Sentinel AI : Pioneering cyber threat detection and mitigation through advanced machine learning
Vandana Agarwal, Navnish Goel, Manish Sharma, Aditya Agarwal, Nisha Gupta, Sheetal Yadav · Journal of Information and Optimization Sciences · 2025
The Covid-19 pandemic has inevitably caused a sharp increase in the use of digital technologies as only manner of safeguarding ourselves. Covid-19 has forced numerous corporations and companies to adapt to remote work life. Owing to the trends towards digitalization of the key sectors of the economy nowadays, the leading enterprises and schools gradually switch to a remote work. The conclusion on the usage of AI and ML in the cybersecurity system is critical to triumph over the cyber threat and avoiding threats to valuable assets in the developed countries. In this article the author introduces a new product called Sentinel AI that implements machine learning for security purposes. The above system uses both supervised and unsupervised learning techniques which includes the deep learning, anomaly detection as well as the behavioral analysis to detect the known as well as the unknown threats. Since Sentinel AI can learn data patterns consistently, better predictions of threats can be done as well as attempts at faking positive results are slimmer, and hence, it is less susceptible to threats. Next-generation technologies along with the examples of their application and the method of improving the cybersecurity based on the anticipating and preventing threats has also been described in this paper.