Threat forecasting leveraging big data for predictive analysis

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 securi...

Descripción completa

Detalles Bibliográficos
Otros Autores: Pirc, John, author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Cambridge, MA : Syngress [2016]
Edición:First edition
Colección:Gale eBooks
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630335806719
Tabla de Contenidos:
  • Front Cover; Threat Forecasting: Leveraging Big Data for Predictive Analysis; Copyright; Contents; About the Authors; Foreword; Why Threat Forecasting is Relevant; What You Will Learn and How You Will Benefit; Preface; Book Organization and Structure; Closing Thoughts; Acknowledgments; Chapter 1: Navigating Todays Threat Landscape; Introduction; Why Threat Forecasting; The Effects of a Data Breach; Barriers to Adopting Threat Forecasting Practices; Going Beyond Historical Threat Reporting; Timing; Generalization; The State of Regulatory Compliance; Industry Specific Guidelines
  • Healthcare InstitutionsFinancial Institutions; Cyber Security Information Sharing Legislation: Watch this Space; Best Practices, Standards, and Frameworks; PCI DSS; NIST Cyber Security Framework; Defense in Depth; Tier 1 Security Technologies; Tier 2 Security Technologies; Update and Evaluate Security Products and Technologies; Cyber Security and the Human Factor; Today's Information Assurance Needs; Chapter 2: Threat Forecasting; Synopsis; Introduction; Threat Forecasting; Dangers of Technology Sprawl; High Speed Big Data Collection and Surveillance; Threat Epidemiology
  • High Frequency Security AlgorithmsSummary; Chapter 3: Security Intelligence; Synopsis; Introduction; Security Intelligence; Information Vetting; KPIs; Programs; Scripts; Shortcuts; Other; Office Macros; Do It Yourself (DIY) Security Intelligence; Build; Buy; Partner; Key Indicator Attributes; Dissemination of Intelligence; Summary; Chapter 4: Identifying Knowledge Elements; Synopsis; Introduction; Defining Knowledge Elements; Intelligence Versus Information; A Quick Note About the Signal-to-Noise Ratio Metaphor; A Brief Note on IOCs and IOIs
  • Identifying Something Important Through the Use of IOAs, IOCs, and IOIsTypes of Knowledge Elements; IOA or Pre-attack Indicators; Indicators of Compromise; Indicators of Interest; Publicly Defined Knowledge Elements; OpenIOC; How It Works; How Do You Get It; Incident Object Description Exchange Format (RFC5070); IODEF Data Model; IODEF Implementation; IOCBucket.com; Cyber Observable eXpression; Summary; Chapter 5: Knowledge Sharing and Community Support; Synopsis; Introduction; Sharing Knowledge Elements; Advantages; Disadvantages; Community Sharing; VERIS; OpenIOC; TAXII; STIX; CybOX
  • Commercial OfferingsStaying Ahead of the Adversary; Summary; Chapter 6: Data Visualization; Synopsis; Introduction; Common Methods; Big Data Analytics; Interactive Visualization; Not Just For the Boardroom; Summary; Chapter 7: Data Simulation; Synopsis; Introduction; Traffic Simulation vs Emulation; Environmental; Flow; Data Sandboxes; Analytic Engines; Quantum Computing; Summary; Chapter 8: Kill Chain Modeling; Synopsis; Introduction; Key Components of Kill Chain Modeling; Leveraging Big Data; Tools Available; Maltego; Splunk; OpenGraphiti; Creation of Data Files; STIX; Kill Chains in STIX
  • Defining A Kill Chain