Data Clustering and Categorization for Processing Results from Penetration Testing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F26%3A0193515" target="_blank" >RIV/00216305:26220/26:0193515 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/abstract/document/11048825" target="_blank" >https://ieeexplore.ieee.org/abstract/document/11048825</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Data Clustering and Categorization for Processing Results from Penetration Testing

Popis výsledku v původním jazyce

As cyber threats and their potential impacts increase, the need for testing cyber resilience has become more important. Web applications are one of the frequent targets of cyberattacks, and therefore, the need for their penetration testing is desirable. However, these applications can contain up to tens of thousands of web resources, making the testing process very difficult. Our paper focuses on categorizing similar web resources from the reconnaissance phase to increase the overall effectiveness of penetration testing. For this purpose, we designed and developed a system for clustering and categorizing web resources using cluster analysis. We experimentally tested our solution in two iterations on 10,000 and 50,000 resources. The results show that e-commerce and newspaper websites contain a large amount of similar content, which our system was able to detect and provide penetration testers with the filtered sources for the next phase of penetration testing.

Název v anglickém jazyce

Data Clustering and Categorization for Processing Results from Penetration Testing

Popis výsledku anglicky

As cyber threats and their potential impacts increase, the need for testing cyber resilience has become more important. Web applications are one of the frequent targets of cyberattacks, and therefore, the need for their penetration testing is desirable. However, these applications can contain up to tens of thousands of web resources, making the testing process very difficult. Our paper focuses on categorizing similar web resources from the reconnaissance phase to increase the overall effectiveness of penetration testing. For this purpose, we designed and developed a system for clustering and categorizing web resources using cluster analysis. We experimentally tested our solution in two iterations on 10,000 and 50,000 resources. The results show that e-commerce and newspaper websites contain a large amount of similar content, which our system was able to detect and provide penetration testers with the filtered sources for the next phase of penetration testing.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20203 - Telecommunications

Projekt

<a href="/cs/project/VK01030019" target="_blank" >VK01030019: Interaktivní kontrolní seznamy pro efektivní testování kybernetické bezpečnosti</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

ICUMT 2024; 16th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops

ISBN

978-3-8007-6544-7

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

131-136

Název nakladatele

VDE

Místo vydání

Meloneras, Gran Canaria, Spain

Místo konání akce

Meloneras, Gran Canaria, Spain

Datum konání akce

26. 11. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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