Recent research has demonstrated that there is no sharp distinction between passive attacks based on side-channel leakage and active attacks based on fault injection. Fault behavior can be processed as side-channel information, offering all the benefits of Differential Power Analysis including noise averaging and hypothesis testing by correlation. In fault attacks, the adversary induces faults into a device while it is executing a known program and observes the reaction. The abnormal reactions of the device are later analyzed to obtain the secrets of the program under execution.

Fault attacks are a powerful threat. They are used to break cryptosystems, Pay TVs, smart cards and other embedded applications. In fault attack resistant design, the fault is assumed to be induced by a smart, malicious, determined attacker who has high knowledge of the design under attack. Moreover, the purpose of fault attack resistant design is for the system to work correctly under intentional fault injection without leaking any secret data information.

Towards building a fault attack resistant design, the problem can be categorized into three main subjects:

• Investigating novel and more powerful threat models and attack procedures.

• Proposing countermeasures to build secure systems against fault attacks

• Building evaluation metrics to measure the security of designs

In this regard, my thesis has covered the first bullet, by proposing the Differential Fault Intensity Analysis (DFIA) based on the biased fault model. The biased fault model in this attack means the gradual behavior of the fault as a cause of increasing the intensity of fault injection. The DFIA attack has been successfully launched on AES, PRESENT and LED block ciphers. Our group has also recently proposed this attack on the AES algorithm running on a LEON3 processor.

In our work, we also propose a countermeasure against one of the most powerful types of fault attacks, namely, Fault Sensitivity Analysis (FSA). This countermeasure is based on balancing the delay of the circuit to destroy the correlation of secret data and timing delay of a circuit.

Additionally, we propose a framework for assessing the vulnerability of designs against fault attacks. An example of this framework is the Timing Violation Vulnerability Factor (TVVF) that is a metric for measuring the vulnerability of hardware against timing violation attacks. We compute TVVF for two implementations of AES algorithm and measure the vulnerability of these designs against two types of fault attacks.

For future work, we plan to propose an attack that is a combination of power measurements and fault injections. This attack is more powerful in the sense that it has less fault injection restrictions and requires less amount of information from the block cipher's data. We also plan to design more efficient and generic evaluation metrics than TVVF.

As shown in this thesis, fault attacks are more serious threat than considered by the cryptography community. This thesis provides a deep understanding of the fault behavior in the circuit and therefore a better knowledge on powerful fault attacks. The techniques developed in this dissertation focus on different aspects of fault attacks on hardware architectures and microprocessors. Considering the proposed fault models, attacks, and evaluation metrics in this thesis, there is hope to develop robust and fault attack resistant microprocessors. We conclude this thesis by observing future areas and opportunities for research.