Hardware-Based Probabilistic Threat Detection and Estimation for Embedded Systems

Nadir Amin Carreon, Sixing Lu, Roman Lysecky

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

With billions of networked connected embedded systems, the security historically provided by the isolation of embedded systems is no longer sufficient. Both proactive security measures that prevent intrusions and reactive measures that detect intrusions are essential. Anomaly-based detection is a common reactive approach employed to detect malware that has evaded proactive defenses by observing anomalous deviations in the system execution. Timing-based anomaly detection detects malware by monitoring the system's internal timing, which offers unique protection against mimicry malware compared to sequence-based anomaly detection. However, previous timing-based anomaly detection methods focus on each operation independently at the granularity of tasks, function calls, system calls, or basic blocks. These approaches neither consider the entire software execution path nor provide a quantitative estimate of the presence of malware. This paper presents a novel model for specifying the normal timing for execution paths in software applications using cumulative distribution functions of timing data in sliding execution windows. We present a probabilistic formulation for estimating the presence of malware for individual operations and sequences of operations within the paths, and we define thresholds to minimize false positives based on training data. Experimental results with a smart connected pacemaker and three sophisticated mimicry malware demonstrate improved performance and accuracy compared to state-of-The-Art timing-based malware detection.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE 36th International Conference on Computer Design, ICCD 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages522-529
Number of pages8
ISBN (Electronic)9781538684771
DOIs
StatePublished - Jan 16 2019
Event36th International Conference on Computer Design, ICCD 2018 - Orlando, United States
Duration: Oct 7 2018Oct 10 2018

Publication series

NameProceedings - 2018 IEEE 36th International Conference on Computer Design, ICCD 2018

Conference

Conference36th International Conference on Computer Design, ICCD 2018
CountryUnited States
CityOrlando
Period10/7/1810/10/18

Keywords

  • Anomaly detection
  • Embedded system security
  • Non-intrusive hardware
  • Timing-based threat detection

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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    Carreon, N. A., Lu, S., & Lysecky, R. (2019). Hardware-Based Probabilistic Threat Detection and Estimation for Embedded Systems. In Proceedings - 2018 IEEE 36th International Conference on Computer Design, ICCD 2018 (pp. 522-529). [8615734] (Proceedings - 2018 IEEE 36th International Conference on Computer Design, ICCD 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCD.2018.00084