Publication | Open Access
Can you Trust your Data?
26
Citations
8
References
1995
Year
Program CheckingEngineeringData TrustInformation SecuritySoftware SystemsVerificationInformation ForensicsSoftware EngineeringSoftware AnalysisFormal VerificationData ScienceStatic CheckingCompilersProgram DerivationData ManagementStatisticsProgramming LanguagesNew Program AnalysisAbstract InterpretationData PrivacyTrustComputer ScienceStatic Program AnalysisData SecurityAutomated ReasoningProgram AnalysisTrust PrivacyFormal MethodsData RiskAbstract Interpretation Framework
A new program analysis is presented, and two compile time methods for this analysis are given. The analysis attempts to answer the question: “Given some trustworthy and some untrustworthy input, can we trust the value of a given variable after execution of some code”. The analyses are based on an abstract interpretation framework and a constraint generation<br />framework, respectively. The analyses are proved safe with respect to an instrumented semantics. We explicitly deal with a language with pointers and possible aliasing problems.<br />The constraint based analysis is related directly to the abstract interpretation and therefore indirectly to the instrumented semantics.
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