# Enhancing Cybersecurity Through Comprehensive Investigation of Data Flow-Based Attack Scenarios
## 3 Proposed Approach
### Methodology
#### 3.2.3 Impact Enumeration
This knowledge can then inform the development and implementation of targeted security measures, ensuring that the most critical components are adequately protected against potential attacks. Figure 7: Frequency of attack scenarios in the _remote control Hx-1_ case study. **Analysis of Attack Scenario Distribution and Prioritization based on Attack Types:**

We performed an analysis of the distribution of attack scenarios based on our classification of the different attack types, as explained in Section 3.2.3. This classification includes sixteen different types of attacks. Among the 3100 scenarios analyzed, a total of 8920 attacks were identified, with some scenarios having multiple attack types. Figure 9 provides a visualization of the categories of attack types and their corresponding frequencies obtained by aggregating the number of attack scenarios within each category. The chart shows that the _Impersonate_ category accounts for the highest proportion of attack types at 17%. This finding highlights the importance of impersonation-based attacks and the need for robust authentication and access control mechanisms within the system. Security experts should prioritize the development of countermeasures and recovery strategies specifically tailored to mitigate these types of attacks, as they represent a significant threat to the integrity of the system. The _Unauthorized Access_ category follows closely in second place, with 11% of the identified attack types. This category includes attacks aimed at gaining unauthorized access to system resources or data, highlighting the importance of implementing comprehensive access control policies and monitoring mechanisms to detect and prevent such attempts. The pie chart also highlights other notable attack categories, such as _Interrupt data flowing (7%)_, _Prevent access to data store (7%)_, and _Remotely execute code (7%)_. These categories represent different attack paths ranging from disruption of data flow to remote execution of malicious code, each presenting unique challenges and requiring tailored security measures. By exploring this visual representation, system security analysts can prioritize the development of recovery mechanisms and security controls based on the most critical attack types within the system. The chart serves as a valuable tool for identifying areas that require immediate attention and resource allocation, enabling a proactive approach to enhancing the system's overall security posture. Figure 8: Component counts in scenarios for the _remote control Hx-1_ case study. Figure 9: Variety of potential attack types targeting the _remote control Hx-1_ case study. **Prevalence and Distribution Analysis of Cyberattack Scenarios:** We analyzed the number of attack scenarios associated with each specific type of attack in the remote control Hx-1 case study. This can provides insight into the prevalence and distribution of the different attack types. The visualization in Figure 10 shows the distribution of scenarios with specific cyberattacks, illustrating the prevalence of the different attack types. The X-axis represents the number of scenarios, while the Y-axis indicates the types of attack. This chart provides a detailed overview of the attack landscape, enabling security professionals to effectively prioritize and allocate resources. The analysis shows that the _Impersonate_ attack type is the most prevalent, accounting for 19% of the identified attack scenarios. This finding underlines the importance of implementing robust authentication and access control mechanisms in the system to mitigate the risks associated with impersonation attacks. Furthermore, the chart highlights several other notable attack types, each comprising 7% of the scenarios. These include _Information not intended for disclosure_, _Unauthorized Access_, _Data Flow Sniffing_, _Change the flow of program execution_, _Crashes_, _Cross-site request forgery_, _Interrupt data flowing_, _Prevent access to data store_, _Remotely execute code_, _Resource consumption_, and _Data Repudiation_.