Predictive Analysis of Ransomware Attacks using Context-aware AI in IoT Systems

Ransomware attacks are emerging as a major source of malware intrusion in recent times. While so far ransomware has affected general-purpose adequately resourceful computing systems, there is visible shift towards low-cost Internet Things systems which tend to manage critical endpoints industrial systems. Many prediction techniques proposed but need for more suitable constrained heterogeneous IoT Using attack context information profiles reduces the use resources required by resource-constrained This paper presents context-aware technique that uses ontology extracting features (connection requests, software updates, etc.) and Artificial Intelligence, Machine Learning algorithms predicting ransomware. The focus rely on early detection penetration attempts There an increase 60 % reduction time taken when using dataset over non-context aware data.