This research aimed to examine the relationship between digital citizenship and information security achievements levels. For this purpose, the research was designed in the relational survey model within the scope of quantitative research. The sample of the research consists of teacher candidates studying at the Faculty of Education of Fırat University in the 2022-2023 academic year. To collect the research data, the Digital Citizenship Questionnaire and the Information Security Achievements Scale were used. At the end of the study, it was revealed that the digital citizenship levels of the teacher candidates were high, and the information security attainment levels related to threats and taking precautions were moderate. According to the gender variable, the digital citizenship levels of teacher candidates were found to be significantly higher in favor of females. Information security achievement levels differ significantly in favor of males according to the gender variable. It has been observed that as the information security achievements of the teacher candidates increase, the correct usage, health and social responsibility levels of digital citizenship tend to increase as well.

In the digital era, web applications have become a prevalent tool for businesses. As the number of web applications continues to grow, they become enticing targets for malicious actors seeking to exploit potential security vulnerabilities. Organizations face constant risks associated with vulnerabilities in their web-based software systems, which can result in data breaches, service disruptions, and a loss of trust. Consequently, organizations require an effective and efficient approach to assess and analyze the security of acquired web-based software, ensuring sufficient confidence in its utilization. This research aims to enhance the quantitative evaluation and analysis of web application security through a model-based approach. We focus on integrating the Open Web Application Security Project s (OWASP) Application Security Verification Standard (ASVS) into a structured and analyzable metamodel. This model aims to effectively assess the security levels of web applications while offering valuable insights into their strengths and weaknesses. By combining the ASVS with a comprehensive framework, we aim to provide a robust methodology for evaluating and analyzing web application security.

Security still remains an afterthought in modern Electronic Design Automation (EDA) tools, which solely focus on enhancing performance and reducing the chip size. Typically, the security analysis is conducted by hand, leading to vulnerabilities in the design remaining unnoticed. Security-aware EDA tools assist the designer in the identification and removal of security threats while keeping performance and area in mind. Stateof-the-art approaches utilize information flow analysis to spot unintended information leakages in design structures. However, the classification of such threats is binary, resulting in negligible leakages being listed as well. A novel quantitative analysis allows the application of a metric to determine a numeric value for a leakage. Nonetheless, current approximations to quantify the leakage are still prone to overlooking leakages. The mathematical model 2D-QModel introduced in this work aims to overcome this shortcoming. Additionally, as previous work only includes a limited threat model, multiple threat models can be applied using the provided approach. Open-source benchmarks are used to show the capabilities of 2D-QModel to identify hardware Trojans in the design while ignoring insignificant leakages.

The perception of security when consumers use the m-fintech payment application impacts satisfaction and continuance intention. However, data security threats and legal breaches have made consumers skeptical about the continuance of m-fintech payments. Therefore, this study aims to analyze the perceived security factor as a form of consumer satisfaction and the desire to continue using it with the support of confirmation behavior. This study uses a quantitative method by surveying 357 m-fintech payment users in Jabodetabek. All collected data has been processed, cleaned, and analyzed utilizing variance-based Structural Equation Modeling statistics. The research finding has proven that all hypotheses are accepted. Perceived security significantly affects confirmation, satisfaction, and continuance intention. A confirmation significantly affects satisfaction, and satisfaction significantly affects the continuance intention of mfintech payment. The originality of this research measures perceived security formatively. The conclusions of this analysis serve as information for the digital central currency bank (CDBC) development plan based on the security level.

The growth of Electric Vehicles (EVs), coupled with the deployment of large-scale extreme fast charging stations (XFCSs), has increased the attack surface for EV ecosystems. To secure such critical cyber-physical systems (CPSs), it is imperative for the system defenders to perform an in-depth analysis of potential attack vectors, evaluate possible countermeasures, and analyze attack-defense scenarios quantitatively to implement a defense strategy that will provide maximum utilization of their limited resources. Therefore, a systematic framework is essential, relying on modeling tools that security experts are familiar with. In this paper, we propose a comprehensive methodology for enabling the defender to perform a high-level attack surface analysis of an XFCS and determine the defense strategy with the highest utility value. We apply STRIDE threat modeling and attack defense tree (ADT) to enumerate realizable attack paths and identify possible defense measures. We then employ analytic hierarchy process (AHP) as a multi-criteria decisionmaking algorithm to obtain the highest utility strategy for the defender to adopt. The proposed methodology is validated by demonstrating its real-world feasibility through a case study, using sample attack paths for an XFCS.

The escalating visibility of secure direct object reference (IDOR) vulnerabilities in API security, as indicated in ⁠ the compilation of OWASP Top 10 API Security Risks, highlights a noteworthy peril to sensitive data. This study explores IDOR vulnerabilities found within Android APIs, intending to clarify their inception while evaluating their implications for application security. This study combined the qualitative and quantitative approaches. Insights were obtained from an actual penetration test on an Android app into the ⁠ primary reasons for IDOR vulnerabilities, underscoring insufficient input validation and weak authorization methods. We stress the frequent occurrence of IDOR vulnerabilities in the OWASP Top 10 API ⁠ vulnerability list, highlighting the necessity to prioritize them in security evaluations. There are mitigation recommendations available for developers, which recognize its limitations involving a possibly small and homogeneous selection ⁠ of tested Android applications, the testing environment that could cause some inaccuracies, and the impact of time constraints. Additionally, the study noted insufficient threat modeling and root ⁠ cause analysis, affecting its generalizability and real-world relevance. However, comprehending and controlling IDOR dangers can enhance Android API ⁠ security, protect user data, and bolster application resilience.

Network security is a problem that is of great concern to all countries at this stage. How to ensure that the network provides effective services to people without being exposed to potential security threats has become a major concern for network security researchers. In order to better understand the network security situation, researchers have studied a variety of quantitative assessment methods, and the most scientific and effective one is the hierarchical quantitative assessment method of the network security threat situation. This method allows the staff to have a very clear understanding of the security of the network system and make correct judgments. This article mainly analyzes the quantitative assessment of the hierarchical network security threat situation from the current situation and methods, which is only for reference.