Human Decision-Making in Computer Security Incident Response Creative Commons License BY-NC 6.2, 423; Version 3.3 DECLARATION
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HUMANDECISION-MAKINGINCOMPUTERSECURITY INCIDENTRESPONSE jonathan michael spring PhD Computer Science Faculty of Engineering University College London (UCL) 423; Supervisors: Prof. David Pym Dr. Phyllis Illari Dr. Emiliano De Cristofaro Jonathan Michael Spring: Human decision-making in computer security incident response Creative Commons license BY-NC 6.2, 423; version 3.3 DECLARATION I, Jonathan Michael Spring, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. London, UK, 423; Jonathan Michael Spring DEDICATION This work is dedicated to my parents, for their continued love and support. 7 ABSTRACT background: Cybersecurity has risen to international importance. Almost every organization will fall victim to a successful cyberat- tack. Yet, guidance for computer security incident response ana- lysts is inadequate. research questions: What heuristics should an incident analyst use to construct general knowledge and analyse attacks? Can we construct formal tools to enable automated decision support for the analyst with such heuristics and knowledge? method: We take an interdisciplinary approach. To answer the first question, we use the research tradition of philosophy of science, specifically the study of mechanisms. To answer the question on formal tools, we use the research tradition of program verification and logic, specifically Separation Logic. results: We identify several heuristics from biological sciences that cybersecurity researchers have re-invented to varying degrees. We consolidate the new mechanisms literature to yield heuristics re- lated to the fact that knowledge is of clusters of multi-field mech- anism schema on four dimensions. General knowledge structures such as the intrusion kill chain provide context and provide hy- potheses for filling in details. The philosophical analysis answers this research question, and also provides constraints on building the logic. Finally, we succeed in defining an incident analysis logic resembling Separation Logic and translating the kill chain into it as a proof of concept. conclusion: These results benefits incident analysis, enabling it to expand from a tradecraft or art to also integrate science. Future research might realize our logic into automated decision-support. Additionally, we have opened the field of cybersecuity to collab- oration with philosophers of science and logicians. 9 IMPACTSTATEMENT The potential impact of this thesis is both within and outside the academy. Improvements to the practice of incident response will take some significant effort to transition, not least because the attention of such personnel is a scarce resource. The learning curve on scientific know- ledge generation heuristics is steep. Nonetheless, I will provide two spe- cific improvements that can impact incident response and Computer Network Defense (CND): • robust knowledge creation and structured-observation design heuristics; • a logical language to communicate reasoning steps without reveal- ing sensitive data. The thesis should enable further work within the academy. This thesis will, in some ways, chart out new fields of philosophy of cybersec- urity in general and of computer security incident response in particular. Furthermore, this thesis will sensitize the fields of logic and philosophy of science to cybersecurity. The three research or development areas that appear most fruitful going forwards are: automated decision sup- port for incident response; meta-logical analysis of the properties of the logic defined; and extension of the account of explanation and mechan- ism discovery both into cybersecurity and back into the philosophical literature on scientific explanation generally. The third area for impact will be in how we train new incident ana- lysts. There are at least three areas in which this impact might be real- ized. First, standards bodies could work to fill the gap Chapter 4 will identify in existing standards. Second, both Chapter 5 and Chapter 6 will identify likely challenges; future work on pedagogy could focus on how to best enable analysts to overcome them. Chapter 6, Chapter 7, and Chapter 9 will offer qualitative progress on some norms and ex- pectations for analytic steps, but integrating these ideas into training and measuring results is future work. In all three of these areas – practice, academics, and pedagogy – in order to bring about impact the work will need to be disseminated, in- tegrated into education, and potentially engage public policy makers or business leaders about integrating these changes into the way computer- security incidents are handled. ; CONTENTS 3 introduction and motivation 45 3.3 Summary of the argument 45 3.4 Impact 46 3.5 Important definitions 47 3.6 Publications and submissions adapted for thesis 48 3.7 Publications not adapted in thesis 49 3.8 Disclaimer 4; i background 4 literature review – incident response 55 4.3 Introduction 55 4.4 Scope 57 4.4.3 Scope—Topic 58 4.4.4 Scope—Publication Venues 5: 4.5 Related literature reviews 65 4.6 Methods 69 4.6.3 Search strategy 69 4.6.4 Appraisal strategy 6: 4.6.5 Synthesis methods 6; 4.6.6 Limitations 74 4.7 Results 76 4.7.3 IETF 77 4.7.4 ISO 78 4.7.5 FIRST 78 4.7.6 Intelligence community 7; 4.7.7 Referenced Documents 82 4.8 Discussion 93 4.8.3 Comments and clarifications on Table 4.34 98 4.8.4 Note on case studies :5 4.9 Gaps and Work Plan :6 4.9.3 Research question :6 4.: Related work :7 4.:.3 Interdisciplinary overlaps :8 4.:.4 Parts of information and computer science :; 4.; Conclusion ;4 5 literature review – science and security ;7 5.3 Purported impediments to a science of security ;8 5.4 Philosophy of science – historical background ;9 5.5 Existing statements of science and security 322 5.5.3 Prepositions: ‘of’ or ‘for’ security 333 5.6 Practicing Science of Security 334 5.6.3 Scientific methods 336 5.6.4 Evaluating Results 342 5.6.5 The nature of scientific inquiry 348 5.6.6 Scientific Language(s) 352 33 34 contents 5.6.7 Engineering or Science? 355 5.7 A Science of Security very much exists 357 5.8 Research plan 359 ii generalising, applying, and formalising know- ledge 6 general knowledge of mechanisms 363 6.3 Introduction 364 6.4 Generality in philosophy of science 367 6.4.3 Turning away from laws 367 6.4.4 Generality and mechanisms 369 6.5 Building mechanistic knowledge in cybersecurity 374 6.5.3 The three challenges for cybersecurity 375 6.5.4 Three examples of cybersecurity mechanisms 37: 6.6 Building general knowledge in cybersecurity 38: 6.6.3 Constraining: On improving coordination in cy- bersecurity 395 6.7 Conclusion 398 7 the intrusion kill chain as a case study 3:3 7.3 Introduction 3:3 7.4 Reasoning with the kill chain as a mechanism 3:6 7.4.3 Higher-level mechanisms 3;2 7.4.4 On lower-level mechanisms 3;4 7.5 Examples of Incident Analysis 3;6 7.5.3 Example 3: The Cuckoo’s Egg 3;7 7.5.4 Example 4: Airport Security 422 7.6 Conclusions 426 8 separation logic as a case study 429 8.3 Introduction to Separation Logic 429 8.4 Solving a Hard Problem 434 8.5 Why Separation Logic Works 439 8.5.3 The separating conjunction 43; 8.5.4 Hoare triples 442 8.5.5 Frame Rule 443 8.5.6 Automatable abduction 444 8.6 The Semantics of Separation Logic 445 8.6.3 Bunched Logic 446 8.6.4 The Semantics of Bunched Logic 447 8.6.5 The Resource Semantics of Separation Lo- gic 44; 8.7 Deployable Proof Theory for Separation Logic 455 8.7.3 Separation Logic and the Frame Rule 456 8.7.4 Deployability via Contextual Refinement 457 8.7.5 Bi-abduction 458 8.8 Conclusion 465 iii a logic of reasoning in incident analysis 9 logic definition 46; 9.3 Philosophical and historical analyses 46; contents 35 9.3.3 Summary of requirements 474 9.4 Logic design choices 475 9.5 Logic Definitions 477 9.5.3 Expressions 478 9.5.4 Basics and syntax 479 9.5.5 Model 47; 9.5.6 Semantics 484 9.5.7 Abduction 486 9.5.8 On the metatheory of the security incident ana- lysis logic 487 9.6 A worked example 488 9.6.3 A logic of the kill chain 492 9.6.4 Using more granular knowledge 495 9.6.5 Composition of attacks into a campaign 497 9.7 Benefits of this logic 49; 9.8 Conclusions 4:2 iv consolidation : summary 4:5 ; conclusions 4:7 v backmatter bibliography 4;5 LISTOFFIGURES Figure 5.3 The mathematical modeling cycle 342 Figure 6.3 GameOver Zeus botnet mechanism 37; Figure 6.4 Simple kill-chain diagram 385 Figure 7.3 Improved kill chain mechanism 3:7 Figure 7.4 Mechanistic translation of common language for computer security incidents 3;2 Figure 7.5 Mechanistic translation of a drive-by down- load 3;5 Figure 7.6 Model of accounting systems generated by Stoll during incident analysis 3;9 Figure 7.7 Representation of game-theoretic model as a mechanism 423 Figure 8.3 Anatomy of a pointer 436 Figure 8.4 Example pointer error – memory leaks 437 Figure 8.5 Pointers forming a linked list 452 Figure 8.6 Satisfaction relation for BI pointer logic 453 LISTOFTABLES Table 4.3 Results of ACM CSUR search for extant literat- ure reviews 67 Table 4.4 All documents found to be relevant through the search methodology 76 Table 4.5 IETF database search results 77 Table 4.6 ISO database search results 79 Table 4.7 Summary of results found through FIRST 7: Table 4.8 intelligence community search results 82 Table 4.9 Data formats cited by IETF standards 84 Table 4.: ISO database search results 87 Table 4.; Publications referenced by NIST SP:22-83 89 Table 4.32 Documents referenced by CERT/CC sources 8; Table 4.33 Resources referenced by intelligence community