## 4 Results
### Scenario 2
#### 4.2.3 Comparative Analysis  
A broader analysis of the impact of the proposed solutions on the security of synchronization, following the same methodology as in the previous section, is presented in Figure 7. The analysis is again split into four parts:  
1. Comparison of scenarios in which all parties are using hebbian versus scenarios in which victims change their update algorithms to proposed solutions.
2. Comparison of scenarios in which all parties are using random walk versus scenarios in which victims change their update algorithms to proposed solutions.
3. Comparison of scenarios in which all parties are using hebbian versus scenarios in which victims change their update algorithms to proposed solutions and the attacker chooses their update rule randomly.
4. Comparison of scenarios in which all parties are using random walk versus scenarios in which victims change their update algorithms to proposed solutions and the attacker chooses their update rule randomly.  
Most of the results are almost the same as in the analysis of Scenario 1. In fact, in the first part (presented in Figure 7a) they are the same-usage of either of the dynamic solutions resulted in attacker achieving a lower percentage of synchronization, compared to all parties using hebbian in all cases. The same applies to the fourth part of the analysis  
Figure 6: Scenario 2–\(K=5,N=34,L=4,QBER=7\).  
(presented in Figure 7d)-when the attacker was choosing their update rule randomly (and the victims were using dynamic update rules), in all of the tests in this scenario, they were unable to synchronize their machines as much as in case where everyone was using random walk.  
In the case of the second part of the analysis (presented in Figure 7b) the results were not identical, but very close to the results from Scenario 1. In Scenario 2, the percentage of tests in which both proposed solutions outperformed random walk synchronization has increased (50% of tests, compared to 41.67% in Scenario 1), percentage of tests in which only dynamic_rows was better and both proposed solutions were worse have decreased (from 16.66% to 11.11% and from 30.55% to 27.78% compared to Scenario 1, respectively), while percentage of tests in which only dynamic_matrix was better when it remained unchanged (11.11%).  
In Scenario 2, the proposed solutions performed significantly worse in the third part of the analysis (shown in Figure 7c). The percentage of cases in which both dynamic  
Figure 7: Attacker’s synchronization percent using different update rules with victims using proposed solutions compared to all parties using the same update rule–Scenario 2. (**a**) Only attacker using hebbian versus all parties using hebbian; (**b**) Only attacker using random walk versus all parties using random walk; (**c**) Attacker using random update rule versus all parties using hebbian; (**d**) Attacker using random update rule versus all parties using random walk.  
approaches performed worse than the hebbian-only synchronization increased from 55.56% to 75%, while the percentage of cases in which both dynamic algorithms performed better increased slightly (from 19.44% to 22.23% compared to Scenario 1), the other metrics have notably decreased: from 19.44% to 2.77% for dynamic_matrix and from 5.55% to 0% for dynamic_rows.  
In general, the outcomes for Scenario 2 are the same as for Scenario 1:  
* If the victims have suspicion that the attacker is using hebbian, it is always better to use any of the dynamic approaches;
* If the victims have suspicion that the attacker is using random walk, in general dynamic_matrix or dynamic_rows are better (about 3/4 of all cases);
* If the attacker is using random update rule, dynamic algorithms perform worse compared to hebbian-only synchronization;
* If the attacker is using random update rule, it is always better to use dynamic update rule compared to all parties synchronizing with random walk.