324 research outputs found
Mist and Edge Computing Cyber-Physical Human-Centered Systems for Industry 5.0: A Cost-Effective IoT Thermal Imaging Safety System
While many companies worldwide are still striving to adjust to Industry 4.0
principles, the transition to Industry 5.0 is already underway. Under such a
paradigm, Cyber-Physical Human-centered Systems (CPHSs) have emerged to
leverage operator capabilities in order to meet the goals of complex
manufacturing systems towards human-centricity, resilience and sustainability.
This article first describes the essential concepts for the development of
Industry 5.0 CPHSs and then analyzes the latest CPHSs, identifying their main
design requirements and key implementation components. Moreover, the major
challenges for the development of such CPHSs are outlined. Next, to illustrate
the previously described concepts, a real-world Industry 5.0 CPHS is presented.
Such a CPHS enables increased operator safety and operation tracking in
manufacturing processes that rely on collaborative robots and heavy machinery.
Specifically, the proposed use case consists of a workshop where a smarter use
of resources is required, and human proximity detection determines when
machinery should be working or not in order to avoid incidents or accidents
involving such machinery. The proposed CPHS makes use of a hybrid edge
computing architecture with smart mist computing nodes that processes thermal
images and reacts to prevent industrial safety issues. The performed
experiments show that, in the selected real-world scenario, the developed CPHS
algorithms are able to detect human presence with low-power devices (with a
Raspberry Pi 3B) in a fast and accurate way (in less than 10 ms with a 97.04%
accuracy), thus being an effective solution that can be integrated into many
Industry 5.0 applications. Finally, this article provides specific guidelines
that will help future developers and managers to overcome the challenges that
will arise when deploying the next generation of CPHSs for smart and
sustainable manufacturing.Comment: 32 page
Intelligent Transportation Systems: Fusing Computer Vision and Sensor Networks for Traffic Management
Intelligent Transportation Systems (ITS) represent a pivotal approach to addressing the complex challenges posed by modern-day urban mobility. By seamlessly integrating computer vision and sensor networks, ITS offer a comprehensive solution for traffic management, safety enhancement, and environmental sustainability. This paper delves into the synergistic fusion of computer vision and sensor networks within the framework of ITS, emphasizing their collective role in optimizing traffic flow, mitigating congestion, and enhancing overall road safety. Leveraging cutting-edge technologies such as machine learning, image processing, and Internet of Things (IoT), ITS harness real-time data acquisition and analytics capabilities to facilitate informed decision-making by transportation authorities. Through a comprehensive review of recent advancements, challenges, and opportunities, this paper illuminates the transformative potential of integrating computer vision and sensor networks in ITS. Furthermore, it presents compelling case studies and exemplary applications, showcasing the tangible benefits of this fusion across diverse traffic management scenarios. Ultimately, this paper advocates for the widespread adoption of integrated ITS solutions as a means to usher in a new era of smarter, safer, and more sustainable urban transportation systems
Integrity and Privacy Protection for Cyber-physical Systems (CPS)
The present-day interoperable and interconnected cyber-physical systems (CPS) provides significant value in our daily lives with the incorporation of advanced technologies. Still, it also increases the exposure to many security privacy risks like (1) maliciously manipulating the CPS data and sensors to compromise the integrity of the system (2) launching internal/external cyber-physical attacks on the central controller dependent CPS systems to cause a single point of failure issues (3) running malicious data and query analytics on the CPS data to identify internal insights and use it for achieving financial incentive. Moreover, (CPS) data privacy protection during sharing, aggregating, and publishing has also become challenging nowadays because most of the existing CPS security and privacy solutions have drawbacks, like (a) lack of a proper vulnerability characterization model to accurately identify where privacy is needed, (b) ignoring data providers privacy preference, (c) using uniform privacy protection which may create inadequate privacy for some provider while overprotecting others.Therefore, to address these issues, the primary purpose of this thesis is to orchestrate the development of a decentralized, p2p connected data privacy preservation model to improve the CPS system's integrity against malicious attacks. In that regard, we adopt blockchain to facilitate a decentralized and highly secured system model for CPS with self-defensive capabilities. This proposed model will mitigate data manipulation attacks from malicious entities by introducing bloom filter-based fast CPS device identity validation and Merkle tree-based fast data verification. Finally, the blockchain consensus will help to keep consistency and eliminate malicious entities from the protection framework. Furthermore, to address the data privacy issues in CPS, we propose a personalized data privacy model by introducing a standard vulnerability profiling library (SVPL) to characterize and quantify the CPS vulnerabilities and identify the necessary privacy requirements. Based on this model, we present our personalized privacy framework (PDP) in which Laplace noise is added based on the individual node's selected privacy preferences. Finally, combining these two proposed methods, we demonstrate that the blockchain-based system model is scalable and fast enough for CPS data's integrity verification. Also, the proposed PDP model can attain better data privacy by eliminating the trade-off between privacy, utility, and risk of losing information
Evaluating Resilience of Cyber-Physical-Social Systems
Nowadays, protecting the network is not the only security concern. Still, in cyber security,
websites and servers are becoming more popular as targets due to the ease with which
they can be accessed when compared to communication networks. Another threat in
cyber physical social systems with human interactions is that they can be attacked and
manipulated not only by technical hacking through networks, but also by manipulating
people and stealing users’ credentials. Therefore, systems should be evaluated beyond cy-
ber security, which means measuring their resilience as a piece of evidence that a system
works properly under cyber-attacks or incidents. In that way, cyber resilience is increas-
ingly discussed and described as the capacity of a system to maintain state awareness for
detecting cyber-attacks. All the tasks for making a system resilient should proactively
maintain a safe level of operational normalcy through rapid system reconfiguration to
detect attacks that would impact system performance. In this work, we broadly studied
a new paradigm of cyber physical social systems and defined a uniform definition of it.
To overcome the complexity of evaluating cyber resilience, especially in these inhomo-
geneous systems, we proposed a framework including applying Attack Tree refinements
and Hierarchical Timed Coloured Petri Nets to model intruder and defender behaviors
and evaluate the impact of each action on the behavior and performance of the system.Hoje em dia, proteger a rede não é a única preocupação de segurança. Ainda assim, na
segurança cibernética, sites e servidores estão se tornando mais populares como alvos
devido à facilidade com que podem ser acessados quando comparados às redes de comu-
nicação. Outra ameaça em sistemas sociais ciberfisicos com interações humanas é que eles
podem ser atacados e manipulados não apenas por hackers técnicos através de redes, mas
também pela manipulação de pessoas e roubo de credenciais de utilizadores. Portanto, os
sistemas devem ser avaliados para além da segurança cibernética, o que significa medir
sua resiliência como uma evidência de que um sistema funciona adequadamente sob
ataques ou incidentes cibernéticos. Dessa forma, a resiliência cibernética é cada vez mais
discutida e descrita como a capacidade de um sistema manter a consciência do estado para
detectar ataques cibernéticos. Todas as tarefas para tornar um sistema resiliente devem
manter proativamente um nível seguro de normalidade operacional por meio da reconfi-
guração rápida do sistema para detectar ataques que afetariam o desempenho do sistema.
Neste trabalho, um novo paradigma de sistemas sociais ciberfisicos é amplamente estu-
dado e uma definição uniforme é proposta. Para superar a complexidade de avaliar a
resiliência cibernética, especialmente nesses sistemas não homogéneos, é proposta uma
estrutura que inclui a aplicação de refinamentos de Árvores de Ataque e Redes de Petri
Coloridas Temporizadas Hierárquicas para modelar comportamentos de invasores e de-
fensores e avaliar o impacto de cada ação no comportamento e desempenho do sistema
Cyber-Physical Systems for Smart Water Networks: A Review
There is a growing demand to equip Smart Water Networks (SWN) with advanced sensing and computation capabilities in order to detect anomalies and apply autonomous event-triggered control. Cyber-Physical Systems (CPSs) have emerged as an important research area capable of intelligently sensing the state of SWN and reacting autonomously in scenarios of unexpected crisis development. Through computational algorithms, CPSs can integrate physical components of SWN, such as sensors and actuators, and provide technological frameworks for data analytics, pertinent decision making, and control. The development of CPSs in SWN requires the collaboration of diverse scientific disciplines such as civil, hydraulics, electronics, environment, computer science, optimization, communication, and control theory. For efficient and successful deployment of CPS in SWN, there is a need for a common methodology in terms of design approaches that can involve various scientific disciplines. This paper reviews the state of the art, challenges, and opportunities for CPSs, that could be explored to design the intelligent sensing, communication, and control capabilities of CPS for SWN. In addition, we look at the challenges and solutions in developing a computational framework from the perspectives of machine learning, optimization, and control theory for SWN.acceptedVersio
Cybersecurity of Industrial Cyber-Physical Systems: A Review
Industrial cyber-physical systems (ICPSs) manage critical infrastructures by
controlling the processes based on the "physics" data gathered by edge sensor
networks. Recent innovations in ubiquitous computing and communication
technologies have prompted the rapid integration of highly interconnected
systems to ICPSs. Hence, the "security by obscurity" principle provided by
air-gapping is no longer followed. As the interconnectivity in ICPSs increases,
so does the attack surface. Industrial vulnerability assessment reports have
shown that a variety of new vulnerabilities have occurred due to this
transition while the most common ones are related to weak boundary protection.
Although there are existing surveys in this context, very little is mentioned
regarding these reports. This paper bridges this gap by defining and reviewing
ICPSs from a cybersecurity perspective. In particular, multi-dimensional
adaptive attack taxonomy is presented and utilized for evaluating real-life
ICPS cyber incidents. We also identify the general shortcomings and highlight
the points that cause a gap in existing literature while defining future
research directions.Comment: 32 pages, 10 figure
Integrated system architecture for decision-making and urban planning in smart cities
Research and development of applications for smart cities are extremely relevant considering the various problems that population growth will bring to large urban centers in the next few years. Although research on cyber-physical systems, cloud computing, embedded devices, sensor and actuator networks, and participatory sensing, among other paradigms, is driving the growth of solutions, there are a lot of challenges that need to be addressed. Based on these observations, in this work, we present an integrated system architecture for decision-making support and urban planning by introducing its building blocks (termed components): sensing/actuation, local processing, communication, cloud platform, and application components. In the sensing/actuation component, we present the major relevant resources for data collection, identification devices, and actuators that can be used in smart city solutions. Sensing/actuation component is followed by the local processing component, which is responsible for processing, decision-making support, and control in local scale. The communication component, as the connection element among all these components, is presented with an emphasis on the open-access metropolitan area network and cellular networks. The cloud platform is the essential component for urban planning and integration with electronic governance legacy systems, and finally, the application component, in which the government administrator and users have access to public management tools, citizen services, and other urban planning resources15
Digital Twins and the Future of their Use Enabling Shift Left and Shift Right Cybersecurity Operations
Digital Twins (DTs), optimize operations and monitor performance in Smart
Critical Systems (SCS) domains like smart grids and manufacturing. DT-based
cybersecurity solutions are in their infancy, lacking a unified strategy to
overcome challenges spanning next three to five decades. These challenges
include reliable data accessibility from Cyber-Physical Systems (CPS),
operating in unpredictable environments. Reliable data sources are pivotal for
intelligent cybersecurity operations aided with underlying modeling
capabilities across the SCS lifecycle, necessitating a DT. To address these
challenges, we propose Security Digital Twins (SDTs) collecting realtime data
from CPS, requiring the Shift Left and Shift Right (SLSR) design paradigm for
SDT to implement both design time and runtime cybersecurity operations.
Incorporating virtual CPS components (VC) in Cloud/Edge, data fusion to SDT
models is enabled with high reliability, providing threat insights and
enhancing cyber resilience. VC-enabled SDT ensures accurate data feeds for
security monitoring for both design and runtime. This design paradigm shift
propagates innovative SDT modeling and analytics for securing future critical
systems. This vision paper outlines intelligent SDT design through innovative
techniques, exploring hybrid intelligence with data-driven and rule-based
semantic SDT models. Various operational use cases are discussed for securing
smart critical systems through underlying modeling and analytics capabilities.Comment: IEEE Submitted Paper: Trust, Privacy and Security in Intelligent
Systems, and Application
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