Identification of Attack Paths Using Kill Chain and Attack Graphs
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F22%3A00125603" target="_blank" >RIV/00216224:14610/22:00125603 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1109/NOMS54207.2022.9789803" target="_blank" >http://dx.doi.org/10.1109/NOMS54207.2022.9789803</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/NOMS54207.2022.9789803" target="_blank" >10.1109/NOMS54207.2022.9789803</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Identification of Attack Paths Using Kill Chain and Attack Graphs
Popis výsledku v původním jazyce
The ever-evolving capabilities of cyber attackers force security administrators to focus on the early identification of emerging threats. Targeted cyber attacks usually consist of several phases, from initial reconnaissance of the network environment to final impact on objectives. This paper investigates the identification of multi-step cyber threat scenarios using kill chain and attack graphs. Kill chain and attack graphs are threat modeling concepts that enable determining weak security defense points. We propose a novel kill chain attack graph that merges kill chain and attack graphs together. This approach determines possible chains of attacker’s actions and their materialization within the protected network. The graph generation uses a categorization of threats according to violated security properties. The graph allows determining the kill chain phase the administrator should focus on and applicable countermeasures to mitigate possible cyber threats. We implemented the proposed approach for a predefined range of cyber threats, especially vulnerability exploitation and network threats. The approach was validated on a real-world use case. Publicly available implementation contains a proof-of-concept kill chain attack graph generator.
Název v anglickém jazyce
Identification of Attack Paths Using Kill Chain and Attack Graphs
Popis výsledku anglicky
The ever-evolving capabilities of cyber attackers force security administrators to focus on the early identification of emerging threats. Targeted cyber attacks usually consist of several phases, from initial reconnaissance of the network environment to final impact on objectives. This paper investigates the identification of multi-step cyber threat scenarios using kill chain and attack graphs. Kill chain and attack graphs are threat modeling concepts that enable determining weak security defense points. We propose a novel kill chain attack graph that merges kill chain and attack graphs together. This approach determines possible chains of attacker’s actions and their materialization within the protected network. The graph generation uses a categorization of threats according to violated security properties. The graph allows determining the kill chain phase the administrator should focus on and applicable countermeasures to mitigate possible cyber threats. We implemented the proposed approach for a predefined range of cyber threats, especially vulnerability exploitation and network threats. The approach was validated on a real-world use case. Publicly available implementation contains a proof-of-concept kill chain attack graph generator.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10200 - Computer and information sciences
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
NOMS 2022 - 2022 IEEE/IFIP Network Operations and Management Symposium
ISBN
9781665406017
ISSN
1542-1201
e-ISSN
—
Počet stran výsledku
6
Strana od-do
1-6
Název nakladatele
IEEE Xplore Digital Library
Místo vydání
Budapest, Hungary
Místo konání akce
Budapest, Hungary
Datum konání akce
1. 1. 2022
Typ akce podle státní příslušnosti
CST - Celostátní akce
Kód UT WoS článku
000851572700059