Open Access
Information security anomalies in the it systems of hungarian public education
Attila Schüller
- 01 Jan 2013
TL;DR: In this paper, the authors have carried out case studies to demonstrate that the reason for these incidents is the human factor and therefore greater attention should be paid to the information security of these systems.
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Abstract: IT systems in public education involve information security risks due to recurrent security incidents. The author has carried out case studies to demonstrate that the reason for these incidents is the human factor. Public education is part of the critical infrastructure through its link with the public administration and associated IT infrastructure. Therefore greater attention should be paid to the information security of these systems. However, it should also be borne in mind that if the public administration authorities are negligent with the national systems our protection in more endangered fields may not be sufficient to counteract cyber terrorism. A kozoktatasban kotelezően előirt informatikai rendszerek szamos informaciobiztonsagi kockazatot rejtenek magukban, melyek miatt visszaterő biztonsagi incidensek fordulnak elő. A szerző esettanulmanyokat keszitett, melyen keresztul ravilagit, hogy ezen incidensek oka kizarolag a human faktor. A kozoktatas egyreszt a kozigazgatason keresztul, masreszt a hozza kapcsolodo informatikai infrastrukturan keresztul epul be a kritikus infrastrukturaba. Emiatt kiemelt figyelmet kellene forditani a műkodesehez szukseges rendszerek informaciobiztonsagi es informatikai vedelmere. Tovabba elgondolkodtato, hogy ha a kozigazgatasi szervek ennyire hanyagul kezelnek orszagos rendszereket, akkor a cyber terrorizmus altal meg inkabb veszelyeztetett teruleteken vajon elegendő vedelemmel rendelkezunk-e.
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References
DOKTORI (PhD) ÉRTEKEZÉS
Kémiai Doktori Iskola,Inzelt György,Záray Gyula +2 more
- 01 Jan 2007
TL;DR: Three novel similarity measures built around dynamic time warping are presented, which enable more precise data mining of time series by incorporating new aspects and provide solutions for time series similarity problems that previously could not be handled with elastic dissimilarity measures.