An overview of the MOP runtime verification framework

Meredith, Patrick; Jin, Dong; Griffith, Dennis; Chen, Feng; Roşu, Grigore

doi:10.1007/s10009-011-0198-6

Cited by 198 publications

(169 citation statements)

References 37 publications

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“…Runtime verification and monitoring for finite state discrete systems has received significant attention (e. g., [9,16,23]). Other approaches monitor continuous-time signals (e. g., [11,28]).…”

Section: Related Workmentioning

confidence: 99%

ModelPlex: verified runtime validation of verified cyber-physical system models

Mitsch

Platzer

2016

Form Methods Syst Des

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Formal verification and validation play a crucial role in making cyber-physical systems (CPS) safe. Formal methods make strong guarantees about the system behavior if accurate models of the system can be obtained, including models of the controller and of the physical dynamics. In CPS, models are essential; but any model we could possibly build necessarily deviates from the real world. If the real system fits to the model, its behavior is guaranteed to satisfy the correctness properties verified with respect to the model. Otherwise, all bets are off. This article introduces ModelPlex, a method ensuring that verification results about models apply to CPS implementations. ModelPlex provides correctness guarantees for CPS executions at runtime: it combines offline verification of CPS models with runtime validation of system executions for compliance with the model. ModelPlex ensures in a provably correct way that the verification results obtained for the model apply to the actual system runs by monitoring the behavior of the world for compliance with the model. If, at some point, the observed behavior no longer complies with the model so that offline verification results no longer apply, ModelPlex initiates provably safe fallback actions, assuming the system dynamics deviation is bounded. This article, furthermore, develops a systematic technique to synthesize provably correct monitors automatically from CPS proofs in differential dynamic logic by a correct-by-construction approach, leading to verifiably correct runtime model validation. Overall, ModelPlex generates provably correct monitor conditions that, if checked to hold at runtime, are provably guaranteed to imply that the offline safety verification results about the CPS model apply to the present run of the actual CPS implementation.

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Section: Related Workmentioning

confidence: 99%

ModelPlex: verified runtime validation of verified cyber-physical system models

Mitsch

Platzer

2016

Form Methods Syst Des

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“…BusMOP [30,35] uses a non-intrusive approach for runtime monitoring similar to R2U2 by means of passive instrumentation on a communication bus. The tool can automatically generate monitors that are executed on an FPGA, thereby achieving zero runtime overhead.…”

Section: Related Workmentioning

confidence: 99%

R2U2: monitoring and diagnosis of security threats for unmanned aerial systems

Moosbrugger

Rozier

Schumann

2017

Form Methods Syst Des

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We present R2U2, a novel framework for runtime monitoring of security properties and diagnosing of security threats on-board Unmanned Aerial Systems (UAS). R2U2, implemented in FPGA hardware, is a real-time, Realizable, Responsive, Unobtrusive Unit for runtime system analysis, now including security threat detection. R2U2 is designed to continuously monitor inputs from on-board components such as the GPS, the ground control station, other sensor readings, actuator outputs, and flight software status. By simultaneously monitoring and performing statistical reasoning, attack patterns and post-attack discrepancies in the UAS behavior can be detected. R2U2 uses runtime observer pairs for Linear and Metric Temporal Logics for property monitoring and Bayesian networks for diagnosis of system health during runtime. We discuss the design and implementation that now enables R2U2 to handle security threats and present simulation results of several attack scenarios on the NASA DragonEye UAS.

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“…The key problem in evaluating a set of monitors given an incoming event is to perform efficient matching of the event (and possibly other facts depending on the logic) against conditions in monitors. This becomes particularly challenging when events carry data parameters, as also heavily studied in state of the art systems [1,11]. We are investigating the combination of expressiveness and efficiency, with focus on expressiveness, as documented in [2].…”

Section: Future Workmentioning

confidence: 99%

Requirements-Driven Log Analysis (Extended Abstract)

Havelund

2012

Testing Software and Systems

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Imagine that you are tasked to help a project improve their testing effort. In a realistic scenario it will quickly become clear, that having an impact is difficult. First of all, it will likely be a challenge to suggest an alternative approach which is significantly more automated and/or more effective than current practice. The reality is that an average software system has a complex input/output behavior. An automated testing approach will have to auto-generate test cases, each being a pair (i, o) consisting of a test input i and an oracle o. The test input i has to be somewhat meaningful, and the oracle o can be very complicated to compute. Second, even in the case where some testing technology has been developed that might improve current practice, it is then likely difficult to completely change the current behavior of the testing team unless the technique is obviously superior and does everything already done by existing technology.So is there an easier way to incorporate formal methods-based approaches than the full fledged test revolution? Fortunately the answer is affirmative. A relatively simple approach is to benefit from possibly already existing logging infrastructure, which after all is part of most systems put in production. A log is a sequence of events, generated by special log recording statements, most often manually inserted in the code by the programmers. An event can be considered as a data record: a mapping from field names to values. We can analyze such a log using formal methods, for example checking it against a formal specification. This separates running the system from analyzing its behavior. It is not meant as an alternative to testing since it does not address the important input generation problem. However, it offers a solution which testing teams might accept since it has low impact on the existing process. A single person might be assigned to perform such log analysis, compared to the entire testing team changing behavior.Note that although logging often is manually programmed, it can be performed using automated code instrumentation, using for example aspect-oriented programming. The point here, however, is that manual logging is often already

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An overview of the MOP runtime verification framework

Cited by 198 publications

References 37 publications

ModelPlex: verified runtime validation of verified cyber-physical system models

ModelPlex: verified runtime validation of verified cyber-physical system models

R2U2: monitoring and diagnosis of security threats for unmanned aerial systems

Requirements-Driven Log Analysis (Extended Abstract)

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