System Assurance

ForewordPrefaceChapter 1: Why hackers know more about our systems 1.1 Operating in cyberspace involves risks 1.2 Why hackers are repeatedly successful 1.3 What are the challenges in defending cybersystems? 1.3.1 Difficulties in understanding and assessing risks 1.3.2 Complex supply chains 1.3.3 Complex system integrations 1.3.4 Limitations of system assessment practices 1.3.5 Limitations of white-box vulnerability detection 1.3.6 Limitations of black-box vulnerability detection 1.4 Where do we go from here? 1.4.1 Systematic and repeatable defense at affordable cost 1.4.2 The OMG software assurance ecosystem 1.4.3 Linguistic modeling to manage the common vocabulary 1.5 Who should read this book?Chapter 2: Confidence as a product 2.1 Are you confident that there is no black cat in the dark room? 2.2 The nature of assurance 2.2.1 Engineering, risk, and assurance 2.2.2 Assurance case 2.3 Overview of the assurance process 2.3.1 Producing confidence 2.3.2 Economics of confidenceChapter 3: How to build confidence 3.1 Assurance in the system life cycle 3.2 Activities of system assurance process 3.2.1 Project definition 3.2.2 Project preparation 3.2.3 Assurance argument development 3.2.4 Architecture security analysis 3.2.5 Evidence analysis 3.2.6 Assurance case deliveryChapter 4: Knowledge of system as an element of cybersecurity argument 4.1 What is system? 4.2 Boundaries of the system 4.3 Resolution of the system description 4.4 Conceptual commitment for system descriptions 4.5 System architecture 4.6 Example of an architecture framework 4.7 Elements of system 4.8 System knowledge involves multiple viewpoints 4.9 Concept of operations (CONOP) 4.10 Network configuration 4.11 System life cycle and assurance 4.11.1 System life cycle stages 4.11.2 Enabling systems 4.11.3 Supply chain 4.11.4 System life cycle processes 4.11.5 The implications to the common vocabulary and the integrated system modelChapter 5: Knowledge of risk as an element of cybersecurity argument 5.1 Introduction 5.2 Basic cybersecurity elements 5.2.1 Assets 5.2.2 Impact 5.2.3 Threats 5.2.4 Safeguards 5.2.5 Vulnerabillities 5.2.6 Risks 5.3 Common vocabulary for threat identification 5.3.1 Defining discernable vocabulary for Assets 5.3.2 Threats and hazards 5.3.3 Defining discernable vocabulary for injury and impact 5.3.4 Defining discernable vocabulary for threats 5.3.5 Threat scenarios and attacks 5.3.6 Defining discernable vocabulary for vulnerabilities 5.3.7 Defining discernable vocabulary for safeguards 5.3.8 Risk 5.4 Systematic threat identification 5.5 Assurance strategies 5.5.1 Injury argument 5.5.2 Entry point argument 5.5.3 Threat argument 5.5.4 Vulnerability argument 5.5.5 Security requirement argument 5.6 Assurance of the threat identificationChapter 6: Knowledge of vulnerabilities as an element of cybersecurity argument 6.1 Vulnerability as a unit of knowledge 6.1.1 What is vulnerability? 6.1.2 The history of vulnerability as a unit of knowledge 6.1.3 Vulnerabilities and the phases of the system life cycle 6.1.4 Enumeration of vulnerabilities as a Knowledge product 6.2 Vulnerability databases 6.2.1 US-CERT 6.2.2 Open source vulnerability database 6.3 Vulnerability life cycle 6.4 NIST Security content automation protocol (SCAP) ecosystem 6.4.1 Overview of SCAP ecosystem 6.4.2 Information exchanges in SCAP ecosystemChapter 7: Vulnerability patterns as a new assurance content 7.1 Beyond current SCAP ecosystem 7.2 Vendor-neutral vulnerability patterns 7.3 Software fault patterns 7.3.1 Safeguard clusters and corresponding SFPs 7.3.2 Direct injury clusters and corresponding SFPs 7.4 Example software fault patternChapter 8: OMG software assurance ecosystem 8.1 Introduction 8.2 OMG assurance ecosystem: toward collaborative cybersecurityChapter 9: Common fact model for assurance content 9.1 Assurance content 9.2 The objectives 9.3 Design criteria for information exchange protocols 9.4 Trade-offs 9.5 Information exchange protocols 9.6 The nuts and bolts of fact models 9.6.1 Objects 9.6.2 Noun concepts 9.6.3 Facts about existence of objects 9.6.4 Individual concepts 9.6.5 Relations between concepts 9.6.6 Verb concepts 9.6.7 Characteristics 9.6.8 Situational concepts 9.6.9 Viewpoints and views 9.6.10 Information exchanges and assurance 9.6.11 Fact-oriented integration 9.6.12 Automatic derivation of facts 9.7 The representation of facts 9.7.1 Representing facts in XML 9.7.2 Representing facts and schemes in Prolog 9.8 The common schema 9.9 System assurance factsChapter 10: Linguistic models 10.1 Fact models and linguistic models 10.2 Background 10.3 Overview of SBVR 10.4 How to use SBVR 10.4.1 Simple vocabulary 10.4.2 Vocabulary entries 10.4.3 Statements 10.4.4 Statements as formal definitions of new concepts 10.5 SBVR vocabulary for describing elementary meanings 10.6 SBVR vocabulary for describing representations 10.7 SBVR vocabulary for describing extensions 10.8 Reference schemes 10.9 SBVR semantic formulations 10.9.1 Defining new terms and facts types using SBVRChapter 11: Standard protocol for exchanging system facts 11.1 Background 11.2 Organization of the KDM vocabulary 11.2.1 Infrastructure layer 11.2.2 Program elements layer 11.2.3 Resource layer 11.2.4 Abstractions layer 11.3 The process of discovering system facts 11.4 Discovering the baseline system facts 11.4.1 Inventory views 11.4.2 Build views 11.4.3 Data views 11.4.4 UI views 11.4.5 Code views 11.4.6 Platform views 11.4.7 Event views 11.5 Performing architecture analysis 11.5.1 Structure views 11.5.2 Conceptual viewsChapter 12: Case study 12.1 Introduction 12.2 Background 12.3 Concepts of operations 12.3.1 Executive summary 12.3.2 Purpose 12.3.3 Locations 12.3.4 Operational authority 12.3.5 System architecture 12.4 Business vocabulary and security policy for Clicks2Bricks in SBVR 12.5 Building the integrated system model 12.5.1 Building the baseline system model 12.5.2 Enhancing the baseline model with the system architecture facts 12.6 Mapping cybersecurity facts to system facts 12.7 Assurance caseIndex