5.1 Brief Review of Basic Techniques for Detection …
463
The mathematical analysis of the measurement results here is based on the characterization of logical elements and their subsequent statistical analysis. In this case, a
new additional function is set for the standard research program, taking into account
the sub-modular nature of the problem: obviously, the smaller the size of the analyzed
circuit, the stronger the impact of the Trojan on the used specific third-party channel.
After characterization process, for each logical circuit of the microcircuit, the
deviation of the experimental measurement results from the expected (calculated)
numerical values is calculated. After that, sensitivity analysis is performed, which
ultimately makes it possible to detect potential malicious microcircuits. It is clear that
the design of any Trojan in the microcircuit determines its effect on side channels.
Some Trojans are more likely to affect the amount of power consumption, others–
the performance. The measurement results of various analyzes (multimodal) are
combined to achieve a higher level of detection. The experiments performed by
the authors demonstrate that if Trojans are installed in the IC regions with normal
sensitivity, the probability of such detection is 100%. The converse case is also true:
this method can be used to determine topology areas where detecting Trojans is most
problematic.
Lamech et al. [30] also use their method to estimated the effectiveness of results
of combined analyses of various side channels. Unlike [28], however, they do not
present a common model for integration of the results obtained by using various
methods of side-channel analysis. They demonstrate that by combining transient
power analysis and performance analysis with subsequent regression analysis it is
possible to achieve higher detection levels than by using each analysis separately.
5.1.15 Increasing the Probability of Trojan Activation Due
to Additional Triggers
To increase the probability of state transitions in environments of microcircuits
under study in the process of functional tests, Salmani et al. [42, 44] presented
their own original approach, which involves inserting false scan triggers into the
original circuit. As a result, Trojans should fully or partially activate and have a
corresponding impact on third-party channels. For example, the logical elements
of a Trojan may turn on, and therefore, during the third-party channel analysis, a
corresponding increase in the level of energy consumption can be observed. The
most important task of this method is to reduce the time for authorization of an IC,
without which its practical implementation would be problematic.
463
The mathematical analysis of the measurement results here is based on the characterization of logical elements and their subsequent statistical analysis. In this case, a
new additional function is set for the standard research program, taking into account
the sub-modular nature of the problem: obviously, the smaller the size of the analyzed
circuit, the stronger the impact of the Trojan on the used specific third-party channel.
After characterization process, for each logical circuit of the microcircuit, the
deviation of the experimental measurement results from the expected (calculated)
numerical values is calculated. After that, sensitivity analysis is performed, which
ultimately makes it possible to detect potential malicious microcircuits. It is clear that
the design of any Trojan in the microcircuit determines its effect on side channels.
Some Trojans are more likely to affect the amount of power consumption, others–
the performance. The measurement results of various analyzes (multimodal) are
combined to achieve a higher level of detection. The experiments performed by
the authors demonstrate that if Trojans are installed in the IC regions with normal
sensitivity, the probability of such detection is 100%. The converse case is also true:
this method can be used to determine topology areas where detecting Trojans is most
problematic.
Lamech et al. [30] also use their method to estimated the effectiveness of results
of combined analyses of various side channels. Unlike [28], however, they do not
present a common model for integration of the results obtained by using various
methods of side-channel analysis. They demonstrate that by combining transient
power analysis and performance analysis with subsequent regression analysis it is
possible to achieve higher detection levels than by using each analysis separately.
5.1.15 Increasing the Probability of Trojan Activation Due
to Additional Triggers
To increase the probability of state transitions in environments of microcircuits
under study in the process of functional tests, Salmani et al. [42, 44] presented
their own original approach, which involves inserting false scan triggers into the
original circuit. As a result, Trojans should fully or partially activate and have a
corresponding impact on third-party channels. For example, the logical elements
of a Trojan may turn on, and therefore, during the third-party channel analysis, a
corresponding increase in the level of energy consumption can be observed. The
most important task of this method is to reduce the time for authorization of an IC,
without which its practical implementation would be problematic.