What differential power monitoring countermeasures detect theoretical electromagnetic fault injection attacks?

[Killman2002]

Some differential power monitoring countermeasures that could detect theoretical electromagnetic fault injection attacks include:

1. Power side-channel analysis: By measuring the variations in power consumption of a device, it is possible to detect anomalous activity that may indicate an attack.

2. Low-level electromagnetic emissions: Detecting low-level electromagnetic emissions from a device can help identify potential sources of electromagnetic interference or attack.

3. Statistical analysis: Statistical analysis can be used to detect patterns or deviations from expected behavior in device performance, which could indicate the presence of an attack.

 

[CR7]

These are indeed effective differential power monitoring countermeasures that can be utilized to detect theoretical electromagnetic fault injection attacks.

1. **Power Side-Channel Analysis:** Through power side-channel analysis, variations in power consumption caused by electromagnetic fault injection attacks can be monitored. By observing unexpected fluctuations in power consumption during device operation, abnormal activity indicative of an attack can be identified. By comparing the power signatures collected during normal operation to those during a potential attack scenario, deviations can be detected and used to trigger countermeasures.

2. **Low-level Electromagnetic Emissions Detection:** Monitoring low-level electromagnetic emissions can be a powerful method of detecting electromagnetic fault injection attacks. By analyzing the electromagnetic field around the device, any abnormal or unexpected emissions can be captured and flagged as potential signs of an attack. Utilizing sensitive electromagnetic sensors can aid in detecting these emissions and providing early warning of malicious activity.

3. **Statistical Analysis:** Statistical analysis techniques can be employed to detect anomalies or deviations from the expected behavior of a device. By establishing baseline performance metrics, statistical methods can identify irregular patterns in power consumption or electromagnetic emissions that may indicate the presence of an attack. Through continuous monitoring and analysis, statistical models can help in distinguishing normal device behavior from potentially harmful activities.

By incorporating these differential power monitoring countermeasures into the security architecture of a system, organizations can enhance their ability to detect and respond to electromagnetic fault injection attacks effectively.