AI-Powered Cybersecurity Data-Driven Threat Detection and Risk Mitigation Strategies
Volume 1 Issue 1
Year of Publication : 2025
Authors : Mohamed Kasim, Appas
Doi : XXXX XXXX XXXX
Keywords
Cybertysecurity, Risk Mitigation Strategies, Artificial Intelligence (AI), ML, DL and NLP.
Abstract
Since cyber threats and attacks on individuals, businesses and governments have escalated in numbers and severity, cybertysecurity has become of the most pressing issues of the digital era. Signature-based Detection Traditional rule and signature based detection mechanisms are well known to be insufficient in order to identify and react properly on such emerging threats. Artificial Intelligence (AI), and data driven analytics that come with it are now changing the way we think about cybersecurity – to become our Personal Predictive-Reactive-Adaptive Force. In this study, we investigate AI and data science-based algorithms for threat detection or risk management. It also presents existing ML, DL and NLP for cyber-security developments specifically focusing on data ingression quality and interpretability from adversarial threats’ perspective and articulates research issues towards responsible AI-driven cyber-security systems.
Cite this Article
Mohamed Kasim, Appas, 2025. "AI-Powered Cybersecurity Data-Driven Threat Detection and Risk Mitigation Strategies", International Journal for Research in Computer Science and Information Technology (IJRCSIT) 1(1): 40-48.