Authors:
Péter Ekler Budapesti Műszaki és Gazdaságtudományi Egyetem, Automatizálási és Alkalmazott Informatikai Tanszék [Budapest University of Technology and Economics, Department of Automation and Applied Informatics] Budapest Hungary

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Dániel Pásztor Budapesti Műszaki és Gazdaságtudományi Egyetem, Automatizálási és Alkalmazott Informatikai Tanszék [Budapest University of Technology and Economics, Department of Automation and Applied Informatics] Budapest Hungary

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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.

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  • Silver David , Schrittwieser Julian , Simonyan Karen , Antonoglou Ioannis , Huang Aja , Guez Arthur , Hubert Thomas , Baker Lucas , Lai Matthew , Bolton Adrian , Chen Yutian , Lillicrap Timothy , Hui Fan , Sifre Laurent , van den Driessche George , Graepel Thore & Hassabis Demis , 'Mastering the game of Go without human knowledge ' (2017 ) 550 (7676 ) Nature , 10 .

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  • Su Jiawei , Vargas Danilo Vasconcellos & Sakurai Kouichi , 'One Pixel Attack for Fooling Deep Neural Networks ' (2019 ) 23 (5 ) IEEE Transactions on Evolutionary Computation , 10 .

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Editor-in-Chief:

Founding Editor-in-Chief:

  • Tamás NÉMETH

Managing Editor:

  • István SABJANICS (Ministry of Interior, Budapest, Hungary)

Editorial Board:

  • Attila ASZÓDI (Budapest University of Technology and Economics)
  • Zoltán BIRKNER (University of Pannonia)
  • Valéria CSÉPE (Research Centre for Natural Sciences, Brain Imaging Centre)
  • Gergely DELI (University of Public Service)
  • Tamás DEZSŐ (Migration Research Institute)
  • Imre DOBÁK (University of Public Service)
  • Marcell Gyula GÁSPÁR (University of Miskolc)
  • József HALLER (University of Public Service)
  • Charaf HASSAN (Budapest University of Technology and Economics)
  • Zoltán GYŐRI (Hungaricum Committee)
  • János JÓZSA (Budapest University of Technology and Economics)
  • András KOLTAY (National Media and Infocommunications Authority)
  • Gábor KOVÁCS (University of Public Service)
  • Levente KOVÁCS buda University)
  • Melinda KOVÁCS (Hungarian University of Agriculture and Life Sciences (MATE))
  • Miklós MARÓTH (Avicenna Institue of Middle Eastern Studies )
  • Judit MÓGOR (Ministry of Interior National Directorate General for Disaster Management)
  • József PALLO (University of Public Service)
  • István SABJANICS (Ministry of Interior)
  • Péter SZABÓ (Hungarian University of Agriculture and Life Sciences (MATE))
  • Miklós SZÓCSKA (Semmelweis University)

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2023  
CrossRef Documents 32
CrossRef Cites 15
Days from submission to acceptance 59
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2021  
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Days from submission to acceptance 33
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2020  
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Scientia et Securitas
Language Hungarian
English
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2020
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per Year
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Founder Academic Council of Home Affairs and
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