Abstract
This chapter briefly summarizes recent research on the problem of inferring security properties of a computation from measurements of unintended electromagnetic emissions from the processing system on which the computation is being executed. The particular approach described involves two ingredients: (i) signal processing and machine learning to map observed analog measurements to program segments; and (ii) the program’s control flow structure which constrains the legitimate transitions between program segments. In particular, the control flow logic of a program can be represented as a control flow graph (CFG) that summarizes possible execution paths and control flows in terms of transitions between basic blocks of the executable. In other words, the ultimate goal of this work is to track the behavior of an execution using unintended electromagnetic emissions. We describe various control flow graphs properties that impact the extent to which valid execution of a program can be monitored and subsequently used for program classification and anomaly detection. Suggestions for future work on graph models are described as well.
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References
Chilenski, M., Cybenko, G., Dekine, I., Kumar, P., Raz, G.: Observability properties of colored graphs. arXiv preprint arXiv:1811.04803 (2018)
Chilenski, M., Cybenko, G., Dekine, I., Kumar, P., Raz, G.: Observability properties of colored graphs. Submitted for publication (2019)
Cleveland, C., Chilenski, M., Dekine, I., Kumar, P., Raz, G.: Microsystem identification and fingerprinting using RF side channels. Technical report, Systems and Technology Research Woburn United States (2019)
Crespi, V., Cybenko, G., Jiang, G.: The theory of trackability with applications to sensor networks. ACM Trans. Sens. Netw. (TOSN) 4(3), 16 (2008)
Cybenko, G., Raz, G.M.: Large-scale analogue measurements and analysis for cyber-security, vol. 3, p. 227. World Scientific (2018)
Dekine, I., Chilenski, M., Cleveland, C., Kumar, P., Raz, G., Li, M.: Information theoretical optimal use of RF side channels for microsystem characterization. In: Cyber Sensing 2019, vol. 11011, p. 1101108. International Society for Optics and Photonics (2019)
Jiang, G.: Weak process models for robust process detection. In: Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense III. Proceedings of SPIE, vol. 5403 (2004)
Jungers, R.M., Blondel, V.D.: Observable graphs. Discrete Appl. Math. 159(10), 981–989 (2011)
Rabiner, L.R.: A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE 77(2), 257–286 (1989)
Sheng, Y., Cybenko, G.V.: Distance measures for nonparametric weak process models. In: 2005 IEEE International Conference on Systems, Man and Cybernetics. IEEE (2005)
Acknowledgements
This work summarized here was the result of many fruitful and enjoyable collaborations with my colleagues and co-authors including: Mark Chilenski, Valentino Crespi, Isacc Dekine, Guofei Jiang, Piyush Kumar, Gil Raz and Yong Sheng.
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Cybenko, G. (2019). Graph Models in Tracking Behaviors for Cyber-Security. In: Albanese, M., Horne, R., Probst, C. (eds) Graphical Models for Security. GraMSec 2019. Lecture Notes in Computer Science(), vol 11720. Springer, Cham. https://doi.org/10.1007/978-3-030-36537-0_1
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DOI: https://doi.org/10.1007/978-3-030-36537-0_1
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