2015 1st URSI Atlantic Radio Science Conference (URSI AT-RASC) 2015
DOI: 10.1109/ursi-at-rasc.2015.7303039
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Automated analysis of the effects induced by radio-frequency pulses on embedded systems for EMC Functional Safety

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Cited by 8 publications
(3 citation statements)
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“…In previous literature, abundant detection/mitigation methods against electromagnetic signal injection attacks have been proposed for various systems: for example, adding extra detection circuits to spot attacks by monitoring abnormal electromagnetic activities [1,2,11,50], encoding critical signals secretly and detecting attacks if the signal integrity corrupts [26,42,48,56], or, exploiting measurements from sensors plus tricky algorithms to detect/mitigate attacks [15,23,24,34,51]. Similar ideas theoretically apply to differential signaling, but millions of devices are not yet protected from the electromagnetic signal injection attacks.…”
Section: Future Countermeasuresmentioning
confidence: 99%
“…In previous literature, abundant detection/mitigation methods against electromagnetic signal injection attacks have been proposed for various systems: for example, adding extra detection circuits to spot attacks by monitoring abnormal electromagnetic activities [1,2,11,50], encoding critical signals secretly and detecting attacks if the signal integrity corrupts [26,42,48,56], or, exploiting measurements from sensors plus tricky algorithms to detect/mitigate attacks [15,23,24,34,51]. Similar ideas theoretically apply to differential signaling, but millions of devices are not yet protected from the electromagnetic signal injection attacks.…”
Section: Future Countermeasuresmentioning
confidence: 99%
“…In addition, in specific devices such as cardiac implantable electrical devices (CIED) [25] and smartphones [45], researchers utilized users' reactions or behaviors while using these devices to identify the existence of attacks on the sensors. A few works mentioned that multiple built-in sensors of a device can react to variations of the electromagnetic environment, and the characteristics can be exploited to detect abnormal electromagnetic activities [21,22]. Such a detection approach is also known as sensor fusion, which has been widely studied to detect signal injections that use other types of attacking signals such as ultrasonics and lasers [16,48].…”
Section: Detectionmentioning
confidence: 99%
“…3) Configuration settings: A better granularity in the user settings could be a great improvement: Letting the user choose his own keyword (already possible on most of devices but few users are doing so), disabling the voice interface by default, allowing the user to finely choose the authorized applications and actions via this interface, especially those accessible before the lock screen authentication process, would be interesting options. 4) Unusual EM activity detection: Recently, it has been shown that the many built-in sensors present in smartphones react to variations of the EM field nearby the device [19]. This characteristic could be used in order to monitor and detect any abnormal EM activity around the smartphone when a voice command is being processed, resulting in a rejection of the command when a suspicious activity is detected.…”
Section: B Countermeasuresmentioning
confidence: 99%