# Challenging Assumptions of Normality in AES s-Box Configurations under Side-Channel Analysis
## 2 Related Works  
Power-based side-channel analysis involves determining the relationships between the power consumption of a device and its operations. The most common targets of this analysis are cryptographic hardware devices. [PERSON] and [PERSON] [8] mention that the \"most basic power side-channel attack\" is Simple Power Analysis (SPA), or the direct observation of the power consumption of a device. Visual observation of the power traces associated with a device executing computations can demonstrate when rounds of AES encryption are computed, as demonstrated by [PERSON] and [PERSON] [8]. An example of SCA is given in Figure 0(a), offering a visual representation of two traces sampled from an AES encryption. While subtle, close visual inspection illustrates small differences between the traces. However, visualizing two collected power traces does not provide an accurate representation of the data or underlying source algorithm. While SPA could lead to insights, or even a possible key extraction, such an exercise would require extensive knowledge of the underlying components of AES and the individual implementation. As a result, the assumption made when performing SPA is that the observer can determine useful leakage information from graphical representations of the power traces. Despite the clear limitations associated with SPA, plotting the time-series of the power traces can yield useful information regarding the processes on a device, noise, and countermeasures such as masking or hiding [9]. Masking is the process of adding a random \"masking value\" to intermediate operations on the device to remove the correlation between the power consumption of the cryptographic device and its secret cryptographic information. Hiding is the process of making power traces gathered using a cryptographic device appear to be random noise. This can be achieved by adding more noise to the operations on the device by performing non-operations (nops) or random process delays [9]. These countermeasures can make SPA difficult to perform, as any notable information from the time-series plots will appear to be random. Ultimately, relying on observations rather than statistical methods can lead to Type II errors, also known as false negatives. Drawing a false negative conclusion commonly occurs when an incorrect assumption leads to concluding that no information was leaked via the power usage of a computational system. [PERSON] et al. proposed a new approach to power-based side-channel analysis called Differential Power Analysis (DPA) [1], which offered a novel, powerful method for exploiting power-based leakage. This approach sought to leverage statistical power, which measures the sensitivity or likelihood that a statistical measure detects an effect when it is actually present, to evaluate difficult-to-observe components in traces. A secret key used by an encryption schema could then be exfiltrated from collected power traces. The statistical process used by [PERSON] et al. relies on separating the collected power traces into two groups based on whether a target's bit was set to 0 or 1. Within each group, the collection of power traces are then averaged based on each trace number to remove any collection-based noise in the time-series data, resulting in two master traces. While taking the average can be affected by outliers and skew, there are no assumptions made to perform the average. These refined traces lack the typically normally distributed perturbations present in electrically generated data. The denoising of the data was more descriptive than ever, giving a stronger power-based representation of the associated computational behavior. By adding an elementary element of fundamental statistical analysis by taking the arithmetic mean, DPA allows for more concrete results in determining whether information was leaked. This development also produced new challenges associated with mitigation strategies against power-based side-channel attacks. As demonstrated by [PERSON] et al.