Littérature scientifique sur le sujet « Cyber pilot »

Solutions on both consumer and state levels have become increasingly vulnerable to sophisticated cyberattacks by e.g. malware, phishing, machine learning and artificial intelligence. As the adoption and integration of information technologies are increasing and solutions are developing, the need to invest in cyber-security is at an all-time high. Investment in cybersecurity is a chief priority within the European Union, and project ECHO is a one initiative that put emphasis on devising, elaborating, implementing and enhancing a series of technological solutions (assets) to counteract cyber-attacks. The research problem of this study is what societal impacts do the ECHO assets have as product, as knowledge use, and as benefits to society. The literature review includes theory and practice from academic papers, EU innovation project and professional reports, and some ECHO project workflows. Relevant academic theoretical approaches that provide a basis for this task are: e-skills and training, Organisational Learning (OL), Societal Impact (SI), Societal Impact Assessment (SIA). This is a qualitative pilot study that evaluates the usefulness of employing a Product/ Knowledge/ Benefit Societal Impact framework to assessment of societal impacts. Data collection involved qualitative participatory observation of a co-creative expert hackathon workshop. This pilot study shows that the methodology path, where societal impact of ICT and AI solutions (e.g. the ECHO assets) are examined as these three elements (product, knowledge use, societal benefit). This pilot study serves as a step to validate this path and design and select practical, rigorous and relevant quantitative methodology to further the understanding of both societal impact assessment of cyber, e-, and AI-based solutions and services. To incorporate societal impacts with cyber and e-skills this study recommends developing and refining actual key performance indicators (KPI) to provide a basis for rigorous and relevant qualitative and quantitative questionnaire based inquiry of cyber, e-, and AI-based solutions and services.

This article presents the results of using the “psychometric paradigm” methodology (P. Slovic, B. Fischhoff, S. Lichtenstein and others) to study the perception of cyber risks and compare them to other risks designated as “traditional”. The respondents in an online survey were presented seven cyber risks (from computer games to hacker attacks and viruses) and 65 traditional risks (from natural disasters to nuclear power plants and terrorism), assessed based on 8 characteristics. As a result, computer games were perceived differently compared to other cyber risks: first of all, they do not induce fear. Other cyber risks are concentrated in an area of relatively obscure and moderately frightening risks, but they do not form a separate cluster. Radiation therapy, herbicides and pesticides are the closest to cyber risks in the two-dimensional space of risk perception. The results of this pilot survey may be considered a reflection of the sample used, where the main participants were active Internet users who were able to distinguish between the presented cyber risks.

This thesis work presents project ``Dart'', i.e. the development of an UAV prototype able to perform autonomous navigation using only on-board systems and sensors. The main objective is to achieve positioning and path following with centimetric precision by using only mass market technologies, in order to ascertain the gap between a completely autonomous ultra-high precision drones and commercial products with reasonable costs. To this aim, Dart core has been designed to feature a high precision on-board vision-based positioning system exploiting the following components: a small camera carried by a gimbal, an embedded electronic board, and an open-source computer vision library. The scenery captured by the camera is processed by a custom software which computes the drone position with respect to known markers. This information is then fused with data read from a IMU to estimate the state of the drone. This system, therefore, acts as a virtual sensor that is able to pilot the UAV along a reference trajectory.

AbstractThe currently designed novel educational scenarios with the walking robot BigFoot from a cyberphysical system perspective to pedagogical rehabilitation is described in the paper. The sensor system of the robot is presented, which is being developed further in order to adequately apply it to two newly formulated educational scenarios. The results of a pilot study are discussed.

The cyber-physical system encompasses physics and cyber systems, which are highly interconnected and networked. Considered to be one of the fascinating inventions of today's world, CPS applications include autonomous vehicles, industrial control systems, medical monitoring, automatic pilot avionics, etc. Autonomous or semi-autonomous vehicles, also known as self-driving or driverless vehicles, are automobiles that require less or no human intervention for operating or controlling them. CPS has brought in several advancements in the automobile industry by providing a seamless human interaction with physical and cyber systems, which includes IoT, artificial intelligence, machine learning, etc. Machine learning algorithms play a major role in enhancing autonomous vehicle models. This chapter focuses on the various machine learning algorithms that are used commonly in building robust autonomous vehicles. This chapter also focuses on the evolution of autonomous vehicles and the backed cyber advancements.

The current state of automated digital information in aviation continues to expand rapidly as NextGen ADS-B(In) systems become more common in the form of Electronic Flight Bag (EFB) pad devices brought onto the flight deck. Integrated systems including satellites, aircraft, and air traffic control (ATC) data currently are not effectively encrypted and invite exposure to cyber attacks targeting flight decks and ATC facilities. The NextGen ATC system was not designed from the outset to identify and nullify cyber threats or attempts at disruption, and the safety gap has enlarged. Performance error at digital human-machine interfaces (HMI) has been well documented in aviation and now presents a potentially significant threat where the HMI can be more susceptible to human error from cyber attacks. Examples of HMI errors arising from digital information produced by automated systems are evaluated by the authors using HMI flaws discovered in recent Boeing 737-Max accidents. SHELL computer diagrams for both the digital flight deck and ATC facilities illustrate how the system is now interconnected for potential cyber threats and identifies how human factors consequences compromising HMI safety and operator performance present potential dangers. Aviation Safety and Reporting System (ASRS) data are examined and confirm HMI threats. The authors contrast various HMI errors with cyber attack effects on cognition, situational awareness, and decision making. A focused examination to assess cyber attack effects on cognitive metrics suggests cognitive clarity of operators is confounded when confronted with conflicting or confusing indications at the HMI. Difficulty in successfully identifying a cyber attack and the actions taken as human factors countermeasures are illustrated in the context of the HMI environment. The Human Factors Analysis and Classification System (HFACS) is used to show how cyber attacks could occur and be addressed along with a dual-path solution.Keywords: NextGen, Cyber attack, SHELL, HMI, Cognitive load, HFACS

The advancement of cyber-physical behaviour detection and understanding in context of urban environment safety and security has been developed in the S4AllCities project (S4AllCities, 2020). Specifically, various concepts of fundamental artificial intelligence and reasoning have been successfully developed and will subsequently be tested in situ in S4AllCities pilot sites during the coming year 2022 (Sabeur et al, 2021). The detection of anomalies in TCP and UDP communication-based protocols taking place in context of urban spaces have been investigated. These were also complemented with the detection of unusualness in crowd physical behaviour in the same urban spaces. The aim is to combine both modes (cyber and physical) of detection and behaviour understanding, in order to advance our situation awareness in context of native knowledge and reasoning for efficiently maintaining safety and security across the urban space. Native knowledge concerns the evaluated risks and mitigation measures for response to potential cyber-physical attacks on the urban space. In this study, the deployed machine learning techniques achieved good performances for classifying cyber and physical behaviour under various scenarios of potential attacks. Our future work is to exercise the performance, evaluation and validation of our intelligent algorithms using in situ cyber and physical observation scenarios of the urban spaces of the three S4AllCities pilot sites in Europe.References:S4AllCities (2020). Safe and Secure Smart Spaces for all Cities H2020 project ID number 883522. https://www.s4allcities.eu/project. Sabeur Z., Angelopoulos C.M., Collick L., Chechina N., Cetinkaya D., Bruno A. (2021) Advanced Cyber and Physical Situation Awareness in Urban Smart Spaces. In: Ayaz H., Asgher U., Paletta L. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2021. Lecture Notes in Networks and Systems, vol 259. pp. 428-441. Springer, Cham. https://doi.org/10.1007/978-3-030-80285-1_50

Energy based Cyber-physical systems (CPS) find their greatest popularity in smart grid applications, where a complex computational algorithm imparts “intelligence” to a supervisory control and data acquisition (SCADA) system used for balancing load distributions. In contrast to this static application of CPS technology, research conducted jointly by U.S. Department of Energy’s, National Energy Technology Laboratory (NETL) and Ames Laboratory proposes a new paradigm in which CPS is used as a core technology in energy system development, design, and deployment. The goal is to speed up the development and deployment of advanced concept power plants, reduce the cost and thereby encouraging private and public investment, and substantially reduce the risk of failure. The current technology development paradigm generally starts with models and bench-scale tests, leading to a pilot plant demonstration of the technology before construction of a commercial system. The concept proposed by NETL and Ames incorporates CPS before and during the construction of a pilot plant — arguably the highest risk part of implementing new energy technologies — and then extends the cyber physical infrastructure to the full-scale plant creating a fully functional and coupled digital twin. The creation of a cyber-physical platform as a part of the advanced energy system design and deployment has the potential to enable the “customization” of energy systems to meet local needs and resources. This will reduce cost and environmental impact of energy production and use. Examples of how the technology development process can be changed in the energy sector will be discussed using fuel cell turbine hybrids as an example.

This report maps the African landscape of Open Science – with a focus on Open Data as a sub-set of Open Science. Data to inform the landscape study were collected through a variety of methods, including surveys, desk research, engagement with a community of practice, networking with stakeholders, participation in conferences, case study presentations, and workshops hosted. Although the majority of African countries (35 of 54) demonstrates commitment to science through its investment in research and development (R&D), academies of science, ministries of science and technology, policies, recognition of research, and participation in the Science Granting Councils Initiative (SGCI), the following countries demonstrate the highest commitment and political willingness to invest in science: Botswana, Ethiopia, Kenya, Senegal, South Africa, Tanzania, and Uganda. In addition to existing policies in Science, Technology and Innovation (STI), the following countries have made progress towards Open Data policies: Botswana, Kenya, Madagascar, Mauritius, South Africa and Uganda. Only two African countries (Kenya and South Africa) at this stage contribute 0.8% of its GDP (Gross Domestic Product) to R&D (Research and Development), which is the closest to the AU’s (African Union’s) suggested 1%. Countries such as Lesotho and Madagascar ranked as 0%, while the R&D expenditure for 24 African countries is unknown. In addition to this, science globally has become fully dependent on stable ICT (Information and Communication Technologies) infrastructure, which includes connectivity/bandwidth, high performance computing facilities and data services. This is especially applicable since countries globally are finding themselves in the midst of the 4th Industrial Revolution (4IR), which is not only “about” data, but which “is” data. According to an article1 by Alan Marcus (2015) (Senior Director, Head of Information Technology and Telecommunications Industries, World Economic Forum), “At its core, data represents a post-industrial opportunity. Its uses have unprecedented complexity, velocity and global reach. As digital communications become ubiquitous, data will rule in a world where nearly everyone and everything is connected in real time. That will require a highly reliable, secure and available infrastructure at its core, and innovation at the edge.” Every industry is affected as part of this revolution – also science. An important component of the digital transformation is “trust” – people must be able to trust that governments and all other industries (including the science sector), adequately handle and protect their data. This requires accountability on a global level, and digital industries must embrace the change and go for a higher standard of protection. “This will reassure consumers and citizens, benefitting the whole digital economy”, says Marcus. A stable and secure information and communication technologies (ICT) infrastructure – currently provided by the National Research and Education Networks (NRENs) – is key to advance collaboration in science. The AfricaConnect2 project (AfricaConnect (2012–2014) and AfricaConnect2 (2016–2018)) through establishing connectivity between National Research and Education Networks (NRENs), is planning to roll out AfricaConnect3 by the end of 2019. The concern however is that selected African governments (with the exception of a few countries such as South Africa, Mozambique, Ethiopia and others) have low awareness of the impact the Internet has today on all societal levels, how much ICT (and the 4th Industrial Revolution) have affected research, and the added value an NREN can bring to higher education and research in addressing the respective needs, which is far more complex than simply providing connectivity. Apart from more commitment and investment in R&D, African governments – to become and remain part of the 4th Industrial Revolution – have no option other than to acknowledge and commit to the role NRENs play in advancing science towards addressing the SDG (Sustainable Development Goals). For successful collaboration and direction, it is fundamental that policies within one country are aligned with one another. Alignment on continental level is crucial for the future Pan-African African Open Science Platform to be successful. Both the HIPSSA ((Harmonization of ICT Policies in Sub-Saharan Africa)3 project and WATRA (the West Africa Telecommunications Regulators Assembly)4, have made progress towards the regulation of the telecom sector, and in particular of bottlenecks which curb the development of competition among ISPs. A study under HIPSSA identified potential bottlenecks in access at an affordable price to the international capacity of submarine cables and suggested means and tools used by regulators to remedy them. Work on the recommended measures and making them operational continues in collaboration with WATRA. In addition to sufficient bandwidth and connectivity, high-performance computing facilities and services in support of data sharing are also required. The South African National Integrated Cyberinfrastructure System5 (NICIS) has made great progress in planning and setting up a cyberinfrastructure ecosystem in support of collaborative science and data sharing. The regional Southern African Development Community6 (SADC) Cyber-infrastructure Framework provides a valuable roadmap towards high-speed Internet, developing human capacity and skills in ICT technologies, high- performance computing and more. The following countries have been identified as having high-performance computing facilities, some as a result of the Square Kilometre Array7 (SKA) partnership: Botswana, Ghana, Kenya, Madagascar, Mozambique, Mauritius, Namibia, South Africa, Tunisia, and Zambia. More and more NRENs – especially the Level 6 NRENs 8 (Algeria, Egypt, Kenya, South Africa, and recently Zambia) – are exploring offering additional services; also in support of data sharing and transfer. The following NRENs already allow for running data-intensive applications and sharing of high-end computing assets, bio-modelling and computation on high-performance/ supercomputers: KENET (Kenya), TENET (South Africa), RENU (Uganda), ZAMREN (Zambia), EUN (Egypt) and ARN (Algeria). Fifteen higher education training institutions from eight African countries (Botswana, Benin, Kenya, Nigeria, Rwanda, South Africa, Sudan, and Tanzania) have been identified as offering formal courses on data science. In addition to formal degrees, a number of international short courses have been developed and free international online courses are also available as an option to build capacity and integrate as part of curricula. The small number of higher education or research intensive institutions offering data science is however insufficient, and there is a desperate need for more training in data science. The CODATA-RDA Schools of Research Data Science aim at addressing the continental need for foundational data skills across all disciplines, along with training conducted by The Carpentries 9 programme (specifically Data Carpentry 10 ). Thus far, CODATA-RDA schools in collaboration with AOSP, integrating content from Data Carpentry, were presented in Rwanda (in 2018), and during17-29 June 2019, in Ethiopia. Awareness regarding Open Science (including Open Data) is evident through the 12 Open Science-related Open Access/Open Data/Open Science declarations and agreements endorsed or signed by African governments; 200 Open Access journals from Africa registered on the Directory of Open Access Journals (DOAJ); 174 Open Access institutional research repositories registered on openDOAR (Directory of Open Access Repositories); 33 Open Access/Open Science policies registered on ROARMAP (Registry of Open Access Repository Mandates and Policies); 24 data repositories registered with the Registry of Data Repositories (re3data.org) (although the pilot project identified 66 research data repositories); and one data repository assigned the CoreTrustSeal. Although this is a start, far more needs to be done to align African data curation and research practices with global standards. Funding to conduct research remains a challenge. African researchers mostly fund their own research, and there are little incentives for them to make their research and accompanying data sets openly accessible. Funding and peer recognition, along with an enabling research environment conducive for research, are regarded as major incentives. The landscape report concludes with a number of concerns towards sharing research data openly, as well as challenges in terms of Open Data policy, ICT infrastructure supportive of data sharing, capacity building, lack of skills, and the need for incentives. Although great progress has been made in terms of Open Science and Open Data practices, more awareness needs to be created and further advocacy efforts are required for buy-in from African governments. A federated African Open Science Platform (AOSP) will not only encourage more collaboration among researchers in addressing the SDGs, but it will also benefit the many stakeholders identified as part of the pilot phase. The time is now, for governments in Africa, to acknowledge the important role of science in general, but specifically Open Science and Open Data, through developing and aligning the relevant policies, investing in an ICT infrastructure conducive for data sharing through committing funding to making NRENs financially sustainable, incentivising open research practices by scientists, and creating opportunities for more scientists and stakeholders across all disciplines to be trained in data management.