A survey on wireless body area networks: architecture, security challenges and research opportunities.

In the era of communication technologies, wireless healthcare networks enable innovative applications to enhance the quality of patients’ lives, provide useful monitoring tools for caregivers, and allows timely intervention. However, due to the sensitive information within the Wireless Body Area Networks (WBANs), insecure data violates the patients’ privacy and may consequently lead to improper medical diagnosis and/or treatment. Achieving a high level of security and privacy in WBAN involves various challenges due to its resource limitations and critical applications. In this paper, a comprehensive survey of the WBAN technology is provided, with a particular focus on the security and privacy concerns along with their countermeasures, followed by proposed research directions and open issues

Wireless based Smart Parking System using Zigbee

One of main issues of developing big parking space for shopping complexes, office complexes and other types of building that requires large parking space is to notify the visitors of occupied and nonoccupied parking space. Most of the visitors might spending up to 30 to 45 minutes just to find an empty parking space. In most recent technology, some parking lot system offered a system that could automatically count when the car entering the empty car space and blocking an infrared signal thus notify the system to count for it. However, this type of sensors actually has an increase of budgeting in order to install and to be maintained. In this project, we have developed a unique solution by providing cost effective solution by using Zigbee technology in parking lot system technology. Instead of using and maintain cable that need to be installed at the ceiling of the parking lot, we developed a system that use wireless technology of Zigbee and it could notify the visitors of empty and non-empty parking lot

Authenticated encryption of pmu data

This paper presents the implementation of anencryption board in order to provide confidentiality, authenticity and integrity of data collected at any point in a power grid, as a potential solution to the Smart Grid cyber security issues. This board consists of a Freescale microcontroller which enables the connection between a PMU (Phasor Measurement Unit) and a ZigBee transmitter. Encryption is done using the SHA256, HMAC-SHA256, KDF-SHA256 and AES256-CBC algorithms. This architecture makes reading and transmission of voltage and currentphasors, energy consumption, frequency, power, power factor and power outages measurements and sendsthis information in real time to a data concentrator where display and subsequent storage are possible. This paper presents the implementation of anencryption board in order to provide confidentiality, authenticity and integrity of data collected at any point in a power grid, as a potential solution to the Smart Grid cyber security issues. This board consists of a Freescale microcontroller which enables the connection between a PMU (Phasor Measurement Unit) and a ZigBee transmitter. Encryption is done using the SHA256, HMAC-SHA256, KDF-SHA256 and AES256-CBC algorithms. This architecture makes reading and transmission of voltage and currentphasors, energy consumption, frequency, power, power factor and power outages measurements and sendsthis information in real time to a data concentrator where display and subsequent storage are possible.

Implantable Medical Devices; Networking Security Survey

Abstract The industry of implantable medical devices (IMDs) is constantly evolving, which is dictated by the pressing need to comprehensively address new challenges in the healthcare field. Accordingly, IMDs are becoming more and more sophisticated. Not long ago, the range of IMDs' technical capacities was expanded, making it possible to establish Internet connection in case of necessity and/or emergency situation for the patient. At the same time, while the web connectivity of today's implantable devices is rather advanced, the issue of equipping the IMDs with sufficiently strong security system remains unresolved. In fact, IMDs have relatively weak security mechanisms which render them vulnerable to cyber-attacks that compromise the quality of IMDs' functionalities. This study revolves around the security deficiencies inherent to three types of sensor-based medical devices; biosensors, insulin pump systems and implantable cardioverter defibrillators. Manufacturers of these devices should take into consideration that security and effectiveness of the functionality of implants is highly dependent on the design. In this paper, we present a comprehensive study of IMDs' architecture and specifically investigate their vulnerabilities at networking interface

A reliable trust-aware reinforcement learning based routing protocol for wireless medical sensor networks.

Interest in the Wireless Medical Sensor Network (WMSN) is rapidly gaining attention thanks to recent advances in semiconductors and wireless communication. However, by virtue of the sensitive medical applications and the stringent resource constraints, there is a need to develop a routing protocol to fulfill WMSN requirements in terms of delivery reliability, attack resiliency, computational overhead and energy efficiency. This doctoral research therefore aims to advance the state of the art in routing by proposing a lightweight, reliable routing protocol for WMSN. Ensuring a reliable path between the source and the destination requires making trustaware routing decisions to avoid untrustworthy paths. A lightweight and effective Trust Management System (TMS) has been developed to evaluate the trust relationship between the sensor nodes with a view to differentiating between trustworthy nodes and untrustworthy ones. Moreover, a resource-conservative Reinforcement Learning (RL) model has been proposed to reduce the computational overhead, along with two updating methods to speed up the algorithm convergence. The reward function is re-defined as a punishment, combining the proposed trust management system to defend against well-known dropping attacks. Furthermore, with a view to addressing the inborn overestimation problem in Q-learning-based routing protocols, we adopted double Q-learning to overcome the positive bias of using a single estimator. An energy model is integrated with the reward function to enhance the network lifetime and balance energy consumption across the network. The proposed energy model uses only local information to avoid the resource burdens and the security concerns of exchanging energy information. Finally, a realistic trust management testbed has been developed to overcome the limitations of using numerical analysis to evaluate proposed trust management schemes, particularly in the context of WMSN. The proposed testbed has been developed as an additional module to the NS-3 simulator to fulfill usability, generalisability, flexibility, scalability and high-performance requirements

Attacks On Near Field Communication Devices

For some years, Near Field Communication (NFC) has been a popularly known technology characterized by its short-distance wireless communication, mainly used in providing different agreeable services such as payment with mobile phones in stores, Electronic Identification, Transportation Electronic Ticketing, Patient Monitoring, and Healthcare. The ability to quickly connect devices offers a level of secure communication. That notwithstanding, looking deeply at NFC and its security level, identifying threats leading to attacks that can alter the user’s confidentiality and data privacy becomes obvious. This paper summarizes some of these attacks, emphasizing four main attack vectors, bringing out a taxonomy of these attack vectors on NFC, and presenting security issues alongside privacy threats within the application environment

Security and Privacy in Smart Grid

Smart grid utilizes different communication technologies to enhance the reliability and efficiency of the power grid; it allows bi-directional flow of electricity and information, about grid status and customers requirements, among different parties in the grid, i.e., connect generation, distribution, transmission, and consumption subsystems together. Thus, smart grid reduces the power losses and increases the efficiency of electricity generation and distribution. Although smart grid improves the quality of grid's services, it exposes the grid to the cyber security threats that communication networks suffer from in addition to other novel threats because of power grid's nature. For instance, the electricity consumption messages sent from consumers to the utility company via wireless network may be captured, modified, or replayed by adversaries. As a consequent, security and privacy concerns are significant challenges in smart grid. Smart grid upgrade creates three main communication architectures: The first one is the communication between electricity customers and utility companies via various networks; i.e., home area networks (HANs), building area networks (BANs), and neighbour area networks (NANs), we refer to these networks as customer-side networks in our thesis. The second architecture is the communication between EVs and grid to charge/discharge their batteries via vehicle-to-grid (V2G) connection. The last network is the grid's connection with measurements units that spread all over the grid to monitor its status and send periodic reports to the main control center (CC) for state estimation and bad data detection purposes. This thesis addresses the security concerns for the three communication architectures. For customer-side networks, the privacy of consumers is the central concern for these networks; also, the transmitted messages integrity and confidentiality should be guaranteed. While the main security concerns for V2G networks are the privacy of vehicle's owners besides the authenticity of participated parties. In the grid's connection with measurements units, integrity attacks, such as false data injection (FDI) attacks, target the measurements' integrity and consequently mislead the main CC to make the wrong decisions for the grid. The thesis presents two solutions for the security problems in the first architecture; i.e., the customer-side networks. The first proposed solution is security and privacy-preserving scheme in BAN, which is a cluster of HANs. The proposed scheme is based on forecasting the future electricity demand for the whole BAN cluster. Thus, BAN connects to the electricity provider only if the total demand of the cluster is changed. The proposed scheme employs the lattice-based public key NTRU crypto-system to guarantee the confidentiality and authenticity of the exchanged messages and to further reduce the computation and communication load. The security analysis shows that our proposed scheme can achieve the privacy and security requirements. In addition, it efficiently reduces the communication and computation overhead. According to the second solution, it is lightweight privacy-preserving aggregation scheme that permits the smart household appliances to aggregate their readings without involving the connected smart meter. The scheme deploys a lightweight lattice-based homomorphic crypto-system that depends on simple addition and multiplication operations. Therefore, the proposed scheme guarantees the customers' privacy and message integrity with lightweight overhead. In addition, the thesis proposes lightweight secure and privacy-preserving V2G connection scheme, in which the power grid assures the confidentiality and integrity of exchanged information during (dis)charging electricity sessions and overcomes EVs' authentication problem. The proposed scheme guarantees the financial profits of the grid and prevents EVs from acting maliciously. Meanwhile, EVs preserve their private information by generating their own pseudonym identities. In addition, the scheme keeps the accountability for the electricity-exchange trade. Furthermore, the proposed scheme provides these security requirements by lightweight overhead; as it diminishes the number of exchanged messages during (dis)charging sessions. Simulation results demonstrate that the proposed scheme significantly reduces the total communication and computation load for V2G connection especially for EVs. FDI attack, which is one of the severe attacks that threatens the smart grid's efficiency and reliability, inserts fake measurements among the correct ones to mislead CC to make wrong decisions and consequently impact on the grid's performance. In the thesis, we have proposed an FDI attack prevention technique that protects the integrity and availability of the measurements at measurement units and during their transmission to the CC, even with the existence of compromised units. The proposed scheme alleviates the negative impacts of FDI attack on grid's performance. Security analysis and performance evaluation show that our scheme guarantees the integrity and availability of the measurements with lightweight overhead, especially on the restricted-capabilities measurement units. The proposed schemes are promising solutions for the security and privacy problems of the three main communication networks in smart grid. The novelty of these proposed schemes does not only because they are robust and efficient security solutions, but also due to their lightweight communication and computation overhead, which qualify them to be applicable on limited-capability devices in the grid. So, this work is considered important progress toward more reliable and authentic smart grid

Efficient Cryptographic Algorithms and Protocols for Mobile Ad Hoc Networks

As the next evolutionary step in digital communication systems, mobile ad hoc networks (MANETs) and their specialization like wireless sensor networks (WSNs) have been attracting much interest in both research and industry communities. In MANETs, network nodes can come together and form a network without depending on any pre-existing infrastructure and human intervention. Unfortunately, the salient characteristics of MANETs, in particular the absence of infrastructure and the constrained resources of mobile devices, present enormous challenges when designing security mechanisms in this environment. Without necessary measures, wireless communications are easy to be intercepted and activities of users can be easily traced. This thesis presents our solutions for two important aspects of securing MANETs, namely efficient key management protocols and fast implementations of cryptographic primitives on constrained devices. Due to the tight cost and constrained resources of high-volume mobile devices used in MANETs, it is desirable to employ lightweight and specialized cryptographic primitives for many security applications. Motivated by the design of the well-known Enigma machine, we present a novel ultra-lightweight cryptographic algorithm, referred to as Hummingbird, for resource-constrained devices. Hummingbird can provide the designed security with small block size and is resistant to the most common attacks such as linear and differential cryptanalysis. Furthermore, we also present efficient software implementations of Hummingbird on 4-, 8- and 16-bit microcontrollers from Atmel and Texas Instruments as well as efficient hardware implementations on the low-cost field programmable gate arrays (FPGAs) from Xilinx, respectively. Our experimental results show that after a system initialization phase Hummingbird can achieve up to 147 and 4.7 times faster throughput for a size-optimized and a speed-optimized software implementation, respectively, when compared to the state-of-the-art ultra-lightweight block cipher PRESENT on the similar platforms. In addition, the speed optimized Hummingbird encryption core can achieve a throughput of 160.4 Mbps and the area optimized encryption core only occupies 253 slices on a Spartan-3 XC3S200 FPGA device. Bilinear pairings on the Jacobians of (hyper-)elliptic curves have received considerable attention as a building block for constructing cryptographic schemes in MANETs with new and novel properties. Motivated by the work of Scott, we investigate how to use efficiently computable automorphisms to speed up pairing computations on two families of non-supersingular genus 2 hyperelliptic curves over prime fields. Our findings lead to new variants of Miller's algorithm in which the length of the main loop can be up to 4 times shorter than that of the original Miller's algorithm in the best case. We also generalize Chatterjee et al.'s idea of encapsulating the computation of the line function with the group operations to genus 2 hyperelliptic curves, and derive new explicit formulae for the group operations in projective and new coordinates in the context of pairing computations. Efficient software implementation of computing the Tate pairing on both a supersingular and a non-supersingular genus 2 curve with the same embedding degree of k = 4 is investigated. Combining the new algorithm with known optimization techniques, we show that pairing computations on non-supersingular genus 2 curves over prime fields use up to 55.8% fewer field operations and run about 10% faster than supersingular genus 2 curves for the same security level. As an important part of a key management mechanism, efficient key revocation protocol, which revokes the cryptographic keys of malicious nodes and isolates them from the network, is crucial for the security and robustness of MANETs. We propose a novel self-organized key revocation scheme for MANETs based on the Dirichlet multinomial model and identity-based cryptography. Firmly rooted in statistics, our key revocation scheme provides a theoretically sound basis for nodes analyzing and predicting peers' behavior based on their own observations and other nodes' reports. Considering the difference of malicious behaviors, we proposed to classify the nodes' behavior into three categories, namely good behavior, suspicious behavior and malicious behavior. Each node in the network keeps track of three categories of behavior and updates its knowledge about other nodes' behavior with 3-dimension Dirichlet distribution. Based on its own analysis, each node is able to protect itself from malicious attacks by either revoking the keys of the nodes with malicious behavior or ceasing the communication with the nodes showing suspicious behavior for some time. The attack-resistant properties of the resulting scheme against false accusation attacks launched by independent and collusive adversaries are also analyzed through extensive simulations. In WSNs, broadcast authentication is a crucial security mechanism that allows a multitude of legitimate users to join in and disseminate messages into the networks in a dynamic and authenticated way. During the past few years, several public-key based multi-user broadcast authentication schemes have been proposed in the literature to achieve immediate authentication and to address the security vulnerability intrinsic to μTESLA-like schemes. Unfortunately, the relatively slow signature verification in signature-based broadcast authentication has also incurred a series of problems such as high energy consumption and long verification delay. We propose an efficient technique to accelerate the signature verification in WSNs through the cooperation among sensor nodes. By allowing some sensor nodes to release the intermediate computation results to their neighbors during the signature verification, a large number of sensor nodes can accelerate their signature verification process significantly. When applying our faster signature verification technique to the broadcast authentication in a 4×4 grid-based WSN, a quantitative performance analysis shows that our scheme needs 17.7%~34.5% less energy and runs about 50% faster than the traditional signature verification method

Sensing and Visualizing Social Context from Spatial Proximity

The concept of pervasive computing, as introduced by Marc Weiser under the name ubiquitous computing in the early 90s, spurred research into various kinds of context-aware systems and applications. There is a wide range of contextual parameters, including location, time, temperature, devices and people in proximity, which have been part of the initial ideas about context-aware computing. While locational context is already a well understood concept, social context---based on the people around us---proves to be harder to grasp and to operationalize. This work continues the line of research into social context, which is based on the proximity and meeting patterns of people in the physical space. It takes this research out of the lab and out of well controlled situations into our urban environments, which are full of ambiguity and opportunities. The key to this research is the tool that caused dramatic change in individual and collective behavior during the last 20 years and which is a manifestation of many of the ideas of the pervasive computing paradigm: the mobile phone. In this work, the mobile is regarded as a proxy for people. Through it, the social environment becomes accessible to digital measurement and processing. To understand the large amount of data that now becomes available to automatic measurement, we will turn to the discipline of social network analysis. It provides powerful methods, that are able to condense data and extract relevant meaning. Visualization helps to understand and interpret the results. This thesis contains a number of experiments, that demonstrate how the automatic measurement of social proximity data through Bluetooth can be used to measure variables of personal behavior, group behavior and the behavior of groups in relation to places. The principal contributions are: * A methodology to visualize personal social context by using an ego proximity network. Specific episodes can be localized and compared. * method to compare different days in terms of social context, e.g. to support automatic diary applications. * A method to compose social geographic maps. Locations of similar social context are detected and combined. * Functions to measure short-term changes in social activity, based on the distinction between strange and familiar devices. * The characterization of Bluetooth inquiries for social proximity sensing. * A dataset of Bluetooth sightings from an ego perspective in seven different settings. Additionally, some settings feature multiple stationary scanners and Cell-ID measurements. * Soft- and hardware to capture, collect, store and analyze Bluetooth proximity data

Evolutionary Robot Swarms Under Real-World Constraints

Tese de doutoramento em Engenharia Electrotécnica e de Computadores, na especialidade de Automação e Robótica, apresentada ao Departamento de Engenharia Electrotécnica e de Computadores da Faculdade de Ciências e Tecnologia da Universidade de CoimbraNas últimas décadas, vários cientistas e engenheiros têm vindo a estudar as estratégias provenientes da natureza. Dentro das arquiteturas biológicas, as sociedades que vivem em enxames revelam que agentes simplistas, tais como formigas ou pássaros, são capazes de realizar tarefas complexas usufruindo de mecanismos de cooperação. Estes sistemas abrangem todas as condições necessárias para a sobrevivência, incorporando comportamentos de cooperação, competição e adaptação. Na “batalha” sem fim em prol do progresso dos mecanismos artificiais desenvolvidos pelo homem, a ciência conseguiu simular o primeiro comportamento em enxame no final dos anos oitenta. Desde então, muitas outras áreas, entre as quais a robótica, beneficiaram de mecanismos de tolerância a falhas inerentes da inteligência coletiva de enxames. A área de investigação deste estudo incide na robótica de enxame, consistindo num domínio particular dos sistemas robóticos cooperativos que incorpora os mecanismos de inteligência coletiva de enxames na robótica. Mais especificamente, propõe-se uma solução completa de robótica de enxames a ser aplicada em contexto real. Nesta ótica, as operações de busca e salvamento foram consideradas como o caso de estudo principal devido ao nível de complexidade associado às mesmas. Tais operações ocorrem tipicamente em cenários dinâmicos de elevadas dimensões, com condições adversas que colocam em causa a aplicabilidade dos sistemas robóticos cooperativos. Este estudo centra-se nestes problemas, procurando novos desafios que não podem ser ultrapassados através da simples adaptação da literatura da especialidade em algoritmos de enxame, planeamento, controlo e técnicas de tomada de decisão. As contribuições deste trabalho sustentam-se em torno da extensão do método Particle Swarm Optimization (PSO) aplicado a sistemas robóticos cooperativos, denominado de Robotic Darwinian Particle Swarm Optimization (RDPSO). O RDPSO consiste numa arquitetura robótica de enxame distribuída que beneficia do particionamento dinâmico da população de robôs utilizando mecanismos evolucionários de exclusão social baseados na sobrevivência do mais forte de Darwin. No entanto, apesar de estar assente no caso de estudo do RDPSO, a aplicabilidade dos conceitos aqui propostos não se encontra restrita ao mesmo, visto que todos os algoritmos parametrizáveis de enxame de robôs podem beneficiar de uma abordagem idêntica. Os fundamentos em torno do RDPSO são introduzidos, focando-se na dinâmica dos robôs, nos constrangimentos introduzidos pelos obstáculos e pela comunicação, e nas suas propriedades evolucionárias. Considerando a colocação inicial dos robôs no ambiente como algo fundamental para aplicar sistemas de enxames em aplicações reais, é assim introduzida uma estratégia de colocação de robôs realista. Para tal, a população de robôs é dividida de forma hierárquica, em que são utilizadas plataformas mais robustas para colocar as plataformas de enxame no cenário de forma autónoma. Após a colocação dos robôs no cenário, é apresentada uma estratégia para permitir a criação e manutenção de uma rede de comunicação móvel ad hoc com tolerância a falhas. Esta estratégia não considera somente a distância entre robôs, mas também a qualidade do nível de sinal rádio frequência, redefinindo assim a sua aplicabilidade em cenários reais. Os aspetos anteriormente mencionados estão sujeitos a uma análise detalhada do sistema de comunicação inerente ao algoritmo, para atingir uma implementação mais escalável do RDPSO a cenários de elevada complexidade. Esta elevada complexidade inerente à dinâmica dos cenários motivaram a ultimar o desenvolvimento do RDPSO, integrando para o efeito um mecanismo adaptativo baseado em informação contextual (e.g., nível de atividade do grupo). Face a estas considerações, o presente estudo pode contribuir para expandir o estado-da-arte em robótica de enxame com algoritmos inovadores aplicados em contexto real. Neste sentido, todos os métodos propostos foram extensivamente validados e comparados com alternativas, tanto em simulação como com robôs reais. Para além disso, e dadas as limitações destes (e.g., número limitado de robôs, cenários de dimensões limitadas, constrangimentos reais limitados), este trabalho contribui ainda para um maior aprofundamento do estado-da-arte, onde se propõe um modelo macroscópico capaz de capturar a dinâmica inerente ao RDPSO e, até certo ponto, estimar analiticamente o desempenho coletivo dos robôs perante determinada tarefa. Em suma, esta investigação pode ter aplicabilidade prática ao colmatar a lacuna que se faz sentir no âmbito das estratégias de enxames de robôs em contexto real e, em particular, em cenários de busca e salvamento.Over the past decades, many scientists and engineers have been studying nature’s best and time-tested patterns and strategies. Within the existing biological architectures, swarm societies revealed that relatively unsophisticated agents with limited capabilities, such as ants or birds, were able to cooperatively accomplish complex tasks necessary for their survival. Those simplistic systems embrace all the conditions necessary to survive, thus embodying cooperative, competitive and adaptive behaviours. In the never-ending battle to advance artificial manmade mechanisms, computer scientists simulated the first swarm behaviour designed to mimic the flocking behaviour of birds in the late eighties. Ever since, many other fields, such as robotics, have benefited from the fault-tolerant mechanism inherent to swarm intelligence. The area of research presented in this Ph.D. Thesis focuses on swarm robotics, which is a particular domain of multi-robot systems (MRS) that embodies the mechanisms of swarm intelligence into robotics. More specifically, this Thesis proposes a complete swarm robotic solution that can be applied to real-world missions. Although the proposed methods do not depend on any particular application, search and rescue (SaR) operations were considered as the main case study due to their inherent level of complexity. Such operations often occur in highly dynamic and large scenarios, with harsh and faulty conditions, that pose several problems to MRS applicability. This Thesis focuses on these problems raising new challenges that cannot be handled appropriately by simple adaptation of state-of-the-art swarm algorithms, planning, control and decision-making techniques. The contributions of this Thesis revolve around an extension of the Particle Swarm Optimization (PSO) to MRS, denoted as Robotic Darwinian Particle Swarm Optimization (RDPSO). The RDPSO is a distributed swarm robotic architecture that benefits from the dynamical partitioning of the whole swarm of robots by means of an evolutionary social exclusion mechanism based on Darwin’s survival-of-the-fittest. Nevertheless, although currently applied solely to the RDPSO case study, the applicability of all concepts herein proposed is not restricted to it, since all parameterized swarm robotic algorithms may benefit from a similar approach The RDPSO is then proposed and used to devise the applicability of novel approaches. The fundamentals around the RDPSO are introduced by focusing on robots’ dynamics, obstacle avoidance, communication constraints and its evolutionary properties. Afterwards, taking the initial deployment of robots within the environment as a basis for applying swarm robotics systems into real-world applications, the development of a realistic deployment strategy is proposed. For that end, the population of robots is hierarchically divided, wherein larger support platforms autonomously deploy smaller exploring platforms in the scenario, while considering communication constraints and obstacles. After the deployment, a way of ensuring a fault-tolerant multi-hop mobile ad hoc communication network (MANET) is introduced to explicitly exchange information needed in a collaborative realworld task execution. Such strategy not only considers the maximum communication range between robots, but also the minimum signal quality, thus refining the applicability to real-world context. This is naturally followed by a deep analysis of the RDPSO communication system, describing the dynamics of the communication data packet structure shared between teammates. Such procedure is a first step to achieving a more scalable implementation by optimizing the communication procedure between robots. The highly dynamic characteristics of real-world applications motivated us to ultimate the RDPSO development with an adaptive strategy based on a set of context-based evaluation metrics. This thesis contributes to the state-of-the-art in swarm robotics with novel algorithms for realworld applications. All of the proposed approaches have been extensively validated in benchmarking tasks, in simulation, and with real robots. On top of that, and due to the limitations inherent to those (e.g., number of robots, scenario dimensions, real-world constraints), this Thesis further contributes to the state-of-the-art by proposing a macroscopic model able to capture the RDPSO dynamics and, to some extent, analytically estimate the collective performance of robots under a certain task. It is the author’s expectation that this Ph.D. Thesis may shed some light into bridging the reality gap inherent to the applicability of swarm strategies to real-world scenarios, and in particular to SaR operations.FCT - SFRH/BD /73382/201