CLOUD BASED ARCHITECTURE FOR ADAPTIVE LOGGING METHOD IMPLEMENTATION

Abstract

Software technology drives a considerable amount of day-to-day processes, changing and shifting the usual way of doing things and can even provide a great aid in times of crisis. From virtual private network solutions that helped battling challenges of remote work models that were necessary during initial outbreaks of COVID-19, to artificial intelligence solutions, that transform the way people learn and research information, and cloud compute models altering the way software is written and deployed – the change is everywhere. But it also brings new dilemmas, including those related to security of software and its consumers, which means that proper protection and control over computer programs is still in high demand.

This paper takes a deeper look at the observability aspect of cybersecurity and presents a model of how theoretical aspects of adaptive logging method can be deployed in a real-life web-server scenario. The model is based on the infrastructure provided by one of the largest cloud computing platforms providers and shows the application and mapping of two important formal definitions to real world services. The applicability of adaptive approach is verified and it is demonstrated that a considerable number of compute platforms should be able to incorporate and execute all the necessary components, making it suitable for different applications and use cases. Also the exclusion of dedicated security mechanisms in the formal definitions of adaptive logging method is shown to be a viable method of operation, given that services provided by the cloud can enforce necessary degree of security and still be transparent to the implementation itself.