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- MakaleAçık Erişim2026Scopus SJRQ1Real-time photovoltaic voltage data-driven dynamic green s-box generation framework for smart grid security
Aydın, Yılmaz; Garipcan, Ali Murat; Özkaynak, Fatih
In this study, a dynamic substitution box (s-box) generation method is proposed using real-time voltage data obtained from photovoltaic (PV) panels as an environmentally sensitive entropy source. These data, affected by environmental conditions such as solar radiation and temperature, exhibit irregular and unpredictable temporal behavior, offering strong potential for cryptographic randomness generation. In this context, the 0–1 test, Kolmogorov Entropy (KE), scale-index analysis, and the National Institute of Standards and Technology (NIST) SP 800-22 test suite are applied to PV voltage data collected at 1-minute intervals, experimentally confirming their chaotic dynamics and high-entropy characteristics. Following appropriate preprocessing and nonlinear mathematical transformations, the validated data are utilized to generate 8-bit s-box structures. The cryptographic strength of the generated s-boxes is quantitatively evaluated using standard security metrics, including nonlinearity (NL), Differential Probability (DP), Linear Probability (LP), Strict Avalanche Criterion (SAC), and Bit Independence Criterion (BIC). The findings reveal that PV data can serve as a functional resource not only for energy monitoring but also for randomness-based cryptographic construction. This approach enables lightweight cryptographic solutions for resource-constrained edge devices requiring <1 KB of memory and supports context-aware data security in renewable energy infrastructures.
- MakaleAçık Erişim2025Scopus SJRQ1An efficient 2D hyper chaos and DNA encoding-based s-box generation method using chaotic evolutionary improvement algorithm for nonlinearity
Garipcan, Ali Murat; Aydin, Yılmaz; Özkaynak, Fatih
In this study, an innovative substitution box (s-box) method is proposed, which combines the complexity and unpredictability of chaotic systems with the natural randomness and security features of Deoxyribonucleic Acid (DNA) encoding, in response to the increasing security requirements in the field of modern cryptography. This method, based on the integration of a two-dimensional (2D) hyper-chaotic Vincent map (VM) and DNA encoding techniques, aims to produce secure and high-performance s-boxes. To evaluate the reliability of the s-boxes, fundamental cryptographic criteria such as nonlinearity (NL), strict avalanche criterion (SAC), differential probability (DP), linear approximation probability (LAP), and bit independence criterion (BIC) are considered. Additionally, a novel chaos-based evolutionary optimization algorithm is proposed to optimize the NL criterion of the s-boxes. This algorithm offers a cost-effective and highly efficient alternative compared to classical metaheuristic methods, providing a balanced structure between security and performance. Experimental findings and comparison results demonstrate that the proposed s-boxes offer effective and reliable solutions for modern cryptographic applications, such as secure data transmission and storage. From a broader perspective, the study makes a meaningful contribution to the literature in the field of data security by presenting a high-performance s-box design meeting the security requirements of cryptographic systems and is resilient against current threats.
AtıfScopus25WoS26OpenAlex23
İncele - MakaleAçık Erişim2019AHP–TOPSIS integration extended with Pythagorean fuzzy sets for information security risk analysis
Ak, M. Fatih; Gul, Muhammet
Risk analysis (RA) contains several methodologies that object to ensure the protection and safety of occupational stakeholders. Multi attribute decision-making (MADM) is one of the most important RA methodologies that is applied to several areas from manufacturing to information technology. With the widespread use of computer networks and the Internet, information security has become very important. Information security is vital as institutions are mostly dependent on information, technology, and systems. This requires a comprehensive and effective implementation of information security RA. Analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are commonly used MADM methods and recently used for RA. In this study, a new RA methodology is proposed based on AHP–TOPSIS integration extended with Pythagorean fuzzy sets. AHP strengthened by interval-valued Pythagorean fuzzy numbers is used to weigh risk parameters with expert judgment. Then, TOPSIS with Pythagorean fuzzy numbers is used to prioritize previously identified risks. A comparison of the proposed approach with three approaches (classical RA method, Pythagorean fuzzy VIKOR and Pythagorean fuzzy MOORA) is also provided. To illustrate the feasibility and practicality of the proposed approach, a case study for information security RA in corrugated cardboard sector is executed.
AtıfScopus152WoS128OpenAlex167İncele