature designs. It allows designers to focus on the system design, leaving the implementation decisions for a next phase. The article illustrates the usefulness of this proposal through a running example, showing the design of an IoT-based solution to support the first responses during medium-sized or large urban incidents. The case study used in the proposal evaluation is based on a real train crash. The proposed modeling approach can be used to design IoT-based systems for other application scenarios, e.g., to support security operatives or monitor chronic patients in their homes.Fil: Monares, Álvaro . Universidad de Chile; ChileFil: Ochoa, Sergio F.. Universidad de Chile; ChileFil: Santos, Rodrigo Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; ArgentinaFil: Orozco, Javier Dario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; ArgentinaFil: Meseguer, Roc . Universidad Politecnica de Catalunya; Españ

Anomaly Recognition in Wireless Ad-hoc Network by using Ant Colony Optimization and Deep Learning

As a result of lower initial investment, greater portability, and lower operational expenses, wireless networks are rapidly replacing their wired counterparts. The new technology that is on the rise is the Mobile Ad-Hoc Network (MANET), which operates without a fixed network infrastructure, can change its topology on the fly, and requires no centralised administration to manage its individual nodes. As a result, MANETs must focus on network efficiency and safety. It is crucial in MANET to pay attention to outliers that may affect QoS settings. Nonetheless, despite the numerous studies devoted to anomaly detection in MANET, security breaches and performance difficulties keep coming back. There is an increased need to provide strategies and approaches that help networks be more safe and robust due to the wide variety of security and performance challenges in MANET. This study presents outlier detection strategies for addressing security and performance challenges in MANET, with a special focus on network anomaly identification. The suggested work utilises a dynamic threshold and outlier detection to tackle the security and performance challenges in MANETs, taking into account metrics such as end-to-end delay, jitter, throughput, packet drop, and energy usage

Capacity Based Evacuation with Dynamic Exit Signs

Exit paths in buildings are designed to minimise evacuation time when the building is at full capacity. We present an evacuation support system which does this regardless of the number of evacuees. The core concept is to even-out congestion in the building by diverting evacuees to less-congested paths in order to make maximal usage of all accessible routes throughout the entire evacuation process. The system issues a set of flow-optimal routes using a capacity-constrained routing algorithm which anticipates evolutions in path metrics using the concept of "future capacity reservation". In order to direct evacuees in an intuitive manner whilst implementing the routing algorithm's scheme, we use dynamic exit signs, i.e. whose pointing direction can be controlled. To make this system practical and minimise reliance on sensors during the evacuation, we use an evacuee mobility model and make several assumptions on the characteristics of the evacuee flow. We validate this concept using simulations, and show how the underpinning assumptions may limit the system's performance, especially in low-headcount evacuations

Securing Embedded Systems for Unmanned Aerial Vehicles

This project focuses on securing embedded systems for unmanned aerial vehicles (UAV). Over the past two decades UAVs have evolved from a primarily military tool into one that is used in many commercial and civil applications. As the market for these products increases the need to protect transmitted data becomes more important. UAVs are flying missions that contain crucial data and without the right protection they can be vulnerable to malicious attacks. This project focuses on building a UAV platform and working to protect the data transmitted on it. The platform was able to detect red color and wirelessly transmit the coordinates of the color to a remote laptop. Areas that were focused on for security included the image processing and wireless communications modules

A spatio-temporal modelling and analysis of digital sensor data for underground mine health and safety

A Research Report submitted to the Faculty of Science, University of the Witwatersrand, in partial fulfilment of the requirements of the degree of Master of Science 2017Health and safety of employees within their work environment is critical. In the mining industry and especially in underground mines, monitoring and management of health and safety of employees is particularly important Most underground mines today are not fully mechanized, except for coal mines. The industry thus still relies on and employs human personnel. Monitoring and managing these mines and hence personnel health and safety as they undertake their trade is therefore a necessity. Implementation of technology, especially in digital sensor systems and real-time spatial analysis systems, provides a means by which health and safety risk factors can be monitored and information gathered to facilitate determination of prevailing risks or prediction of such risks. Technology therefore can be used to make better decisions and implement specialized emergency response to avert or reduce the extent of injuries, casualties and damages in an underground mine. This research project looks into determination of prominent risk factors in an underground mine, determination of parameters for modeling of such risk factors and the implementation of ESRI’s ArcGIS platform for the retrieval and analysis of streaming sensor data about this parameter from an underground mine. A proof of concept (POC) system is developed that analyses streaming digital sensor data and determines the status of the underground mine environment. The results from this analysis are displayed in a dashboard application for a control room environment. The results and achievements of this research project, especially from a dashboard system perspective, show the possibilities of an integrated GIS-based solution for real-time data processing and determination of the prevailing conditions in an underground mine. This solution also opens up a wide pool of possibilities through which systems integration and its benefits can be achieved, especially in underground mines and focusing on health and safety, as previously silo systems can be integrated at data levels, enabling data sharing, analysis, predictions and making of informed decisions.MT201

IoT for measurements and measurements for IoT

The thesis is framed in the broad strand of the Internet of Things, providing two parallel paths. On one hand, it deals with the identification of operational scenarios in which the IoT paradigm could be innovative and preferable to pre-existing solutions, discussing in detail a couple of applications. On the other hand, the thesis presents methodologies to assess the performance of technologies and related enabling protocols for IoT systems, focusing mainly on metrics and parameters related to the functioning of the physical layer of the systems