# Enhancing Cybersecurity Through Comprehensive Investigation of Data Flow-Based Attack Scenarios
## 3 Proposed Approach
### Methodology
#### 3.2.3 Impact Enumeration
* **Resource consumption:** A type of cyberattack where an attacker intentionally consumes or exhausts critical system resources such as computational power, memory, CPU processing power, network bandwidth, and storage capacity. * **Prevent access to data store:** A type of cyberattack in which an attacker intentionally disrupts or denies access to data stores within a system or network. This attack prevents legitimate users or system components from accessing and retrieving stored data. * **Incorrect data delivery:** A type of cyberattack where an attacker intentionally manipulates, substitutes, or falsifies data that are transmitted or delivered within the system. * **Denial of data reception:** A type of cyberattack in which an adversary intentionally prevents or obstructs the intended reception of data by the CPS. * **Sending data to the attacker's target:** A type of cyberattack in which an attacker deliberately reroutes or forwards data generated or processed by the system to a destination of their choosing. This destination, known as the attacker's target, is typically under their control or influence. * **Writing data to the attacker's target:** A type of cyberattack in which an attacker alters the system's data in such a way that the modified data are written or directed towards a destination controlled by the attacker. This destination typically resides outside the CPS environment and is under the control of the adversary. Such an attack can compromise data integrity and potentially cause harm to the system and its users. By categorizing the attacks into general and CPS-specific attacks, it is possible to better understand the unique threats and vulnerabilities faced by cyber-physical systems. The list of CPS-specific attacks, including those targeting industrial control systems, sensor networks, and physical processes, serves as a foundation for the subsequent steps of our proposed approach. In the next step, we leverage the list to generate attack profiles that capture the characteristics, origins, and potential impacts of each attack scenario. By explicitly highlighting the CPS-specific attack categories within the list and utilizing these for subsequent attack profiling and scenario generation, it becomes possible to focus on the unique vulnerabilities and challenges faced by cyber-physical systems. In this step, we generate the attack profile by investigating and analyzing the threat report produced by the Microsoft Threat Modeling tool. For the purposes of this paper, the term 'threat report' specifically refers to the report generated by the tool. The list generated by STRIDE (\(tList\)) contains information about only one of the two interacting components. A component can be an entity, process, or data store in the DFD. Each exchange of information is represented by a data flow, called an _Interaction_ (\(Int\)). We implement an additional functionality to identify the right Source (\(S\)) and Destination (\(D\)) for each \(Int\). This information is needed in order to identify the origin and direction of the threat, where it enters the system, and where it goes. One of the challenges is that each component of the system can be a source for several components, and can also be a destination for several; therefore, we need to identify all the origins and destinations of each exchange of information. It may also be the case that the same information exchange (\(Int\)) takes place between several sources and destinations. We refer to such an interaction as redundant information. Consequently, while any of the Source, Destination, and Interaction can be redundant, but there must be a unique combination of Source, Interaction, and Destination such that \(S\xrightarrow{Int}D\). Because each data flow can cause more than one threat, we go through each of the associated threat categories, identify effects caused by all threat scenarios, and map them to the classes introduced in regard to the attack impact (see Section 3.2.3).