# Enhancing Cybersecurity Through Comprehensive Investigation of Data Flow-Based Attack Scenarios
## 3 Proposed Approach
### Methodology
#### 3.2.3 Impact Enumeration
This approach formalizes networked sets of devices and a symbolic intruder model in rewriting logic; in particular, attacks can be detected by changing the input and output behavior of the system and analyzing its effect on the system's behavior. Covert attacks and replay attacks were modeled and analyzed in this study; however, combinations of attacks were not considered. A study conducted by [PERSON] et al. [42] employed the STRIDE methodology to define privacy issues and establish a mapping between the system elements and identified privacy threats. The authors employed threat tree analysis and privacy-enhancing technologies (PETs) to identify privacy threats and align them with existing threats. This study introduced LINDDUN as a systematic threat modeling methodology, which adopts an approach similar to that of STRIDE for addressing threat modeling. LINDDUN stands for Linkability, Identifiability, Nonrepudiation, Detectability, Information Disclosure, Content Unawareness, and Policy and Consent Noncompliance, representing the privacy threats identified in their study. Using this framework for other use cases requires updating the privacy threats, as the privacy categories in this work are more conceptual. In addition, real-world case studies should be undertaken to evaluate the correctness of this framework. With the aim of enhancing security during the design phase of software development, [PERSON] et al. [43] devised an in-house tool in Java built upon the Oracle security tool. Their study concentrated on evaluating system security from various perspectives, including the integration of static code analysis into the development process, the software development life cycle, and the principles of security-by-design. Numerous studies have employed the STRIDE framework to discern security threats across diverse domains and use cases. For instance, [PERSON] [44] explored security concerns in smart homes and healthcare systems, leveraging STRIDE analysis to identify potential threats, offering potential countermeasures tailored to this use case. Additionally, the integration of intrusion detection and prevention systems within smart home networks was investigated to enhance the efficient identification and prevention of attacks and malicious activities. In another study, [PERSON] et al. [45] contributed to the utilization of STRIDE threat modeling at various levels of abstraction within software systems. Their work focused on automating the generation of security tests through STRIDE threat modeling. Their proposed approach emphasizes the repeatability and reproducibility of security tests, facilitating their execution during software development processes that involve frequent changes. While the authors sought to mitigate the identified security threats using analysis and modeling results, their study revealed that only a limited number of mutants were successfully eliminated in the examined use cases. They attributed this outcome to the exclusive utilization of free threat scanning and security tools for system analysis. Several methods have been developed to describe and analyze attack surfaces in cybersecurity contexts. Attack trees, first introduced by [PERSON] et al. [46], provide a structured, hierarchical representation of potential attack paths. They provide a visual way to analyze security threats, but can become very complex for large systems. Attack graphs [47] also represent possible attack paths in a system, and are more flexible than attack trees; however, they can be difficult to create and analyze for complex systems. The DREAD model, which was also developed by Microsoft, helps to quantify, compare, and prioritize the risks of evaluated threats [48]. Data flow analysis has also been incorporated into security assessment in various ways [49]. Taint analysis tracks the flow of untrusted data through a program [50], while information flow control enforces security policies on data flows within a system [51].