1.
G. Venkatesh
– Computer Science and Engg., Sri Venkateshwara Engg. College, JNTU, Hyderabad, Telangana, India.
2.
Anusha Merugu and P. Ilanna
– Computer Science and Engg., Sri Venkateshwara Engg. College, JNTU, Hyderabad, Telangana, India.
Abstract
Both in terms of frequency and size, cyber-attacks are increasing at a pace well beyond traditional defenses. This project aims to build an AI-driven security analysis framework: Discovering and for the most-timely possible reaction in real-time to new type threats on different fronts. It can tell signs of zero-day attacks from network traffic, user behavior logs. Over time, thanks to deep learning and other recent AI technologies, such methods will come to recognition ever more quickly among human observers. Threat intelligence Automation combined with intelligent light and fast reaction enabled by rapid response guarantees continuous learning and protection that keeps pace with changes in the environment across cloud, IoT (the Internet of Things) and corporate environments. This not only reinforces traditional system defenses but also makes them much more robust against sophisticated attacks.
Keywords Adaptive response, AI-powered security, Anomaly detection, Automated threat intelligence, Cybersecurity framework, Cyber threat detection, Deep learning, Machine learning, Natural Language Processing
