## 2 Related Works
### Countermeasures Against SCAs  
To mitigate the risks posed by SCAs, several countermeasures have been developed. Hiding techniques attempt to randomize power consumption patterns by introducing noise or varying execution sequences, making it harder for attackers to extract meaningful information. Blinding methods involve mathematically altering cryptographic computations to obscure correlations between intermediate values and final results. Masking techniques introduce random values during encryption processes to prevent attackers from deriving sensitive data through statistical analysis [23]. Despite their effectiveness, these countermeasures are increasingly challenged by DL-SCA methodologies, which can adapt to and learn from complex data patterns, bypassing traditional security measures [24]. Recent studies have proposed hybrid countermeasures that combine multiple defensive techniques to improve resistance against DL-SCAs [25]. For example, dynamic power management, randomized instruction execution, and noise injection are being explored as complementary approaches to traditional hiding and masking techniques. The effectiveness of these combined countermeasures depends on implementation efficiency, resource overhead, and adaptability to evolving attack methodologies. Table 1 presents an overview of countermeasures used against SCAs, categorizing them based on their primary defense mechanisms. These methods aim to either obscure power consumption patterns, introduce mathematical transformations, or combine multiple techniques to enhance resistance to DL-based attacks. Hiding techniques are a class of side-channel countermeasures designed to make the power consumption of cryptographic devices independent of the data values being processed and the operations being performed. Formally, a hiding countermeasure ensures that the instantaneous power consumption either exhibits random variation or remains constant across different computations, thereby decoupling data-dependent leakage from observable side-channel signals [25]. This is typically achieved by reducing the signal-to-noise ratio (SNR) of the leakage, making it harder to distinguish meaningful patterns [1]. There are two principal approaches to achieving this. The first is to introduce randomization in power consumption per clock cycle, typically by varying the timing or sequence of cryptographic operations. The second is to enforce constant power consumption through uniform switching activity or balanced logic styles, regardless of the input or operation. While achieving perfect randomness or uniformity is infeasible in practice, hiding techniques approximate these conditions to obscure exploitable patterns in power traces, thereby enhancing resistance against power analysis attacks. Table 2 shows the classification of hiding techniques. \begin{table}
\begin{tabular}{c p{142.3 pt}} \hline \hline
**Response Method** & **Method Description** \\ \hline \multirow{2}{*}{Hiding Methods} & Generating random numbers and providing independence between intermediate values in actual computation to prevent leakage. \\ \hline \multirow{2}{*}{Blinding Methods} & Obscures input and output values through transformation functions. \\ \hline \multirow{2}{*}{Masking Methods} & Randomizes key and message data to prevent correlation with actual values. \\ \hline \multirow{2}{*}{Hybrid Methods} & Combines multiple countermeasures such as noise injection and randomized execution to improve resilience. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Countermeasures against side-channel attacks. Among various hiding techniques, dummy insertion remains one of the most widely adopted approaches, primarily because it does not require hardware or algorithmic modifications [25]. To bypass such dummy-based countermeasures, several prior studies have employed techniques such as feature fusion and data denoising [19], while others have utilized CNNs to identify dummy instructions in IC card environments [26].