Detecting Failures and Attacks via Digital Sensors

Detection of abnormal behaviors is essential in complex and/or strategic systems requiring a high level of safety and security. Sensing environmental conditions to ensure that the device is not operating out-of-specifications is highly useful in detecting anomalies caused by failures or malevolent a...

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Veröffentlicht in:IEEE transactions on computer-aided design of integrated circuits and systems 2021-07, Vol.40 (7), p.1315-1326
Hauptverfasser: Anik, Md Toufiq Hasan, Danger, Jean-Luc, Guilley, Sylvain, Karimi, Naghmeh
Format: Artikel
Sprache:eng
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Zusammenfassung:Detection of abnormal behaviors is essential in complex and/or strategic systems requiring a high level of safety and security. Sensing environmental conditions to ensure that the device is not operating out-of-specifications is highly useful in detecting anomalies caused by failures or malevolent actions. In this regard, digital sensors (DSs) are particularly attractive as they are portable and can be easily calibrated. In contrast to analog sensors, DSs have an interesting property that considers the operating environmental conditions as a whole, i.e., they are sensitive to temperature, voltage, and process altogether, without precise knowledge about each. This property endows DSs with fewer false positives compared to analog sensors. This article studies a low-cost DS, discusses its presilicon architecture and post-silicon calibration such that it detects system failures accurately in the designer's preferable range of operating conditions. The impact of aging in this sensor is studied extensively. Tradeoffs between false positive and undetection rates are discussed. As an example, we target the substitution box (S-Box) of the PRESENT cipher assuming that it can be the target of fault injection attacks launched via abruptly changing the operating temperature and voltage. We show that such malfunction can be accurately detected by our DS, i.e., with a very negligible percentage of false and missed alarms (
ISSN:0278-0070
1937-4151
DOI:10.1109/TCAD.2020.3020921