Big Data-Driven Information Security Behavioural Profiling for Organisational Resilience

Abstract

As cyber threats become more common, it is imperative to comprehend the behavioural patterns that contribute to security risks to bolster organisational resilience. This study aims to discover particular actions before security incidents in organisations by utilising big data analytics on survey responses to reveal these patterns. The main goal is to identify employee behaviours that are security vulnerabilities in order to gain practical insight for proactive risk management. A survey is conducted to collect data from various departments within the selected organisation. The survey gathered information regarding individuals' daily routines, compliance with security protocols, responses to security training, and past experiences with security breaches. The gathered information was analysed to find patterns and trends in behaviour associated with increased security risks. The study findings emphasise the importance of monitoring these behavioural indicators in order to enhance organisational resilience. Organisations can successfully reduce risks by understanding and dealing with these basic behaviours, implementing targeted interventions, improving security training programmes, and refining policies. This study provides valuable information on key indicators of employee behaviour that can be used to proactively tackle security risks, making a significant contribution to cybersecurity and the overall resilience of the organisation. The results derived from this study offer practical recommendations for organisations to enhance their defence against cyber threats by implementing informed behavioural monitoring and management.