Threat Forecasting: Leveraging Big Data For Predictive Analysis

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. 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. Drawing upon years of practical experience and using numerous examples and illustrative case studies, the book 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. In addition, a proven methodology that can be used to create a full threat forecast analysis for any size enterprise network is included. Discusses the danger of using historic data as the basis for predicting future breaches Explains how to use security intelligence as a tool to develop threat forecasting techniques Presents case studies and actual data to demonstrate threat data visualization techniques and threat simulation tools Explores the usage of kill chain modeling to inform actionable security intelligence Presents a methodology that can be used to create a full threat forecast analysis for any size enterprise network

• | Author: John Pirc, David DeSanto
• | Publisher: Syngress
• | Publication Date: May 17, 2016
• | Number of Pages: 400 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 0128000066
• | ISBN-13: 9780128000069