Integrating Artificial Intelligence and Machine Learning Algorithms to Enhance Cybersecurity for E-Investment

Cyber threats targeting these systems are increasingly being refused as the use of e-investment continues to grow. This study provides an insightful idea on how integrating AI and ML Algorithms can help to boost the cybersecurity on Einvestment platforms. In order to identify irregularities, anticipate possible attacks, and enhance incident response, our AI- powered platform makes use of both supervised and unsupervised machine learning approaches. The methods for detecting fraud and emphasized the use of neural networks, decision trees, and support vector machines (SVM) in financial systems. Our system finds treads and weakness by analysis large amounts of data from multiple sources, allowing for proactive threat mitigation.