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Agria Média 2020 konferencia

„Az oktatás digitális átállása korunk pedagógiai forradalma”

Scientia et Securitas
Author: Árpád Szörény Rab
Open access

Összefoglalás. A mesterséges intelligencia az elmúlt években hatalmas fejlődésen ment keresztül, melynek köszönhetően ma már rengeteg különböző szakterületen megtalálható valamilyen formában, rengeteg kutatás szerves részévé vált. Ez leginkább az egyre inkább fejlődő tanulóalgoritmusoknak, illetve a Big Data környezetnek köszönhető, mely óriási mennyiségű tanítóadatot képes szolgáltatni.

A cikk célja, hogy összefoglalja a technológia jelenlegi állapotát. Ismertetésre kerül a mesterséges intelligencia történelme, az alkalmazási területek egy nagyobb része, melyek központi eleme a mesterséges intelligencia. Ezek mellett rámutat a mesterséges intelligencia különböző biztonsági réseire, illetve a kiberbiztonság területén való felhasználhatóságra. A cikk a jelenlegi mesterséges intelligencia alkalmazások egy szeletét mutatja be, melyek jól illusztrálják a széles felhasználási területet.

Summary. In the past years artificial intelligence has seen several improvements, which drove its usage to grow in various different areas and became the focus of many researches. This can be attributed to improvements made in the learning algorithms and Big Data techniques, which can provide tremendous amount of training.

The goal of this paper is to summarize the current state of artificial intelligence. We present its history, introduce the terminology used, and show technological areas using artificial intelligence as a core part of their applications. The paper also introduces the security concerns related to artificial intelligence solutions but also highlights how the technology can be used to enhance security in different applications. Finally, we present future opportunities and possible improvements. The paper shows some general artificial intelligence applications that demonstrate the wide range usage of the technology.

Many applications are built around artificial intelligence technologies and there are many services that a developer can use to achieve intelligent behavior. The foundation of different approaches is a well-designed learning algorithm, while the key to every learning algorithm is the quality of the data set that is used during the learning phase. There are applications that focus on image processing like face detection or other gesture detection to identify a person. Other solutions compare signatures while others are for object or plate number detection (for example the automatic parking system of an office building). Artificial intelligence and accurate data handling can be also used for anomaly detection in a real time system. For example, there are ongoing researches for anomaly detection at the ZalaZone autonomous car test field based on the collected sensor data. There are also more general applications like user profiling and automatic content recommendation by using behavior analysis techniques.

However, the artificial intelligence technology also has security risks needed to be eliminated before applying an application publicly. One concern is the generation of fake contents. These must be detected with other algorithms that focus on small but noticeable differences. It is also essential to protect the data which is used by the learning algorithm and protect the logic flow of the solution. Network security can help to protect these applications.

Artificial intelligence can also help strengthen the security of a solution as it is able to detect network anomalies and signs of a security issue. Therefore, the technology is widely used in IT security to prevent different type of attacks.

As different BigData technologies, computational power, and storage capacity increase over time, there is space for improved artificial intelligence solution that can learn from large and real time data sets. The advancements in sensors can also help to give more precise data for different solutions. Finally, advanced natural language processing can help with communication between humans and computer based solutions.

Open access

Összefoglalás. A XXI. század első felében a korábban sok évtizeden keresztül lassan változó közlekedés gyorsított ütemben alakul át. Ez alatt a pár év alatt több változás következik be, több kihívást kell leküzdeni, mint a korábbi időszakban. Az elektromos hajtás térnyerése, új járműhasználati módok mellett a járművek autonomizálódása és összekapcsolódása jelenti az új irányokat, amelyek kihívás elé állítják nemcsak az autóipart, hanem a járművek használóit és a szabályzókat, az államot is. Kutatásainkban az önvezető autózás jelentette kihívásokat emeljük ki a többi, röviden bemutatott trend közül, majd pedig vizsgáljuk, milyen kihívásokat támaszt a digitalizálódó állam felé az önvezetés felé elmozduló járműves technológia.

Summary. In the first half of the 21st century, transportation that has been slowly changing over many decades has been transforming at an accelerated rate. Over the course of these few years, there will be more changes and more challenges to overcome. For a century it was unquestionable that a vehicle is driven by a driver and its energy comes via diesel or petrol from crude oil. Today vehicles’ autonomy in driving is increasing, and instead of crude oil based fuels first biocomponents and gaseous fuels appeared, and now electricity knocks at the door. The proliferation of the electric driving, the new modes of vehicle use, and the autonomy and connectivity of vehicles represent new directions that challenge not only the automotive industry, but also vehicle users and regulators, and the states. New technologies bring about new security and safety challenges as well. Most of the challenges pop up in the cyber security domain. And its result is that a closer cooperation is necessary between the automotive industry and informatics. As these two leading industrial fields have a different setup, the cooperation is energy demanding task for all participants. Modification and upgrade of the homologation process seems to be one of the potential gateways that could merge the safety requests. Improving traditionally rigid automotive homologation processes needs a lot of extended test opportunities. In our research, we highlight the challenges posed by self-driving cars and show some trends briefly, and then examine the challenges posed by vehicle technology moving towards self-driving, and towards digitizing. The certification process of the automotive industry is highlighted and modifications are proposed. We propose to extend the traditional proving ground based certification processes with special, autonomous vehicles designed processes that are partially made within the virtual reality-proving ground mixtures. A newly designed proving ground not only offers a wide range of vehicle and traffic tests for conventional, connected and automated vehicles, but can also be used to test possible prototype solutions, as well as helps to develop the type-approval process, and useful for educational purposes. Cyber security has special dimensions, newly developed test environment is necessary to validate the vehicles and their elements. A complete vehicle testing and validation center is proposed to establish for automotive cyber security features, focusing not only on known, but also on unknown vulnerabilities. It will help to develop dedicated tests to eliminate unknown vulnerabilities and potential new vulnerabilities.

Open access

Összefoglalás. A blokklánc-technológiákat első sikeres alkalmazásuk, a kriptopénzek tették híressé és hírhedté. Valódi jelentőségük azonban az általuk létrehozott új informatikai rendszerkategóriában, az adatbázis jellegű, több résztvevő által közösen hitelesen tartott elosztott főkönyvekben rejlik. A tanulmány ismerteti ezek alapelveit, jellemző üzleti alkalmazási mintáit és a „blokkláncosítást”, mint bevezetési stratégia tervezési elvet. Új eredményként a blokkláncosítás a biztonság területén alkalmazhatóságának megteremtéséhez felállításra kerül egy ismert példákon alapuló érték-modell.

Summary. Blockchain technologies were made famous – and arguably, infamous – by their first successful application: cryptocurrencies. Their true significance, however, lies in the novel IT system category they established: distributed ledgers, which are electronic systems of records maintained by multiple parties. The paper summarizes the key concepts of distributed ledger technologies, their key business application types and „blockchainification” as an innovation strategy planning methodology. As a novel contribution, the paper proposes the application of „blockchainification” in the complex context of security, and sets up an initial version of the necessary domain-specific value and application type framework.

Distributed Ledger Technologies (DLT) have reached maturity where they can be applied to, and have been demonstrated to be able to, facilitate a very broad range of cross-organizational and client-organization cooperation patterns. For enterprise and industrial usage, DLT key value dimensions, supporting blockchain capbilities and value driver application types have been already collected, facilitating the structured and benefit-based planning of their introduction.

One such approach is what we coined „blockchainification”. Blockchainification starts with a decomposition of the business architecture of an organization, to the point where specific cooperations can be characterized, both functionally and by the parties involved. Given such a decomposition, the viability of migrating or replacing the functionality with a DLT-based solution can be assessed, on a cooperation by cooperation basis, including the associated risks and benefits. This way, a blockchain introduction strategy can be formulated for the gradual introduction of DLTs. Additionally, blockchainification suggests – at least in the first phases of an introduction strategy – an emphasis on solutions where a DLT essentially just „replaces” the current information system support of already-digitized cooperations.

While in the enterprise and industrial sphere blockchainification is already facilitated by an example-based understanding of key value dimensions, blockchain capabilities and value driver applications, for many other domains, these prerequisites are missing. Importantly, what is already available is not readily applicable for organizations involved in security activities in the broad sense; in many aspects, the value these organizations seek from IT systems is markedly different from the enterprise world. Thus, the paper proposes an initial key value dimension and supporting blockchain capability model for organizations involved in providing a select set of security services.

Open access

Összefoglalás. „A mesterséges intelligencia társadalma” című könyvem, és ebből Kevin Kelly, amerikai teoretikus 2016-os összegzését foglalom itt röviden össze, mely a kialakult társadalmi állapotaink főbb változásait mutatja be a gépi értelem mindennapjainkra való szétterjedésének menetében. Kelly könyve tizenegy változási tendenciát elemez, melyek már bő harminc éve elkezdődtek a személyi számítógépek tömeges elterjedésével, de különösen a következő harminc évben hozzák létre a mesterséges intelligencia társadalmát.

Open access
Scientia et Securitas
Authors: Brigitta Tóth, Ádám Boncz, Bálint File, István Winkler, and Márk Molnár

Összefoglalás. A hálózatkutatás idegtudományi alkalmazása áttörő eredményt hozott a humán kogníció és a neurális rendszerek közötti kapcsolat megértésében. Jelen tanulmány célja a neurális hálózatok néhány kutatási területét mutatja be a laborunkban végzett vizsgálatok eredményein keresztül. Bemutatjuk az agyi aktivitás mérésének és az agyi területek közötti kommunikációs hálózatok modellezésének technikáját. Majd kiemelünk két kutatási terület: 1) az agyi hálózatok életkori változásainak vizsgálatát, ami választ ad arra, hogy hogyan öregszik az emberi agy; 2) az emberi agyak közötti hálózat modelljének vizsgálatát, amely a hatékony emberi kommunikáció idegrendszeri mechanizmusait próbálja feltárni. Tárgyaljuk a humán kommunikációra képes mesterséges intelligencia fejlesztésének lehetőségét is. Végül kitérünk az agyi hálózatok kutatásának biztonságpolitikai vonatkozásaira.

Summary. The human brain consists of 100 billion neurons connected by about 100 trillion synapses, which are hierarchically organized in different scales in anatomical space and time. Thus, it sounds reasonable to assume that the brain is the most complex network known to man. Network science applications in neuroscience are aimed to understand how human feeling, thought and behavior could emerge from this biological system of the brain. The present review focuses on the recent results and the future of network neuroscience. The following topics will be discussed:

Modeling the network of communication among brain areas. Neural activity can be recorded with high temporal precision using electroencephalography (EEG). Communication strength between brain regions then might be estimated by calculating mathematical synchronization indices between source localized EEG time series. Finally, graph theoretical models can describe the relationship between system elements (i.e. efficiency of communication or centrality of an element).

How does the brain age? While for a newborn the high plasticity of the brain provides the foundation of cognitive development, cognition declines with advanced age due to so far largely unknown neural mechanisms. In one of our studies, we demonstrated that there is a correlation between the anatomical development of the brain (at prenatal age) and its network topology. Specifically, the more developed the baby’s brain, the more functionally specialized/modular it was. In another study we found that in older adults, when compared to young adults, connectivity within modules of their brain network is decreased, with an associated decline in their short-term memory capacity. Moreover, Mild Cognitive Impairment patients (early stage of Alzheimer) were characterized with a significantly lower level of connectivity between their brain modules than the healthy elderly.

Human communication via shared network of brain activity. In another study we recorded the brain activity of a speaker and multiple listeners. We investigated the brain network similarity across listeners and between the speaker and listeners. We found that brain activity was significantly correlated among listeners, providing evidence for the fact that the same content is processed via similar neural computations within different brains. The data also suggested that the more the brain activity synchronizes the more the mental state of the individuals overlap. We also found significantly synchronized brain activity between speaker and listeners. Specifically 1) listeners’ brain activity within the speech processing cortices was synchronized to speaker’s brain activity with a time lag, indicating that listeners’ speech comprehension processes replicated the speaker’s speech production processes; and 2) listeners’ frontal cortical activity was synchronized to speaker’s later brain activity, that is, listeners preceded the speaker, indicating that speech content is predicted by the listeners based on the context.

Future challenges. Future research could target artificial intelligence development that is capable of human-like communication. To achieve this, the simultaneous recording of brain activity from listener and speaker is needed together with efficiency of the communication. These data could be then modelled via AI to detect biomarkers of communication efficiency. In general, neurotechnology has been rapidly developing within and outside of research and in clinical fields thus it is time for re-conceptualizing the corresponding human right law in order to avoid unwanted consequences of technological applications.

Open access

Összefoglalás. Jelen cikk célja a járműipar egyes területeit érintő kiberbiztonsági kockázatok vizsgálata. Fentiekkel összhangban a cikk első részében a járműipar kiberbiztonsági szempontból releváns területei kerülnek meghatározásra. Ezt követően megtörténik a 2018. évben rögzített járműipari kibertámadások kockázatalapú értékelő elemzése.

Summary. Nowadays, cybersecurity has a critical impact to our lives. The Internet has also got a substantial role in our days since many people are constantly connected to the Internet (e.g., through online social networks) . Besides, numerous personal and individual devices are connected. The growing number of connected devices and cyberspace expansion make our lives easier. However, this affects our privacy, with the potential for unauthorized use of personal information. In summary, life in a networked world carries unknown dangers.

In the future, many new risk factors are expected to occur, which will significantly increase the level of cybersecurity threats. Examining the aspects of the automotive industry, we should mention the summary of which explores the field’s problems through novel theoretical solutions and related practical considerations. The book pays special attention to vehicle communication and networked systems. This book examines three main scientific directions for 5G-compliant vehicle-to-vehicle communication and cooperative vehicle control: modeling and testing capabilities for vehicle-to-vehicle communication, state-of-the-art technologies related to the physical layer, and MAC design procedures .

Cheng and colleagues examined the communication channels currently applied in the automotive industry or that are expected to be applied soon. Particular attention has been paid to examining the tasks and challenges that need to be addressed in order to support the spread of the connected transport systems in the future. The evaluation focused on the cooperation of connected vehicles. Their study also outlined the most important security risks and challenges associated with new communication solutions.

In the light of the above-mentioned considerations, it can be said that the emergence of connected and autonomous vehicles can make a significant contribution to the positive effects of cyberspace, but can also have a disadvantageous impact on the vulnerability of transport processes.

In line with this, it is important to examine and understand the vulnerabilities of connected and autonomous vehicles, the threats to vehicles. With this knowledge, automotive cybersecurity professionals’ responsibility is to develop appropriate security functions and capabilities for connected and autonomous vehicles and transport systems. This enables the systems to detect, evaluate, and, if necessary, treat different attacks and malicious interventions.

Along with the above objectives, many research studies in the automotive segment have already focused on identifying cybersecurity assessment frameworks for motor vehicles. Among these, it is worth highlighting the projects “HEAling Vulnerabilities to ENhance Software Security and Safety” and “E-safety vehicle intrusion protected applications” .

Open access

Összefoglalás. Az elektronikusan tárolt információ biztonsága, általánosabban véve a kiberbiztonság, az egyik legnagyobb kihívás a 21. században. Folyamatosan jelennek meg újabb és újabb fenyegetések, melyekre innovatív és újszerű megoldásokat kell adni. Ezek az innovatív megoldások mindenképpen magukkal hozzák az olyan új típusú technológiák használatát az információbiztonságban, mint például a Nagy Adatokból (Big Data) való építkezés és az erre épülő mesterséges intelligencia. Ennek támogatása érdekében az Európai Unió a 2021 és 2027 közötti időszakban kiemelt fontosságúnak tartja a kiberbiztonsági innovációkat. A tanulmány bemutatja a kiberbiztonsági kompetenciahálózatok tervezetét, illetve ismerteti, hogy milyen kutatás-fejlesztés-innovációs lehetőségek lesznek a következő évtizedben Európában.

Summary. Security of stored digital information and more generally, cybersecurity is one of the biggest challenges of the 21st century. Besides the negative effects of cybercrime, cyberespionage, or other state sponsored activities, like cyberwarfare, our society and economy should face the exposure of infocommunication systems all around us. At the dawn of 4th industrial revolution when the whole world is going to be digitalized and will be surrounded by networked digital devices in homes, cities and industry, new threats are constantly emerging that need to be responded with new innovative solutions. These innovative solutions should include the usage of big data and artificial intelligence built onto it. They should also give a response for the inherited risks of legacy systems that can be found in many critical information infrastructures. Meanwhile, they should protect the digital privacy of citizens by not giving out unnecessary user data which is contradictory with the need of big data and AI mentioned before.

Due to the emerging cybersecurity threats and the virtually non-existence of European cybersecurity market, European Union gives high importance for cybersecurity innovation and will support it between 2021 and 2027. In the proposed budget for this period, approximately 3 billion of euros is expected to be spent to cybersecurity related research. On the one hand, that fund may help European research institutes, enterprises, and startups to appear on the global market, on the other hand this is the only possible way to regain Europe’s digital independence from the United States and China. In alignment with the European security policy, these innovative solutions may also lead to reducing the amount of cybercrime, ensure the resilience of continental critical information infrastructure and can help to establish strong European cyberwarfare capabilities. As Ursula von der Leyden, president of the European Commission said in her op-ed in February 2020, “The point is that Europe’s digital transition must protect and empower citizens, businesses and society as a whole. It has to deliver for people so that they feel the benefits of technology in their lives. To make this happen, Europe needs to have its own digital capacities – be it quantum computing, 5G, cybersecurity or artificial intelligence (AI). These are some of the technologies we have identified as areas for strategic investment, for which EU funding can draw in national and private sector funds.” The study presents the draft of cybersecurity competence networks and describes what R&D&I possibilities will be in Europe in the next decade.

Open access

Összefoglalás. A mesterséges intelligencia (továbbiakban: MI) fogalma az egyik napról a másikra robbant be a tudományos világból a nemzetközi és a hazai köztudatba. Az MI számos formában jelen van életünkben és az elkövetkező pár évtizeden belül pedig olyan megkerülhetetlen és hétköznapi technológiai megoldássá válik, mint ma az internet. Ezért érdemes megvizsgálni, hogy mit mondanak a kutatások az automatizáció hatásairól, mit gondolnak erről a munkáltatók, valamint a jövő munkavállalói. Létfontosságú, hogy megmutassuk az MI-ben rejlő társadalmi és piaci lehetőségeket, biztonsági veszélyeket, ezáltal növelve a magyar vállalkozók versenyképességét és a munkavállalók karrierlehetőségeit. Ennek egyik kezdőlépése a társadalom tudatosítása, valamint az MI oktatásban történő bevezetése, mely kiterjed a technológia iskolákban történő alkalmazásától, egészen használatának, fejlesztésének, biztonsági kockázatainak az oktatásáig.

Summary. The concept of artificial intelligence (hereinafter: AI) has exploded overnight from the scientific world into international and domestic public consciousness.

AI is present in many forms in our lives, and over the next few decades it is set to become as an essential and everyday tech solution as the Internet today.

Therefore, it is worth examining what research says about the effects of automation and what employers and future employees think about it. It is therefore of critical importance to demonstrate the social and market potentials and dangers for safety of AI, thereby increasing the competitiveness of Hungarian entrepreneurs and the career opportunities of the employees.

One of the first steps in this is to raise public awareness and introduce AI into education, ranging from the use of technology in schools to the education of its use, safety risk and development.

Is it worth thinking about what the distant future can bring to humanity? There are various professional predictions as to when we will invent the “real” AI, the master algorithm that controls each process, when we will achieve the singularity, from which AI will be able to program itself beyond human intelligence. Never, according to pessimists, between 2040–2100, according to optimists. Moreover, in the meantime, genetic engineering or a brain amplified with nanorobots may precede machine intelligence. What is certain is that cooperation and coexistence will be the cornerstone, so technical, philosophical, social, ethical and legal responses must be developed as long as the decision is in the hands of the US and not the AI. However, all this is a complex task, as logical contradictions in national regulations and political opinions, for example, are very difficult to handle for a rational algorithm. (Lovászy 2019) Regulation is needed that does not hinder economic development, but strengthens transparency and security.

The opportunities inherent in AI will be decisive for both Hungary’s competitiveness and the success of the individual in the coming decades. In my study, I pointed out that the conscious use and development of AI by education, the knowledge of security risks can be a breaking point for broad strata of our nation.

So, I first examined the impact of the use of AI on the labor market, what new generations of workers think and want, and how it all affects the educator, the content and tools of education, the methodology, and what are the benefits and risks. Then I flashed a couple of possible visions in which, whether we achieve singularity in the near or distant future or not, AI will be a crucial part of our everyday lives.

The pillars, technological and sectoral focuses, and transformative projects of the newly adopted Artificial Intelligence Strategy Foundation will crucially determine how much we will be able to exploit the opportunities of the decades ahead at the individual and state levels. In order to increase Hungary’s competitiveness, it calls for further research and wide-ranging professional consultations on the conditions (infrastructure, competencies, etc.) and modern methods for the successful integration of AI, the awareness of society and the education of different age groups.

Open access