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Organizations perform security analysis for assessing network health and safe-guarding their growing networks through Vulnerability Assessments (AKA VA Scans). The output of VA scans is reports on individual hosts and its vulnerabilities, which, are of little use as the origin of the attack can't be located from these. Attack Graphs, generated without an in-depth analysis of the VA reports, are used to fill in these gaps, but only provide cursory information. This study presents an effective model of depicting the devices and the data flow that efficiently identifies the weakest nodes along with the concerned vulnerability's origin.The complexity of the attach graph using MulVal has been greatly reduced using the proposed approach of using the risk and CVSS base score as evaluation criteria. This makes it easier for the user to interpret the attack graphs and thus reduce the time taken needed to identify the attack paths and where the attack originates from.
|Title of host publication||2019 International Conference on Computer Communication and Informatics, ICCCI 2019|
|Publisher||IEEE, Institute of Electrical and Electronics Engineers|
|Number of pages||6|
|Publication status||Published - 2019|
|Event||9th International Conference on Computer Communication and Informatics, ICCCI 2019 - Coimbatore, Tamil Nadu, India|
Duration: 23 Jan 2019 → 25 Jan 2019
|Name||2019 International Conference on Computer Communication and Informatics, ICCCI 2019|
|Conference||9th International Conference on Computer Communication and Informatics, ICCCI 2019|
|City||Coimbatore, Tamil Nadu|
|Period||23/01/19 → 25/01/19|
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