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Home > Computing and Information Technology > Computer security > Information Security Analytics: Finding Security Insights, Patterns, and Anomalies in Big Data
Information Security Analytics: Finding Security Insights, Patterns, and Anomalies in Big Data

Information Security Analytics: Finding Security Insights, Patterns, and Anomalies in Big Data


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About the Book

Information Security Analytics gives you insights into the practice of analytics and, more importantly, how you can utilize analytic techniques to identify trends and outliers that may not be possible to identify using traditional security analysis techniques. Information Security Analytics dispels the myth that analytics within the information security domain is limited to just security incident and event management systems and basic network analysis. Analytic techniques can help you mine data and identify patterns and relationships in any form of security data. Using the techniques covered in this book, you will be able to gain security insights into unstructured big data of any type. The authors of Information Security Analytics bring a wealth of analytics experience to demonstrate practical, hands-on techniques through case studies and using freely-available tools that will allow you to find anomalies and outliers by combining disparate data sets. They also teach you everything you need to know about threat simulation techniques and how to use analytics as a powerful decision-making tool to assess security control and process requirements within your organization. Ultimately, you will learn how to use these simulation techniques to help predict and profile potential risks to your organization. Written by security practitioners, for security practitioners Real-world case studies and scenarios are provided for each analytics technique Learn about open-source analytics and statistical packages, tools, and applications Step-by-step guidance on how to use analytics tools and how they map to the techniques and scenarios provided Learn how to design and utilize simulations for "what-if" scenarios to simulate security events and processes Learn how to utilize big data techniques to assist in incident response and intrusion analysis

About the Author :
Mark Ryan Talabis is the Chief Threat Scientist of Zvelo Inc. Previously he was the Director of the Cloud Business Unit of FireEye Inc. He was also the Lead Researcher and VP of Secure DNA and was an Information Technology Consultant for the Office of Regional Economic Integration (OREI) of the Asian Development Bank (ADB). ? He is co-author of the book "Information Security Risk Assessment Toolkit: Practical Assessments through Data Collection and Data Analysis" from Syngress. He has presented in various security and academic conferences and organizations around the world including Blackhat, Defcon, Shakacon, INFORMS, INFRAGARD, ISSA, and ISACA. He has a number of published papers to his name in various peer-reviewed journals and is also an alumni member of the Honeynet Project. He has a Master of Liberal Arts Degree (ALM) in Information Technology from Harvard University and a Master of Science (MS) degree in Information Technology from Ateneo de Manila University. He holds several certifications including a Certified Information Systems Security Professional (CISSP); Certified Information Systems Auditor (CISA); and Certified in Risk and Information Systems Control (CRISC). Robert McPherson leads a team of data scientists for a Fortune 100 Insurance and Financial Service company in the US. He has 13 years of experience as a leader of research and analytics teams, specializing in predictive modeling, simulations, econometric analysis, and applied statistics. Bob works with a team of researchers who utilize simulation and big data methods to model the impact of catastrophes on millions of insurance policies...simulating up to 100,000 years of hurricanes, earthquakes, and wildfires, as well as severe winter and summer storms, on more than two trillion dollars worth of insured property value. He has used predictive modeling and advanced statistical methods to develop automated outlier detection methods, build automated underwriting models, perform product and customer segmentation analysis, and design competitor war game simulations. I. Miyamoto is a computer investigator with a government agency. She has over 15 years of computer investigative and computer forensics experience and over 12 years intelligence analysis experience. She holds the following degrees: B.S. Software Engineering, B.A. in Japanese Language, M.A. in National Security and Strategic Studies, M.S. in Strategic Intelligence, M.A. in Management, M.Ed. in Special Education and Ed.D. in Education. Jason Martin is Vice President of Cloud Business for FireEye, Inc. the global leader in advanced threat detection technology. Prior to joining FireEye Jason was the President and CEO of Secure DNA (acquired by FireEye), a company that provided innovative security products and solutions to companies throughout Asia-Pacific and the US Mainland. Customers included Fortune 1000 companies, global government agencies, state and local governments, and private organizations of all sizes. Mr. Martin has over fifteen years of experience in Information Security, is a published author and speaker, and is the co-founder of the Shakacon Security Conference.

Review :
"a good how-to guide with plenty of coding examples, to show the reader how to effectively use the tools to make sense of the data they have....the gold-standard on the topic."--RSAConference.com, Information Security Analytics


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Product Details
  • ISBN-13: 9780128005064
  • Publisher: Syngress Media,U.S.
  • Publisher Imprint: Syngress Media,U.S.
  • Language: English
  • Sub Title: Finding Security Insights, Patterns, and Anomalies in Big Data
  • ISBN-10: 0128005068
  • Publisher Date: 25 Nov 2014
  • Binding: Digital (delivered electronically)
  • No of Pages: 182


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