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Runtime monitoring and verification of systems with hidden information

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Abstract

This paper describes a technique for runtime monitoring (RM) and runtime verification (RV) of systems with invisible events and data artifacts. Our approach combines well-known hidden markov model (HMM) techniques for learning and subsequent identification of hidden artifacts, with runtime monitoring of probabilistic formal specifications. The proposed approach entails a process in which the end-user first develops and validates deterministic formal specification assertions, s/he then identifies hidden artifacts in those assertions. Those artifacts induce the state set of the identifying HMM. HMM parameters are learned using standard frequency analysis techniques. In the verification or monitoring phase, the system emits visible events and data symbols, used by the HMM to deduce invisible events and data symbols, and sequences thereof; both types of symbols are then used by a probabilistic formal specification assertion to monitor or verify the system.

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Notes

  1. Further details about validation testing are available in [3].

  2. We assume that frequencies above 5 cars/sec are measured as 5 cars/s.

  3. All three tables with HMM probabilities of observations are provided as examples only. They are not results of an experiment. The probabilities of the scenario of Fig. 9a are calculated based on these probability distributions.

  4. More accurately, PS(Con) is an extended state vector that includes the state variable and the states of all local variables, such as the timer state and the bSuccess flag.

  5. Although all PODs are normalized (e.g., \(\sum _{1 \le i \le N} \alpha 't(i) = 1\), for all \(t\)), its possible that the POD in one or more states scales down geometrically with t.

References

  1. Davies KH, Biddulph R, Balashek S (1952) Automatic speech recognition of spoken digits. J Acoust Soc Am 24(6):637–642

    Article  Google Scholar 

  2. Drusinsky D (2006) Modeling and verification using UML statecharts—a working guide to reactive system design. Runtime monitoring and execution-based model checking. Elsevier, Amsterdam

    Google Scholar 

  3. Drusinsky D (2011) Practical UML-based specification, validation, and verification of mission-critical software. DogEar Publishing, Michigan

  4. Drusinsky D (2000) The temporal rover and the ATG rover. In: Proceedings of SPIN 2000 workshop. LNCS, vol 1885. Springer, Berlin, pp 323–329

  5. Drusinsky D (2012) Behavioral and temporal pattern detection within financial data with hidden information. J Univers Comput Sci 18(14):1950–1966

    Google Scholar 

  6. Drusinsky D, Michael JB, Shing M (Dec. 2008) A visual tradeoff space for formal verification and validation techniques. IEEE Syst J 2(4):513–519

  7. Drusinsky D, Michael B, Otani T, Shing M (2008) Validating UML statechart-based assertions libraries for improved reliability and assurance. In: Proceedings of the second international conference on secure system integration and reliability improvement (SSIRI 2008), Yokohama, Japan, 14–17 July 2008, pp 47–51. Best paper award

  8. Drusinsky D, Shing M (2003) Verification of timing properties in rapid system prototyping. In: Proceedings of 14th IEEE international workshop in rapid systems prototyping, 9–11 June 2003, pp 47–53

  9. Demir K, Drusinsky D, Shing M (2006) Creation and validation of embedded assertions statecharts. In: 17th IEEE international workshop on rapid systems prototyping, Chania, Greece, June, pp 17–23

  10. Harel D (1987) Statecharts: a visual formalism for complex systems. Sci Comput Program 8(3):231–274

    Article  MATH  MathSciNet  Google Scholar 

  11. Havelund K, Pressburger T (2000) Model checking Java programs using Java PathFinder. Int J Softw Tools Technol Transf 2(4):366–381

    Google Scholar 

  12. Havelund K, Rosu G (2004) An overview of the runtime verification tool Java PathExplorer. In: Formal Methods in System Design, vol 24. Springer, The Netherlands, pp 189–215

  13. Hopcroft JE Ullman JD (2006) Introduction to automata theory, languages, and computation. Addison Wesley, Boston

  14. JUnit. http://www.junit.org

  15. Kohavi Z, Jha NK (2009) Switching and finite automata theory. Cambridge University Press, Cambridge

  16. Mann TP (2006) Numerically stable hidden markov model implementation. An HMM scaling tutorial

  17. Newberg L (2009) Error statistics of hidden Markov model and hidden Boltzmann model results. BMC Bioinform 10:212. doi:10.1186/1471-2105-10-212

    Article  Google Scholar 

  18. Pierce J (1969) Whither speech recognition. J Acoust Soc Am

  19. Rabiner LW (1989) A tutorial on hidden markov models and selected applications in speach recognition. Proc IEEE 77(2):257–286

    Google Scholar 

  20. Rätsch, G, Sonnenburg S, Srinivasan J, Witte H, Müller KR, Sommer RJ, Schölkopf B (2007) Improving the C. elegans genome annotation using machine learning. PLoS Comput Biol 3(2):e20. doi:10.1371/journal.pcbi.0030020

  21. Sammapun U, Lee I, Sokolsky O (2005) RT-MaC: Runtime monitoring and checking of quantitative and probabilistic properties. In: Proceedings 11th IEEE international conference on embedded and real-time computing systems and applications. IEEE, New York, pp 147–153

  22. Singh S (1999) The code book: the science of secrecy from ancient Egypt to quantum cryptography. Fourth Estate, London, pp 143–189, ISBN: 1-85702-879-1

  23. The StateRover. http://www.time-rover.com

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Authors and Affiliations

  1. Department of Computer Science, Naval Postgraduate School, 1411 Cunningham Road, Monterey, CA, 93943, USA

    Doron Drusinsky

  2. Time Rover, Inc., 11425 Charsan Lane, Cupertino, CA, 95014, USA

    Doron Drusinsky

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  1. Doron Drusinsky
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Correspondence to Doron Drusinsky.

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This research was funded by a Grant from the US Defense Threat Reduction Agency (DTRA). The views expressed in this document are those of the author and do not reflect the official policy or position of the Department of Defense or the US Government.

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Drusinsky, D. Runtime monitoring and verification of systems with hidden information. Innovations Syst Softw Eng 10, 123–136 (2014). https://doi.org/10.1007/s11334-013-0224-9

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