Cybersecurity Risk Prediction

Predicting Cyberattacks with the help of Machine Learning. Learning (PCAML) is a system that predicts cyber threats using a range of data sets and artificial intelligence. PCAML models have high precision and low false positives through the analysis of system logs and user behaviour based on logistic regression, Support Vector Machines, Multinomial Naive Bayes, and TFIDF. Having its proactive defence strategies and early warning features, this technology can revolutionize the process of cybersecurity. PCAML has immense potentials of enhancing security within organisations and lower the risk of cyber attacks even though challenges such as accuracy and evolving threats exist.