**4. Performance Evaluations**

In this section, the sensitivity of the initial conditions and the control parameters is measured by the cross-correlation coefficient. Furthermore, the quantitative values of the randomness of sequences generated by the 2D-ICSM are determined using NIST-800-22 randomness tests.

## *4.1. Cross-Correlation Coefficient*

To estimate the sensitivity of the initial conditions and the control parameters of the 2D-ICSM, we use the cross-correlation coefficient (CCF); its equation is given by

$$\text{CCF}(a\_t, \beta\_t) = \frac{\sum\_{t=1}^{N} (a\_t - A(a))(\beta\_t - A(\beta))}{\sqrt{\sum\_{t=1}^{N} (a\_t - A(a))^2 \sum\_{t=1}^{N} (\beta - A(\beta))^2}},\tag{4}$$

where *A*(*α*) represents the mean value of the time series *αt*, meanwhile *A*(*β*) represents the mean value of the time series *βt*. When *CCF*(*αt*, *βt*) is close to 0, then it can be indicated that these two-time series are diverging.

Figure <sup>5</sup> presents the sensitivity of the 2D-ICSM with the parameters *α* ∈ [0, 8] and *β* = 12. In this figure, the sensitivity is estimated by calculating the CCF between the original time series and the modified time series. It is important to mention here that the modified time series was generated by the 2D-ICSM using a very small error, *<sup>e</sup>* = <sup>5</sup> × <sup>10</sup>−5, which was added to the initial value *<sup>x</sup>*<sup>0</sup> and the parameter *α*, as shown in Figure 5a,b, respectively. It can be observed that the 2D-ICSM has a high level of sensitivity to its initial values and control parameters.

**Figure 5.** The CCF analysis of the 2D-ICSM with 0 ≤ *α* ≤ 8 and *β* = 12: (**a**) the CCF with the initial values (0.1 + *e*, 0.1); (**b**) the CCF with the initial values (0.1, 0.1) and for *α* + *e*.
