## 5 Validation and Data Analysis with ML
### Second Scenario: Experimentation with BCT
The BC access control data structure is considered in terms of normal activity and the detected attacks in the IIoT networks. Based on the BC access control data structure, the results illustrate the ability of the system to detect brute force attacks by counting the number of times tentatively guessing a password that exceeds a number of times (this value has been set to five in our experiments). Several locations for the same command are considered as a DDoS attack against an IIoT network (i.e., greater or equal to two locations). By considering BC for sensor access control, DDoS, injection, brute force and XSS attacks are reduced considerably: as depicted in Figure 11, the DDoS, Brute force, injection and XSS attacks are reduced by a factor of 34.98%, 25.93%, 37.90% and 46.57%, respectively. Brute force attack cannot be detected for 100% due to the wrong number of times tentatively entering a password performed by an authorized user. In addition, DDoS could not be detected due to the huge variant of this kind of attack. \begin{table} \begin{tabular}{c c c c c c c c c} \hline \hline
**\%** & \
\begin{tabular}{c} **Normal** \\ **Activity** \\ \end{tabular} & **DDoS** & **DoS** & **Injection** & **MitM** &
\begin{tabular}{c} **Brute** \\ **Force** \\ \end{tabular} & **XSS** & **Scanning** \\ \hline ANN & 100 & 100 & 99.3 & 100 & 100 & 100 & 100 & 99.7 \\ DT & 99.9 & 100 & 99.9 & 99.4 & 100 & 100 & 100 & 99.8 \\ SVM & 100 & 100 & 100 & 100 & 99.8 & 100 & 100 \\ RF & 99.5 & 99.7 & 99.3 & 99.6 & 57.7 & 99.8 & 99.4 & 99 \\ NB & 61.9 & 95.8 & 56.6 & 82.4 & 11.8 & 98.2 & 87.8 & 25.1 \\ \hline \hline \end{tabular}   
* To validate our model in this context, a five-step-based scenario is proposed as follows:
* Data sensing gathered from physical layer (including read/write of new sensor value and authentication request). * Data control and validation performed by the access control system in the transport layer level (i.e., the client process will prepare the sensorID, userID and userpwd to be sent to server process for an authentication request). * BC access control data structure will be used to save relevant data related to sensor authentication process (i.e., including authentication identity, authorized persons, location for the same command and the number of tentative with wrong password. All collected data are used to create a smart contract describing the sensor information asset performed by the application layer to provide sensor authentication service. * ML tools and optimization technique. This process is carried out by the advanced service layer based on the information provided by the BC access control data structure to detect DDoS and brute force attacks by using the gathered data (i.e., LocationFor-SameCommand and Numberofentativewithwrongpassword will serve as features). The optimization technique is employed through the usage of the SMO classifier (a kind of SVM classifier) by implementing [PERSON]’s sequential minimal optimization algorithm for training a support vector classifier. * Data analysis and performance metrics: this step is required to determine the performance evaluation of the proposed model in terms of the four introduced metrics (accuracy, precision, sensitivity and MCC). In the second scenario, the same classification process as in the first scenario (as described in Figure 7) was selected, considering extra features (authenticationIdentity, AuthorizedPersons, Numberofentativewithwrongpassword and CommandLocation) provided by the smart contract data structure. Figure 11 describes the data instance repartition for the various studied attacks. The BC access control data structure is considered in terms of normal activity and the detected attacks in the IIoT networks. Based on the BC access control data structure, the results illustrate the ability of the system to detect brute force attacks by counting the number of times tentatively guessing a password that exceeds a number of times (this value has been set to five in our experiments).