Cyber threats demand proactive, automated defenses. Examine AI analytics, automated incident responses, vulnerability assessments and predictive modeling to empower cybersecurity professionals and IT managers to fortify organizational security in a relentless cyber landscape.
Cyber threats demand proactive, automated defenses. Examine AI analytics, automated incident responses, vulnerability assessments and predictive modeling to empower cybersecurity professionals and IT managers to fortify organizational security in a relentless cyber landscape.
Adele Kuzmiakova is a machine learning engineer working at the intersection of machine learning, computer vision, and natural language processing. Adele attended Cornell University in New York, United States for her undergraduate studies. She studied engineering with a focus on applied math. Some of the deep learning problems Adele worked on include predicting air quality from public webcams, developing a real-time human movement tracking, using 3D computer vision to create 3D avatars from selfies in order to bring online clothes shopping closer to reality, and creating visual stories and photobooks from photos on mobile devices. She is also passionate about exchanging ideas and inspiring other people and acted as a workshop organizer at Women in Data Science conference in Geneva, Switzerland in 2022 and 2023.
Inhaltsangabe
* Chapter 1 Introduction to Cyber Threat Intelligence * Chapter 2 Information Sharing and Dimensions to Circumvent Incidents and Mitigate Cyber Threats * Chapter 3 From Monitoring Logging, and Network Analysis to Threat Intelligence Extraction * Chapter 4 Threat Intelligence Platforms (TIPs) * Chapter 5 Automated Threat Analysis * Chapter 6 Incident Detection and Response Automation * Chapter 7 Threat Intelligence Sharing and Collaboration * Chapter 8 Machine Learning and AI in Threat Intelligence * Chapter 9 Automated Threat Intelligence Management * Chapter 10 Future Trends and Emerging Technologies
