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Threat Forecasting
Leveraging Big Data for Predictive Analysis

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

John Pirc (Author), David DeSanto (Author), Iain Davison (Author), Will Gragido (Author)

9780128000069, Elsevier Science

Paperback, published 17 May 2016

188 pages
23.5 x 19 x 1.3 cm, 0.43 kg

"The authors have rooted this text in real-world implementations and approaches, but with enough of a grounding in the concepts that what you learn here will remain relevant as, inevitably, the nature of the threats we face, and of the kinds of threat forecasting that emerge to tackle them, continue to evolve." --Network Security

"If you’re looking for a book to give a solid overview of what threat forecasting can do for your organization, you don’t have to look further. It’s concise and coherent, provides great real-world examples, is short enough to read in one or two sittings, and provides good advice on getting colleagues and management to support the effort..." --Help Net Security

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.

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

Subject Areas: Computer security [UR], Management of specific areas [KJMV]

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