Threat Forecasting Leveraging Big Data for Predictive Analysis [Paperback]

Drawing upon years of practical experience and using numerous examples and illustrative case studies, Threat Forecasting: Leveraging Big Data for Predictive Analysis discusses important topics, including the danger of using historic data as the basis for predicting future breaches, how to use security intelligence as a tool to develop threat forecasting techniques, and how to use threat data visualization techniques and threat simulation tools. Readers will gain valuable security insights into unstructured big data, along with tactics on how to use the data to their advantage to reduce risk.

• Presents case studies and actual data to demonstrate threat data visualization techniques and threat simulation tools
• Explores the usage of kill chain modelling to inform actionable security intelligence
• Demonstrates a methodology that can be used to create a full threat forecast analysis for enterprise networks of any size

1. Navigating Today's Threat Landscape 2. Threat Forecasting 3. Security Intelligence 4. Identifying Knowledge Elements 5. Knowledge Sharing and Community Support 6. Data Visualization 7. Data Simulation 8. Kill Chain Modeling 9. Connecting the Dots 10. The Road Ahead

Discusses the dangers associated with relying on historical data, security incident reports, and network analysis to predict future security breaches

John Pirc has more than 19 years of experience in Security R&D, worldwide security product management, marketing, testing, forensics, consulting, and critical infrastructure architecting and deployment. Additionally, John is an advisor to HP's CISO on Cyber Security and lectured at the US Naval Post Graduate School.

John extensive expertise in the Security field stems from past work experience with the US Intelligence Community, as Chief Technology Officel“I