Scientia et Securitas
Volume/Issue:
Volume 2: Issue 2
Hogyan befolyásolja a villamosenergia-hálózatról rendelkezésre álló információ a fizikai támadások által okozott sérülékenységről alkotott képet?
A hazai energiaszolgáltatás túlélőképessége
Author:
Bálint Hartmann Eötvös Loránd Kutatási Hálózat, Energiatudományi Kutatóközpont, Budapest, Magyarország; ELKH Centre for Energy Research, Budapest, Hungary

Search for other papers by Bálint Hartmann in
Current site
Google Scholar
PubMed Close
Pages:
155–163
Online Publication Date:
10 Oct 2021
Publication Date:
10 Oct 2021
Article Category:
Research Article
DOI:
https://doi.org/10.1556/112.2021.00030
Keywords:
power system; vulnerability; complex network; attack; betweenness;
Keywords (Hungarian):
villamosenergia-rendszer; sérülékenység; komplex hálózat; támadás; köztiség;
Open access

Összefoglaló. A villamosenergia-rendszerek fizikai támadásokkal szembeni ellenálló képessége a közelmúltban világszerte történt események ismeretében egyre nagyobb hangsúlyt kap a tématerület kutatásaiban. Az ilyen eseményekre való megfelelő felkészüléshez elengedhetetlen az üzemeltetett infrastruktúrának, elsősorban annak gyengeségeinek pontos ismerete. A cikkben Magyarország villamosenergia-hálózatának adatai alapján készített súlyozatlan és súlyozott gráfokon végzünk vizsgálatokat, hogy megértsük a különböző stratégia mentén kiválasztott célpontok elleni támadások milyen mértékben csökkentik a topológiai hatékonyságot. A cikk célja egyben a magyar hálózat sérülékenységének általános bemutatása is, mely hasznos bemeneti információ lehet a kockázati tervek elkészítésekor.

Summary. Tolerance of the power grid against physical intrusions has gained importance in the light of various attacks that have taken place around the world. To adequately prepare for such events, grid operators have to possess a deep understanding of their infrastructure, more specifically, of its weaknesses. A graph representation of the Hungarian power grid was created in a way that the vertices are generators, transformers, and substations and the edges are high-voltage transmission lines. All transmission and sub-transmission elements were considered, including the 132 kV network as well. The network is subjected to various types of single and double element attacks, objects of which are selected according to different aspects. The vulnerability of the network is measured as a relative drop in efficiency when a vertex or an edge is removed from the network. Efficiency is a measure of the network’s performance, assuming that the efficiency for transmitting electricity between vertices i and j is proportional to the reciprocal of their distance. In this paper, simultaneous removals were considered, arranged into two scenarios (single or double element removal) and a total of 5 cases were carried out (single vertex removal, single edge removal, double vertex removal, double edge removal, single vertex and single edge removal). During the examinations, all possible removal combinations were simulated, thus the 5 cases represent 385, 504, 73920, 128271 and 193797 runs, respectively. After all runs were performed, damage values were determined for random and targeted attacks, and attacks causing maximal damage were also identified. In all cases, damage was calculated for unweighted and weighted networks as well, to enable the comparison of those two models. The aims of this paper are threefold: to perform a general assessment on the vulnerability of the Hungarian power grid against random and targeted attacks; to compare the damage caused by different attack strategies; and to highlight the differences between using unweighted and weighted graphs representations. Random removal of a single vertex or a single edge caused 0.3–0.4% drop in efficiency, respectively, which indicates a high tolerance against such attacks. Damage for random double attacks was still only in the range of 0.6–0.8%, which is acceptable. It was shown that if targets are selected by the attacker based on the betweenness rank of the element, damage would be below the maximal possible values. Comparison of the damage measured in the unweighted and the weighted network representations has shown that damage to the weighted network tends to be bigger for vertex attacks, but the contrary is observed for edge attacks. Numerical differences between the two representations do not show any trend that could be generalised, but in the case of the most vulnerable elements significant differences were found in damage measures, which underlines the importance of using weighted models.

  • 1

    Albert, R., Albert, I., & Nakarado, G. L. (2004) Structural vulnerability of the North American power grid. Physical Review E, Vol. 69. No. 2. https://link.aps.org/doi/10.1103/PhysRevE.69.025103

  • 2

    Arianos, S., Bompard, E., Carbone, A., & Xue, F. (2009) Power grid vulnerability: A complex network approach. Chaos: An Interdisciplianry Journal of Nonlinear Science, Vol. 19. No. 1. https://doi.org/10.1063/1.3077229

  • 3

    Aziz, T., Lin, Z., Waseem, M., & Liu, S. (2020) Review on optimization methodologies in transmission network reconfiguration of power systems for grid resilience. International Transactions on Electrical Energy Systems, Vol. 31. No. 3. https://doi.org/10.1002/2050-7038.12704

  • 4

    Beyza, J., Garcia-Paricio, E., Ruiz, H. F., & Yusta, J. M. (2020) Geodesic Vulnerability Approach for Identification of Critical Buses in Power Systems. Journal of Modern Power Systems and Clean Energy, Vol. 8. pp. 727–736. https://doi.org/10.35833/MPCE.2018.000779

  • 5

    Bompard, E., Napoli, R., & Xue, F. (2009) Analysis of structural vulnerabilities in power transmission grids. International Journal of Critical Infrastructure Protection, Vol. 2., No. 1–2. pp. 5–12. https://doi.org/10.1016/j.ijcip.2009.02.002

  • 6

    Bompard, E., Wu, D., & Xue, F. (2010) The concept of betweenness in the analysis of power grid vulnerability. Proc. Complexity in Engineering, 2010 (COMPENG’10), Rome, Italy, 22–24 February 2010, pp. 52–54. https://doi.org/10.1109/COMPENG.2010.10

  • 7

    Brummitt, C. D., D’Souza, R. M., & Leicht, R. (2012) Suppressing cascades of load in interdependent networks. Proceedings of the National Acemy of the United States of America, Vol. 109. No. 12. E680–E689, https://doi.org/10.1073/pnas.1110586109

  • 8

    Chassin, D. P., & Posse, C. (2005) Evaluating North American electric grid reliability using the Barabási–Albert network model. Physica A, Vol. 355. No. 2–4. pp. 667–677. https://doi.org/10.1016/j.physa.2005.02.051

  • 9

    Chen, Z., Zhu, J., Li, S., & Luo, T. (2020) Detection of False Data Injection Attack in Automatic Generation Control System with Wind Energy based on Fuzzy Support Vector Machine. Proc. IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society, Singapore, 2020, pp. 3523–3528. https://doi.org/10.1109/IECON43393.2020.9255020

  • 10

    Crucitti, P., Latora, V., & Marchiori, M. (2004a) A topological analysis of the Italian electric power grid. Physica A, Vol. 338. No. 1–2. pp. 92–97. https://doi.org/10.1016/j.physa.2004.02.029

  • 11

    Crucitti, P., Latora, V., & Marchiori, M. (2004b) Model for cascading failures in complex networks. Physical Review E, Vol. 69. No. 4. https://link.aps.org/doi/10.1103/PhysRevE.69.045104

  • 12

    Crucitti, P., Latora, V., Marchiori, M. (2005) Locating critical lines in high-voltage electrical power grids. Fluctuation and Noise Letters, Vol. 5. No. 2. L201–L208, https://doi.org/10.1142/S0219477505002562

  • 13

    Cuadra, L., Salcedo-Sanz, S., Ser, J., Jiménez-Fernández, S., & Geem, Z. W. (2015) A Critical Review of Robustness in Power Grids Using Complex Networks Concepts. Energies, Vol. 8. No. 9. pp. 9211–9265. https://doi.org/10.3390/en8099211

  • 14

    Dwivedi, A., Yu, X., & Sokolowski, P. (2009) Identifying vulnerable lines in a power network using complex network theory. Proc. IEEE International Symposium on Industrial Electronics (ISIE 2009), Seoul, Korea, 5–8 July 2009, pp. 18–23. https://doi.org/10.1109/ISIE.2009.5214082

  • 15

    Dwivedi, A., Yu, X., & Sokolowski, P. (2010) Analyzing power network vulnerability with maximum flow based centrality approach. Proc. 8th IEEE International Conference on Industrial Informatics (INDIN), Osaka, Japan, 1–16 July 2010, pp. 336–341. https://doi.org/10.1109/INDIN.2010.5549398

  • 16

    Edib, S. N., Lin, Y., Vokkarane, V., Qiu, F., Yao, R., & Zhao, D. (2020) PMU and Communication Infrastructure Restoration for Post-Attack Observability Recovery of Power Grids. Proc. 2020 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), Tempe, AZ, USA, 2020, pp. 1–6. https://doi.org/10.1109/SmartGridComm47815.2020.9303014

  • 17

    Európai Parlament és Tanács (2019) Az Európai Parlament és a Tanács (EU) 2019/941 rendelete (2019. június 5.) a villamosenergia-ágazati kockázatokra való felkészülésről és a 2005/89/EK irányelv hatályon kívül helyezéséről

  • 18

    Európai Unió (2017) A Bizottság (EU) 2017/1485 rendelete (2017. augusztus 2.) a villamosenergia-átviteli hálózat üzemeltetésére vonatkozó iránymutatás megalkotásáról.

  • 19

    Fang, J., Wu, J., Zheng, Z., & Tse, C. K. (2021) Revealing Structural and Functional Vulnerability of Power Grids to Cascading Failures. IEEE Journal on Emergingand Selected Topics in Cirtuits and Systems, Vol. 11. No. 1. pp. 133–143. https://doi.org/10.1109/JETCAS.2020.3033066

  • 20

    Fronczak, A., Fronczak, P., & Hołyst, J. A. (2004) Average path length in random networks. Physical Review E, Vol. 70. No. 5. https://link.aps.org/doi/10.1103/PhysRevE.70.056110

  • 21

    Galindo-González, C. C., Angulo-Garcia, D., & Osorio, G. (2020) Decreased resilience in power grids under dynamically induced vulnerabilities. New Journal of Physics, Vol. 22. https://doi.org/10.1088/1367-2630/abb962

  • 22

    Gao, X., Pu, C., & Li, L. (2020) Vulnerability assessment of power grids against cost-constrained hybrid attacks. IEEE Transactions on Circuits and Systems II, Vol. 68. No. 4. pp. 1477–1481. https://doi.org/10.1109/TCSII.2020.3033545

  • 23

    Ghafouri, M., Au, M., Kassouf, M., Debbabi, M., Assi, C., & Yan, J. (2020) Detection and Mitigation of Cyber Attacks on Voltage Stability Monitoring of Smart Grids. IEEE Transactions on Smart Grid, Vol. 11. No. 6. pp. 5227–5238. https://doi.org/10.1109/TSG.2020.3004303

  • 24

    Gouhua, Z., Ce, W., Jianhua, Z., Jingyan, Y., Yin, Z., & Manyin, D. (2008) Vulnerability assessment of bulk power grid based on complex network theory. Proc. Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT 2008), Nanjuing, China, 6–9 April 2008, pp. 1554–1558. https://doi.org/10.1109/DRPT.2008.4523652

  • 25

    Han, P., & Zhang, S. (2011) Analysis of cascading failures in small-world power grid. International Journal of Energy Science, Vol. 1. No. 2. pp. 99–104.

  • 26

    He, Z., Jiang, F., Qian, F., Li, F., Yuan, X., Sang, Z., & Xie, Y. (2020) Defense Resources Optimization for AC-DC Hybrid System Against the Coordination Attack of False Data Injection Attack and Physical Attack. Proc. 2020 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia), Weihai, China, 2020, pp. 657–662. https://doi.org/10.1109/ICPSAsia48933.2020.9208447

  • 27

    Hines, P., Blumsack, S., Sanchez, E. C., & Barrows, C. (2010) The topological and electrical structure of power grids. Proc. 43th Hawaii International Conference on System Sciences (HICSS), Honolulu, HI, USA, 5–8 January 2010, pp. 1–10. https://doi.org/10.1109/HICSS.2010.398

  • 28

    Holmgren, Å. J. (2006) Using graph models to analyze the vulnerability of electric power networks. Risk Analysis, Vol. 26. No. 4. pp. 955–969. https://doi.org/10.1111/j.1539-6924.2006.00791.x

  • 29

    Holmgren, Å. J., Jenelius, A., & Westin, J. (2007) Evaluating strategies for defending electric power networks against antagonistic attacks. IEEE Transactions on Power Systems, Vol. 22. No. 1. pp. 76–84. https://doi.org/10.1109/TPWRS.2006.889080

  • 30

    Jin, M., Lavaei, J., Sojoudi, S., & Baldick, R. (2021) Boundary Defense Against Cyber Threat for Power System State Estimation. IEEE Transactions on Information Forensics and Security, Vol. 16., pp. 1752–1767. https://doi.org/10.1109/TIFS.2020.3043065

  • 31

    Khare, G., Mohapatra, A., & Singh, S. N. (2021) A Real-Time Approach for Detection and Correction of False Data in PMU Measurements. Electric Power Systems Research, Vol. 191. https://doi.org/10.1016/j.epsr.2020.106866

  • 32

    Kinney, R., Crucitti, P., Albert, R., & Latora, V. (2005) Modeling cascading failures in the North American power grid. The European Physical Journal B, Vol. 46., pp. 101–107. https://doi.org/10.1140/epjb/e2005-00237-9

  • 33

    Lesieutre, B., Borden, A., & Ramanathan, P. (2020) Preserving Confidentiality of Critical Energy Infrastructure Information. Principles of Cyber-Physical Systems: An Interdisciplinary Approach. Cambridge University Press. https://doi.org/10.1017/9781107588981

  • 34

    Liu, Z., & Wang, L. (2021) Leveraging Network Topology Optimization to Strengthen Power Grid Resilience Against Cyber-Physical Attacks. IEEE Transactions on Smart Grid, Vol. 12. No. 2. pp. 1552–1564. https://doi.org/10.1109/TSG.2020.3028123

  • 35

    Long, X., & Chen, C. (2020) Study on the Vulnerability of Power Grid Cascade Failures Based on Complex Network Theory. In: Jia Y., Zhang W., Fu Y. (eds) Proceedings of 2020 Chinese Intelligent Systems Conference. CISC 2020. Lecture Notes in Electrical Engineering, Vol. 706., pp. 307–315. https://doi.org/10.1007/978-981-15-8458-9_33

  • 36

    Mei, S., Zhang, X., & Cao, M. (2011a) Complex Small-World Power Grids. Power Grid Complexity, pp. 161–178. https://doi.org/10.1007/978-3-642-16211-4_5

  • 37

    Mei, S., Zhang, X., & Cao, M. (2011b) Power grid growth and evolution. Power Grid Complexity, pp. 133–160. https://doi.org/10.1007/978-3-642-16211-4_4

  • 38

    Pace, G. D., Wang, Z., Benin, J., He, H., & Sun, Y. (2020) Evaluation of Communication Delay Based Attack Against the Smart Grid. Proc. 2020 IEEE Kansas Power and Energy Conference (KPEC), Manhattan, KS, USA, 2020, pp. 1–6. https://doi.org/10.1109/KPEC47870.2020.9167543

  • 39

    Pagani, G. A., & Aiello, M. (2011) Towards decentralization: A topological investigation of the medium and low voltage grids. IEEE Transactions on Smart Grid, Vol. 2. No. 3. pp. 538–547. https://doi.org/10.1109/TSG.2011.2147810

  • 40

    Pahwa, S., Hodges, A., Scoglio, C., & Wood, S. (2010) Topological analysis of the power grid and mitigation strategies against cascading failures. Proc. 4th Annual IEEE Systems Conference, San Diego, CA, USA, 5–8 April 2010, pp. 272–276. https://doi.org/10.1109/SYSTEMS.2010.5482329

  • 41

    Panigrahi, P., & Maity, S. (2020) Structural vulnerability analysis in small-world power grid networks based on weighted topological model. International Transactions on Electrical Energy Systems, Vol. 30. No. 7. e12401, https://doi.org/10.1002/2050-7038.12401

  • 42

    Pepyne, D. L. (2007) Topology and cascading line outages in power grids. Journal of Systems Science and Systems Engineering, Vol. 16. pp. 202–221. https://doi.org/10.1007/s11518-007-5044-8

  • 43

    Rajkumar, V. S., Tealane, M., Ştefanov, A., Presekal, A., & Palensky, P. (2020) Cyber Attacks on Power System Automation and Protection and Impact Analysis. Proc. 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), The Hague, Netherlands, pp. 247–254. https://doi.org/10.1109/ISGT-Europe47291.2020.9248840

  • 44

    Rosas-Casals, M., Bologna, S., Bompard, E., D’Agostino, G., Ellens, W., Pagani, G.A, Scala, A, & Verma, T. (2015) Knowing power grids and understanding complexity science. International Journal of Critical Infrastructures, Vol. 11. No. 1. pp. 4–14. https://dx.doi.org/10.1504/IJCIS.2015.067399

  • 45

    Rosas-Casals, M., Valverde, S., & Solé, R. V. (2007) Topological vulnerability of the European power grid under errors and attacks. International Journal of Bifurcation and Chaos, Vol. 17. No. 7. pp. 2465–2475. https://doi.org/10.1142/S0218127407018531

  • 46

    Rosato, V., Bologna, S., & Tiriticco, F. (2007) Topological properties of high-voltage electrical transmission networks. Electric Power Systems Research, Vol. 77. No. 2. pp. 99–105. https://doi.org/10.1016/j.epsr.2005.05.013

  • 47

    Saraswat, G., Rui, Y., Yajing, L., & Yingchen Z. (2020) Analyzing the Effects of Cyberattacks on Distribution System State Estimation: Preprint, United States: N. p., 2020. Web. https://www.osti.gov/biblio/1737538

  • 48

    Sharma, D., Lin, C., Luo, X., Wu., D., Thulasiraman, K., & Jiang, J.N. (2020) Advanced techniques of power system restoration and practical applications in transmission grids. Electric Power Systems Research, Vol. 182., 106238, https://doi.org/10.1016/j.epsr.2020.106238

  • 49

    Shen, M., Gao, X., & Peng, M. (2020) Effects of Malware Attacks on the Cascading Failure of Cyber-physical Power System. Journal of Physics, Conference Series, 1624, 062005, https://doi.org/10.1088/1742-6596/1624/6/062005

  • 50

    Sičanica, Z., & Vujaklija, I. (2020) Resilience to cascading failures. A complex network approach for analysing the Croatian power grid. Proc. 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), Opatija, Croatia, 2020, pp. 918–922. https://doi.org/10.23919/MIPRO48935.2020.9245160

  • 51

    Singh, N. K., & Mahajan, V. (2020) Analysis and Evaluation of Cyber-attack Impact on Critical Power System Infrastructure. Smart Science, Vol. 9. pp. 1–13. https://doi.org/10.1080/23080477.2020.1861502

  • 52

    Solé, R. V., Rosas-Casals, M., Corominas-Murtra, B., & Valverde, S. (2008) Robustness of the European power grids under intentional attack. Physical Review E, Vol. 77. No. 2. 026102, https://link.aps.org/doi/10.1103/PhysRevE.77.026102

  • 53

    Tu, H., Shen, H-L., & Xia, Y. (2020) Cascading Failures of Power System with the Consideration of Cyber Attacks. Proc. 2020 IEEE International Symposium on Circuits and Systems (ISCAS), Sevilla, pp. 1–4. https://doi.org/10.1109/ISCAS45731.2020.9180816

  • 54

    Wang, G., Kong, X., Zhu, C., Xu, J., & Cao, Y. (2010) Identification of key lines in complex power grid based on power flow entropy. Proc. 2010 China International Conference on Electricity Distribution (CICED), Nanjing, China, 13–16 September 2010, pp. 1–6.

  • 55

    Wang, J. W., & Rong, L. L. (2009) Cascade-based attack vulnerability on the US power grid. Safety Science, Vol. 47. No. 10. pp. 1332–1336. https://doi.org/10.1016/j.ssci.2009.02.002

  • 56

    Wang, W., Song, Y., Li, Y., & Jia, Y. (2020) Research on Cascading Failures Model of Power Grid Based on Complex Network. Proc. 2020 Chinese Control And Decision Conference (CCDC), Hefei, China, 2020, pp. 1367–1372. https://doi.org/10.1109/CCDC49329.2020.9164048

  • 57

    Wang, Z., Scaglione, A., & Thomas, R. J. (2010) The node degree distribution in power grid and its topology robustness under random and selective node removals. Proc. 2010 IEEE International Conference on Communications Workshops (ICC), Capetown, South Africa, 23–27 May 2010, pp. 1–5. https://doi.org/10.1109/ICCW.2010.5503926

  • 58

    Watts, D., & Strogatz, S. (1998) Collective dynamics of ‘small-world’ networks. Nature, Vol. 393. pp. 440–442. https://doi.org/10.1038/30918

  • 59

    Wu, Y., Chen, J., Ru, Y., Xu, H., Roger, M., & Ni, M. (2020) Research on Power Communication Network Planning Based on Information Transmission Reachability Against Cyber-Attacks. IEEE Systems Journal, Early Access, Vol. 15. No. 2. pp. 2883–2894. https://doi.org/10.1109/JSYST.2020.3026997

  • 60

    Xiong X., Sun, D., Hao, S., Lin, G., & Li, H. (2020) Detection of False Data Injection Attack Based on Improved Distortion Index Method. Proc. 2020 IEEE 20th International Conference on Communication Technology (ICCT), Nanning, China, 2020, pp. 1161–1168. https://doi.org/10.1109/ICCT50939.2020.9295794

  • 61

    Zhou, X., Canady, R., Li, Y., Koutsoukos, X., & Gokhale, A. (2020) Overcoming Stealthy Adversarial Attacks on Power Grid Load Predictions Through Dynamic Data Repair. In: Darema F., Blasch E., Ravela S., Aved A. (eds) Dynamic Data Driven Applications Systems. DDDAS 2020. Lecture Notes in Computer Science, Vol. 12312., Springer, Cham., pp. 102–109. https://doi.org/10.1007/978-3-030-61725-7_14

  • Collapse
  • Expand
Cover Scientia et Securitas
Scientia et Securitas
Online ISSN:
2732-2688

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 (Óbuda 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)

Ministry of Interior
Science Strategy and Coordination Department
Address: H-2090 Remeteszőlős, Nagykovácsi út 3.
Phone: (+36 26) 795 906
E-mail: scietsec@bm.gov.hu

DOAJ

2023  
CrossRef Documents 32
CrossRef Cites 15
Days from submission to acceptance 59
Days from acceptance to publication 104
Acceptance Rate 81%

2022  
CrossRef Documents 38
CrossRef Cites 10
Days from submission to acceptance 54
Days from acceptance to publication 78
Acceptance Rate 84%

2021  
CrossRef Documents 46
CrossRef Cites 0
Days from submission to acceptance 33
Days from acceptance to publication 85
Acceptance Rate 93%

2020  
CrossRef Documents 13
CrossRef Cites 0
Days from submission to acceptance 30
Days from acceptance to publication 62
Acceptance Rate 93%

Publication Model Gold Open Access
Submission Fee none
Article Processing Charge none

Scientia et Securitas
Language Hungarian
English
Size A4
Year of
Foundation		 2020
Volumes
per Year		 1
Issues
per Year		 4
Founder Academic Council of Home Affairs and
Association of Hungarian PhD and DLA Candidates
Founder's
Address		 H-2090 Remeteszőlős, Hungary, Nagykovácsi út 3.
H-1055 Budapest, Hungary Falk Miksa utca 1.
Publisher Akadémiai Kiadó
Publisher's
Address		 H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher		 Chief Executive Officer, Akadémiai Kiadó
Applied
Licenses		 CC-BY 4.0
CC-BY-NC 4.0
ISSN ISSN 2732-2688

Monthly Content Usage

Abstract Views Full Text Views PDF Downloads
Apr 2024 0 36 4
May 2024 0 24 4
Jun 2024 0 33 4
Jul 2024 0 66 17
Aug 2024 0 29 14
Sep 2024 0 43 18
Oct 2024 0 53 12