# Low-Cost Full Correlated-Power-Noise Generator to Counteract Side-Channel Attacks
## 2 PA Attacks and Effective Countermeasures
### Attacks  
Actual attack strategies exhibit significant differences in terms of cost, time, equipment, and expertise. Since the reverse engineering of chips demands costly and advanced equipment, there has been an interest in exploring alternative methods for developing physical attacks [1]. The focus was on identifying the information accessible to attackers, which was not assumed within the cryptographic protocols. Within this category of threats, a secondary classification is made between active and passive attacks. An active attack changes the functionality of the device during operation manipulating its inputs, power supply, or temperature, then finally analyzing the behaviour of the target after the manipulation. In contrast, in a passive attack, the secret information is revealed while the cryptographic device operates in the correct way, so the attack may even go unnoticed by device users. For this reason, researchers show great interest in studying the security against these latest attacks. Passive non-invasive attacks, particularly SCAs targeting cryptographic devices, exploit specific physical data to uncover confidential or critical information contained by the target. Depending on the exploited leakage, the SCA attacks can be classified into different types of attacks [1]. One of the most known SCAs is timing attacks [8], where the adversaries may recover data from systems through meticulous timing measurements during operations. This attack proves to be computationally economical and the attacker does not need to have strong knowledge of the device. On the other hand, PA [3] or electromagnetic (EM) [9] attacks leverage the correlation between power consumption or electromagnetic radiation, respectively, in cryptographic circuits and the data being processed. SCA attacks can also be categorized based on different attacker models [1]. Non-profiled attacks assume that the adversary has access only to the specific targeted device, often needing additional information like hypothetical power models or specific details of the implementation. Examples of non-profiled attacks include Simple Power Analysis (SPA) and DPA/CPA attacks [3]. Still, profiled attacks involve adversaries who not only have access to the target device but also possess other samples under their control. This access enables the attacker to model the physical behavior of the target, determining its response to all possible secret intermediate values in a phase known as the profiling phase. Examples of profiling attacks encompass Template or machine-learning-based attacks. This study measures the security of crypto-implementations by performing non-profiled attacks as the CPA attacks. The objective of a CPA attack is to uncover the confidential cryptographic key employed by a device by analyzing a substantial volume of power consumption traces obtained from the Device Under Test (DUT) during data encryption or decryption. In the practical execution of a CPA attack, an adversary begins by observing and capturing a series of \(m\) encryption operations or power traces, denoted as \(T[1:m]\). Each trace comprises \(n\) sampled points so the power consumption matrix is \(T[m,n]\).Additionally, the attacker acquires recordings of either the \(ciphertext\)\([1:m]\), \(plaintexts\)\([1:m]\), or both. The analysis centers on an intermediate cipher operation where the private key interacts with a known value, typically \(plaintext\) or \(ciphertext\), corresponding to the operation performed during the first or last encryption round, respectively. Figure 1 shows the steps in a complete CPA attack on the first round. Once the operation of interest has been identified,and the power consumption traces \(T\) have been collected, the subsequent step in the CPA attack involves calculating intermediate hypothetical values, \(H[m,n]\), for each of the possible keys \(k\). These hypothetical values are subsequently correlated with power consumption values using a power model. The choice of the power model significantly impacts the success of the attack.