16 research outputs found
A Framework for Facilitating Secure Design and Development of IoT Systems
The term Internet of Things (IoT) describes an ever-growing ecosystem of physical objects
or things interconnected with each other and connected to the Internet. IoT devices
consist of a wide range of highly heterogeneous inanimate and animate objects. Thus, a
thing in the context of the IoT can even mean a person with blood pressure or heart rate
monitor implant or a pet with a biochip transponder. IoT devices range from ordinary
household appliances, such as smart light bulbs or smart coffee makers, to sophisticated
tools for industrial automation. IoT is currently leading a revolutionary change in many
industries and, as a result, a lot of industries and organizations are adopting the paradigm
to gain a competitive edge. This allows them to boost operational efficiency and optimize
system performance through real-time data management, which results in an optimized
balance between energy usage and throughput. Another important application area is
the Industrial Internet of Things (IIoT), which is the application of the IoT in industrial
settings. This is also referred to as the Industrial Internet or Industry 4.0, where Cyber-
Physical Systems (CPS) are interconnected using various technologies to achieve wireless
control as well as advanced manufacturing and factory automation. IoT applications
are becoming increasingly prevalent across many application domains, including smart
healthcare, smart cities, smart grids, smart farming, and smart supply chain management.
Similarly, IoT is currently transforming the way people live and work, and hence
the demand for smart consumer products among people is also increasing steadily. Thus,
many big industry giants, as well as startup companies, are competing to dominate the
market with their new IoT products and services, and hence unlocking the business value
of IoT.
Despite its increasing popularity, potential benefits, and proven capabilities, IoT is still in
its infancy and fraught with challenges. The technology is faced with many challenges, including
connectivity issues, compatibility/interoperability between devices and systems,
lack of standardization, management of the huge amounts of data, and lack of tools for
forensic investigations. However, the state of insecurity and privacy concerns in the IoT
are arguably among the key factors restraining the universal adoption of the technology.
Consequently, many recent research studies reveal that there are security and privacy issues
associated with the design and implementation of several IoT devices and Smart Applications
(smart apps). This can be attributed, partly, to the fact that as some IoT device
makers and smart apps development companies (especially the start-ups) reap business
value from the huge IoT market, they tend to neglect the importance of security. As a
result, many IoT devices and smart apps are created with security vulnerabilities, which
have resulted in many IoT related security breaches in recent years.
This thesis is focused on addressing the security and privacy challenges that were briefly
highlighted in the previous paragraph. Given that the Internet is not a secure environ ment even for the traditional computer systems makes IoT systems even less secure due
to the inherent constraints associated with many IoT devices. These constraints, which are
mainly imposed by cost since many IoT edge devices are expected to be inexpensive and
disposable, include limited energy resources, limited computational and storage capabilities,
as well as lossy networks due to the much lower hardware performance compared
to conventional computers. While there are many security and privacy issues in the IoT
today, arguably a root cause of such issues is that many start-up IoT device manufacturers
and smart apps development companies do not adhere to the concept of security by
design. Consequently, some of these companies produce IoT devices and smart apps with
security vulnerabilities.
In recent years, attackers have exploited different security vulnerabilities in IoT infrastructures
which have caused several data breaches and other security and privacy incidents
involving IoT devices and smart apps. These have attracted significant attention
from the research community in both academia and industry, resulting in a surge of proposals
put forward by many researchers. Although research approaches and findings may
vary across different research studies, the consensus is that a fundamental prerequisite for
addressing IoT security and privacy challenges is to build security and privacy protection
into IoT devices and smart apps from the very beginning. To this end, this thesis investigates
how to bake security and privacy into IoT systems from the onset, and as its main
objective, this thesis particularly focuses on providing a solution that can foster the design
and development of secure IoT devices and smart apps, namely the IoT Hardware Platform
Security Advisor (IoT-HarPSecA) framework. The security framework is expected to
provide support to designers and developers in IoT start-up companies during the design
and implementation of IoT systems. IoT-HarPSecA framework is also expected to facilitate
the implementation of security in existing IoT systems.
To accomplish the previously mentioned objective as well as to affirm the aforementioned
assertion, the following step-by-step problem-solving approach is followed. The first step
is an exhaustive survey of different aspects of IoT security and privacy, including security requirements in IoT architecture, security threats in IoT architecture, IoT application domains
and their associated cyber assets, the complexity of IoT vulnerabilities, and some
possible IoT security and privacy countermeasures; and the survey wraps up with a brief
overview of IoT hardware development platforms. The next steps are the identification of
many challenges and issues associated with the IoT, which narrowed down to the abovementioned
fundamental security/privacy issue; followed by a study of different aspects of
security implementation in the IoT. The remaining steps are the framework design thinking
process, framework design and implementation, and finally, framework performance
evaluation.
IoT-HarPSecA offers three functionality features, namely security requirement elicitation security best practice guidelines for secure development, and above all, a feature that recommends
specific Lightweight Cryptographic Algorithms (LWCAs) for both software and
hardware implementations. Accordingly, IoT-HarPSecA is composed of three main components,
namely Security Requirements Elicitation (SRE) component, Security Best Practice
Guidelines (SBPG) component, and Lightweight Cryptographic Algorithms Recommendation
(LWCAR) component, each of them servicing one of the aforementioned features.
The author has implemented a command-line tool in C++ to serve as an interface
between users and the security framework. This thesis presents a detailed description,
design, and implementation of the SRE, SBPG, and LWCAR components of the security
framework. It also presents real-world practical scenarios that show how IoT-HarPSecA
can be used to elicit security requirements, generate security best practices, and recommend
appropriate LWCAs based on user inputs. Furthermore, the thesis presents performance
evaluation of the SRE, SBPG, and LWCAR components framework tools, which
shows that IoT-HarPSecA can serve as a roadmap for secure IoT development.O termo Internet das coisas (IoT) é utilizado para descrever um ecossistema, em expansão,
de objetos físicos ou elementos interconetados entre si e à Internet. Os dispositivos
IoT consistem numa gama vasta e heterogénea de objetos animados ou inanimados e,
neste contexto, podem pertencer à IoT um indivíduo com um implante que monitoriza a
frequência cardíaca ou até mesmo um animal de estimação que tenha um biochip. Estes
dispositivos variam entre eletrodomésticos, tais como máquinas de café ou lâmpadas inteligentes,
a ferramentas sofisticadas de uso na automatização industrial. A IoT está a
revolucionar e a provocar mudanças em várias indústrias e muitas adotam esta tecnologia
para incrementar as suas vantagens competitivas. Este paradigma melhora a eficiência
operacional e otimiza o desempenho de sistemas através da gestão de dados em tempo
real, resultando num balanço otimizado entre o uso energético e a taxa de transferência.
Outra área de aplicação é a IoT Industrial (IIoT) ou internet industrial ou Indústria 4.0,
ou seja, uma aplicação de IoT no âmbito industrial, onde os sistemas ciberfísicos estão interconectados
a diversas tecnologias de forma a obter um controlo de rede sem fios, bem
como fabricações avançadas e automatização fabril. As aplicações da IoT estão a crescer
e a tornarem-se predominantes em muitos domínios de aplicação inteligentes como sistemas
de saúde, cidades, redes, agricultura e sistemas de fornecimento. Da mesma forma,
a IoT está a transformar estilos de vida e de trabalho e assim, a procura por produtos inteligentes
está constantemente a aumentar. As grandes indústrias e startups competem
entre si de forma a dominar o mercado com os seus novos serviços e produtos IoT, desbloqueando
o valor de negócio da IoT.
Apesar da sua crescente popularidade, benefícios e capacidades comprovadas, a IoT está
ainda a dar os seus primeiros passos e é confrontada com muitos desafios. Entre eles,
problemas de conectividade, compatibilidade/interoperabilidade entre dispositivos e sistemas,
falta de padronização, gestão das enormes quantidades de dados e ainda falta de
ferramentas para investigações forenses. No entanto, preocupações quanto ao estado de
segurança e privacidade ainda estão entre os fatores adversos à adesão universal desta
tecnologia. Estudos recentes revelaram que existem questões de segurança e privacidade
associadas ao design e implementação de vários dispositivos IoT e aplicações inteligentes
(smart apps.), isto pode ser devido ao facto, em parte, de que alguns fabricantes e empresas
de desenvolvimento de dispositivos (especialmente startups) IoT e smart apps., recolham
o valor de negócio dos grandes mercados IoT, negligenciando assim a importância
da segurança, resultando em dispositivos IoT e smart apps. com carências e violações de
segurança da IoT nos últimos anos.
Esta tese aborda os desafios de segurança e privacidade que foram supra mencionados.
Visto que a Internet e os sistemas informáticos tradicionais são por vezes considerados inseguros,
os sistemas IoT tornam-se ainda mais inseguros, devido a restrições inerentes a tais dispositivos. Estas restrições são impostas devido ao custo, uma vez que se espera que
muitos dispositivos de ponta sejam de baixo custo e descartáveis, com recursos energéticos
limitados, bem como limitações na capacidade de armazenamento e computacionais,
e redes com perdas devido a um desempenho de hardware de qualidade inferior, quando
comparados com computadores convencionais. Uma das raízes do problema é o facto
de que muitos fabricantes, startups e empresas de desenvolvimento destes dispositivos e
smart apps não adiram ao conceito de segurança por construção, ou seja, logo na conceção,
não preveem a proteção da privacidade e segurança. Assim, alguns dos produtos e
dispositivos produzidos apresentam vulnerabilidades na segurança.
Nos últimos anos, hackers maliciosos têm explorado diferentes vulnerabilidades de segurança
nas infraestruturas da IoT, causando violações de dados e outros incidentes de
privacidade envolvendo dispositivos IoT e smart apps. Estes têm atraído uma atenção significativa
por parte das comunidades académica e industrial, que culminaram num grande
número de propostas apresentadas por investigadores científicos. Ainda que as abordagens
de pesquisa e os resultados variem entre os diferentes estudos, há um consenso e
pré-requisito fundamental para enfrentar os desafios de privacidade e segurança da IoT,
que buscam construir proteção de segurança e privacidade em dispositivos IoT e smart
apps. desde o fabrico. Para esta finalidade, esta tese investiga como produzir segurança
e privacidade destes sistemas desde a produção, e como principal objetivo, concentra-se
em fornecer soluções que possam promover a conceção e o desenvolvimento de dispositivos
IoT e smart apps., nomeadamente um conjunto de ferramentas chamado Consultor
de Segurança da Plataforma de Hardware da IoT (IoT-HarPSecA). Espera-se que o conjunto
de ferramentas forneça apoio a designers e programadores em startups durante a
conceção e implementação destes sistemas ou que facilite a integração de mecanismos de
segurança nos sistemas préexistentes.
De modo a alcançar o objetivo proposto, recorre-se à seguinte abordagem. A primeira fase
consiste num levantamento exaustivo de diferentes aspetos da segurança e privacidade na
IoT, incluindo requisitos de segurança na arquitetura da IoT e ameaças à sua segurança,
os seus domínios de aplicação e os ativos cibernéticos associados, a complexidade das
vulnerabilidades da IoT e ainda possíveis contramedidas relacionadas com a segurança e
privacidade. Evolui-se para uma breve visão geral das plataformas de desenvolvimento
de hardware da IoT. As fases seguintes consistem na identificação dos desafios e questões
associadas à IoT, que foram restringidos às questões de segurança e privacidade. As demais
etapas abordam o processo de pensamento de conceção (design thinking), design e
implementação e, finalmente, a avaliação do desempenho.
O IoT-HarPSecA é composto por três componentes principais: a Obtenção de Requisitos
de Segurança (SRE), Orientações de Melhores Práticas de Segurança (SBPG) e a recomendação
de Componentes de Algoritmos Criptográficos Leves (LWCAR) na implementação de software e hardware. O autor implementou uma ferramenta em linha de comandos
usando linguagem C++ que serve como interface entre os utilizadores e a IoT-HarPSecA.
Esta tese apresenta ainda uma descrição detalhada, desenho e implementação das componentes
SRE, SBPG, e LWCAR. Apresenta ainda cenários práticos do mundo real que
demostram como o IoT-HarPSecA pode ser utilizado para elicitar requisitos de segurança,
gerar boas práticas de segurança (em termos de recomendações de implementação) e recomendar
algoritmos criptográficos leves apropriados com base no contributo dos utilizadores.
De igual forma, apresenta-se a avaliação do desempenho destes três componentes,
demonstrando que o IoT-HarPSecA pode servir como um roteiro para o desenvolvimento
seguro da IoT
1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface
A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Remote Sensing
This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas
Book of short Abstracts of the 11th International Symposium on Digital Earth
The Booklet is a collection of accepted short abstracts of the ISDE11 Symposium
Bioinspired metaheuristic algorithms for global optimization
This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions
Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter
In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF
Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm
Abstract— Online transportation has become a basic
requirement of the general public in support of all activities to go
to work, school or vacation to the sights. Public transportation
services compete to provide the best service so that consumers
feel comfortable using the services offered, so that all activities
are noticed, one of them is the search for the shortest route in
picking the buyer or delivering to the destination. Node
Combination method can minimize memory usage and this
methode is more optimal when compared to A* and Ant Colony
in the shortest route search like Dijkstra algorithm, but can’t
store the history node that has been passed. Therefore, using
node combination algorithm is very good in searching the
shortest distance is not the shortest route. This paper is
structured to modify the node combination algorithm to solve the
problem of finding the shortest route at the dynamic location
obtained from the transport fleet by displaying the nodes that
have the shortest distance and will be implemented in the
geographic information system in the form of map to facilitate
the use of the system.
Keywords— Shortest Path, Algorithm Dijkstra, Node
Combination, Dynamic Location (key words