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ZAT113 Data Analytics for Cyber Security Module 2, ZAT113 Data Analytics…

- - - - Define, Measure, Analyse, Improve and Control along with logical Modification of the design and a Redesign process leading back to Measurement
    - - Understand
        
        Why analyzing and what you are collecting to achieve the goal
        Collect
        
        The data you need to meet goal
        Explore
        
        The data you collect as there is no guarantee it will be useful or tell everything
        Communicate
        
        What you have found using visual and non-visual methods
    - - Singular Event
        Things that occur that we want to analyse. e.g. A Specific attack on an organization, the mechanisms of a specific malware variant, or the system movement of a specific individual.
        Definable, narrow in scope. Easy to understand and apply the measurable, specific and concise elements to.
        Persistent Monitoring
        More resource intensive and engages in machine learning to analyse the data gathered in near real-time.
    - - Understanding what data we have available. e,g, dealing with a pdf file theres only so many ways it can be manipulated.
        You would need to have a working knowledge of the ways the PDF can be compromised to start your data analysis process.
    - - e.g. exporting a PCAP showing only UDP packets which provided smaller data surface for analysis
    - - e.g. median salary of Australians is found by analysing salary of all Australians and finding the Median (middle) number
        Quantitative - Looking at numbers to generate statistics, trends and other useful results. e.g. "37% of employees have a persistent login session" which means a third of workforce never logs out of systems.
        Qualitative - To analyse non-traditional data such as pictures, images, video, writing etc.
    - - e.g. Dropping packets from certain domains if they are performing DoS attacks on system.Creating redundancies in network to accommodate hardware failures.
    - - Deployment - using analysis to communicate findings and recommended outcomes based on the data. e.g. look at modelling the effects of a ransomware attack against your organisation and find that the loss would be minimal so recommend that the organisation keeps off-site backups but do nothing special
        Control - Continuous monitoring and management of the improvement.