Runtime monitoring is commonly used to detect the violation of desired properties in safety critical cyber-physical systems by observing its executions. Bauer et al. introduced an influential framework for monitoring Linear Temporal Logic (LTL) properties based on a three-valued semantics for a finite execution: the formula is already satisfied by the given execution, it is already violated, or it is still undetermined, i.e., it can still be satisfied and violated by appropriate extensions of the given execution. However, a wide range of formulas are not monitorable under this approach, meaning that there are executions for which satisfaction and violation will always remain undetermined no matter how it is extended. In particular, Bauer et al. report that 44% of the formulas they consider in their experiments fall into this category. Recently, a robust semantics for LTL was introduced to capture different degrees by which a property can be violated. In this paper we introduce a robust semantics for finite strings and show its potential in monitoring: every formula considered by Bauer et al. is monitorable under our approach. Furthermore, we discuss which properties that come naturally in LTL monitoring—such as the realizability of all truth values—can be transferred to the robust setting. We show that LTL formulas with robust semantics can be monitored by deterministic automata, and provide tight bounds on the size of the constructed automaton. Lastly, we report on a prototype implementation and compare it to the LTL monitor of Bauer et al. on a sample of examples.
- Award ID(s):
- 2102106
- NSF-PAR ID:
- 10467381
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- Journal of the ACM
- Volume:
- 69
- Issue:
- 5
- ISSN:
- 0004-5411
- Page Range / eLocation ID:
- 1 to 31
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract -
null (Ed.)Runtime monitoring is commonly used to detect the violation of desired properties in safety critical cyber-physical systems by observing its executions. Bauer et al. introduced an influential framework for monitoring Linear Temporal Logic (LTL) properties based on a three-valued semantics: the formula is already satisfied by the given prefix, it is already violated, or it is still undetermined, i.e., it can still be satisfied and violated by appropriate extensions. However, a wide range of formulas are not monitorable under this approach, meaning that they have a prefix for which satisfaction and violation will always remain undetermined no matter how it is extended. In particular, Bauer et al. report that 44% of the formulas they consider in their experiments fall into this category. Recently, a robust semantics for LTL was introduced to capture different degrees by which a property can be violated. In this paper we introduce a robust semantics for finite strings and show its potential in monitoring: every formula considered by Bauer et al. is monitorable under our approach. Furthermore, we discuss which properties that come naturally in LTL monitoring — such as the realizability of all truth values — can be transferred to the robust setting. Lastly, we show that LTL formulas with robust semantics can be monitored by deterministic automata and report on a prototype implementation.more » « less
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null (Ed.)Robust Linear Temporal Logic (rLTL) was crafted to incorporate the notion of robustness into Linear-time Temporal Logic (LTL) specifications. Technically, robustness was formalized in the logic rLTL via 5 different truth values and it led to an increase in the time complexity of the associated model checking problem. In general, model checking an rLTL formula relies on constructing a generalized Büchi automaton of size 5^|φ| where |φ| denotes the length of an rLTL formula φ. It was recently shown that the size of this automaton can be reduced to 3^|φ| (and even smaller) when the formulas to be model checked come from a fragment of rLTL. In this paper, we introduce Evrostos, the first tool for model checking formulas in this fragment. We also present several empirical studies, based on models and LTL formulas reported in the literature, confirming that rLTL model checking for the aforementioned fragment incurs in a time overhead that makes the verification of rLTL practical.more » « less
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Bogomolov, Sergiy ; Parker, David (Ed.)Resiliency is the ability to quickly recover from a violation and avoid future violations for as long as possible. Such a property is of fundamental importance for Cyber-Physical Systems (CPS), and yet, to date, there is no widely agreed-upon formal treatment of CPS resiliency. We present an STL-based framework for reasoning about resiliency in CPS in which resiliency has a syntactic characterization in the form of an STL-based Resiliency Specification (SRS). Given an arbitrary STL formula φ, time bounds α and β, the SRS of φ, Rα,β (φ), is the STL formula ¬φU[0,α]G[0,β)φ, specifying that recovery from a violation of φ occur within time α (recoverability), and subsequently that φ be maintained for duration β (durability). These R-expressions, which are atoms in our SRS logic, can be combined using STL operators, allowing one to express composite resiliency specifications, e.g., multiple SRSs must hold simultaneously, or the system must eventually be resilient. We define a quantitative semantics for SRSs in the form of a Resilience Satisfaction Value (ReSV) function r and prove its soundness and completeness w.r.t. STL’s Boolean semantics. The r-value for Rα,β (φ) atoms is a singleton set containing a pair quantifying recoverability and durability. The r-value for a composite SRS formula results in a set of non-dominated recoverability-durability pairs, given that the ReSVs of subformulas might not be directly comparable (e.g., one subformula has superior durability but worse recoverability than another). To the best of our knowledge, this is the first multi-dimensional quantitative semantics for an STL-based logic. Two case studies demonstrate the practical utility of our approach. https://doi.org/10.1007/978-3-031-15839-1_7more » « less
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Abstract Runtime verification is a complementary approach to testing, model checking and other static verification techniques to verify software properties. Monitorability characterizes what can be verified (monitored) at run time. Different definitions of monitorability have been given both for trace properties and for hyperproperties (properties defined over sets of traces), but these definitions usually cover only some aspects of what is important when characterizing the notion of monitorability. The first contribution of this paper is a refinement of classic notions of monitorability both for trace properties and hyperproperties, taking into account, among other things, the computability of the monitor. A second contribution of our work is to show that black-box monitoring of HyperLTL (a logic for hyperproperties) is in general unfeasible, and to suggest a gray-box approach in which we combine static and runtime verification. The main idea is to call a static verifier as an oracle at run time allowing, in some cases, to give a final verdict for properties that are considered to be non-monitorable under a black-box approach. Our third contribution is the instantiation of this solution to a privacy property called distributed data minimization which cannot be verified using black-box runtime verification. We use an SMT-based static verifier as an oracle at run time. We have implemented our gray-box approach for monitoring data minimization into the proof-of-concept tool Minion . We describe the tool and apply it to a few case studies to show its feasibility.more » « less
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3550483
