Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.781413
Title: Improving cyber situational awareness via data mining and predictive analytic techniques
Author: Pourmouri, Sina
ISNI:       0000 0004 7967 0380
Awarding Body: Sheffield Hallam University
Current Institution: Sheffield Hallam University
Date of Award: 2019
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Abstract:
As cyber-attacks have become more common in everyday life, there is a need for maintaining and improving cyber security standards in any business or industry. Cyber Situational Awareness (CSA) is a broad strategy which can be adopted by any business or government to tackle cyber-attacks and incidents. CSA is based on current and past incidents, elements and actors in any system. Managers and decision makers need to monitor their systems constantly to understand ongoing events and changes which it can lead to predict future incidents. Prediction of future cyber incidents then can guide cyber managers to be prepared against future cyber threats and breaches. This research aims to improve cyber situational awareness by developing a framework based on data mining techniques specifically classification methods known as predictive approaches and Open Source Intelligence (OSINT). OSINT is another important element in this research because not only it is accessible publicly but also it is cost effective and research friendly. This research highlights the importance of understanding past and current CSA, which it can lead to more preparation against future cyber threats, and cyber security experts can use the developed framework with other different methods and provide a comprehensive strategy to improve cyber security and safety.
Supervisor: Akhgar, Babak Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.781413  DOI: Not available
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