D.3.3 ALGORITHMS FOR INCREMENTAL ... - SecureChange

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6.2 Application to the ATM case study Since [4] used a different case study, we now illustrate briefly how the inductive approach can be used in the ATM case study, in particular the introduction of the AMAN. We consider the starting situation where System Engineer has delegated permission on the CWP including Flight Data and State Flight Info, but its tasks or goals use only the CWP software part (see the left side of the figure below). In order to fulfil the least privilege principle, a change reaction might perform a modification of permissions to delegate only the required parts of CWP. Figure 13. ATM model state before quick fix application The goal of the quick fix generation in this case is to check that an actor has been delegated the permission to data only if it is used in at least one of its tasks or goals. The exploration would apply change operations for removing and creating delegation relations until there is no violating delegation. An example generated inductive rule is the following: quick fix rule correctLeastPriviligeViolationOnData(D,RDd,A) { precondition leastPriviligeViolationOnData(D,RDd,A); action { call substituteDataPriviligeToParts(D,RDd,A); call removeUnusedDataPriviligeOnActor(A);} <strong>D.3.3</strong> Algorithms for Incremental Requirements Models Evaluation and Transformation| version 1.19 | page 30/136
Figure 14. ATM model state after quick fix application A possible solution model is demonstrated on the Figure 14. Once either the engineer or the exploration found the complex change reaction that corrects the least privilege violation, the framework can store it for future use. In this case, the precondition of the reaction is the goal, and the signature is the violation. The included simple operations replace the single delegation of permission with similar relations on the subparts, and finally remove the relations that are not needed since the data is not used. <strong>D.3.3</strong> Algorithms for Incremental Requirements Models Evaluation and Transformation| version 1.19 | page 31/136
Page 1 and 2: D.3.3 ALGORITHMS FOR INCREMENTAL RE
Page 3 and 4: 1.14 19 January Final 1.15 23 Janua
Page 5 and 6: Index DOCUMENT INFORMATION 1 DOCUME
Page 7 and 8: 1 Introduction This deliverable pre
Page 9 and 10: (Clause 6.4.3) processes of ISO/IEC
Page 11 and 12: 3 Orchestrating Requirements and Ri
Page 13 and 14: grey. The ADS-B introduction requir
Page 15 and 16: The security risk manager identifie
Page 17 and 18: are supported by the argumentation
Page 19 and 20: ADS-B Manage ADS-B signal ADS-B sig
Page 21 and 22: the stagnation suite (i.e. obsolete
Page 23 and 24: 5 A framework for modeling and reas
Page 25 and 26: sectors. And there is 42% of probab
Page 27 and 28: SDA(C) = {DA 2 , DA 4 , DA 8 , DA 1
Page 29: application contexts is saved if th
Page 33 and 34: References [1] Yudis Asnar, Fabio M
Page 35 and 36: Managing Changes with Legacy Securi
Page 37 and 38: Failure in the provisioning of corr
Page 39 and 40: propagated to the system designer a
Page 41 and 42: APPENDIX B D.3.3 Algorithms for Inc
Page 43 and 44: is sometimes difficult, especially
Page 45 and 46: Tactical Monitor air R controller t
Page 47 and 48: protected from harm. Since in CORAS
Page 49 and 50: CModel. The postcondtion checks the
Page 51 and 52: of ADS-B signal and Availability of
Page 53 and 54: extensions to i* to model and analy
Page 55 and 56: 3. Bzivin, J., Dup, G., Jouault, F.
Page 57 and 58: APPENDIX C D.3.3 Algorithms for Inc
Page 59 and 60: steps. Section V demonstrates the R
Page 61 and 62: that should be mitigated by the sys
Page 63 and 64: CPU value PINconfirmed(PIN, card-de
Page 65 and 66: TABLE IV PRIORITIZATION OF RISKS FO
Page 67 and 68: context. We believe that the Common
Page 69 and 70: Managing Evolution by Orchestrating
Page 71 and 72: 1.1 The Contribution of this Paper
Page 73 and 74: Fig. 3. Integrated Change Managemen
Page 75 and 76: The requirement analysis is an iter
Page 77 and 78: Table 1. Conceptual Interface Requi
Page 79 and 80: Legend: Goals surrounded by dashed
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Table 5. Test Suite for GP-2.2 Tran
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6. P. K. Chittimalli and M. J. Harr
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Noname manuscript No. (will be inse
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Dealing with Known Unknowns: A Goal
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Understanding How to Manage Require
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Chatzoglou et al. [4] conducted a s
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Evolution Elicitation Probability E
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Table 2. Participants Background Pa
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for the defined success criteria. O
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Fig. 3. Codes Coverage ATM systems,
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The feedbacks provided by the ATM e
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3. P. Carlshamre, K. Sandahl, M. Li
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Quick fix generation for DSMLs Ábe
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• extensibility: the supported li
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Fig. 7. Overview of the Quick fix g
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Fig. 9. Evaluation results (|V(M I
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