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Yayın ANN activation function estimators for homomorphic encrypted inference(Institute of Electrical and Electronics Engineers Inc., 2025-06-13) Harb, Mhd Raja Abou; Çeliktaş, BarışHomomorphic Encryption (HE) enables secure computations on encrypted data, facilitating machine learning inference in sensitive environments such as healthcare and finance. However, efficiently handling non-linear activation functions, specifically Sigmoid and Tanh, remains a significant computational challenge for encrypted inference using Artificial Neural Networks (ANNs). This study introduces a lightweight, ANN-based estimator designed to accurately approximate activation functions under homomorphic encryption. Unlike traditional polynomial and piecewise linear approximations, the proposed ANN estimators achieve superior accuracy with lower computational overhead associated with bootstrapping or high-degree polynomial techniques. These estimators are trained on plaintext data and seamlessly integrated into encrypted inference pipelines, significantly outperforming conventional methods. Experimental evaluations demonstrate notable improvements, with ANN estimators enhancing accuracy by approximately 2% for Sigmoid and up to 73% for Tanh functions, improving F1-scores by approximately 2% for Sigmoid and up to 88% for Tanh, and markedly reducing Mean Square Error (MSE) by up to 96% compared to polynomial approximations. The ANN estimator achieves an accuracy of 97.70% and an AUC of 0.9997 when integrated into a CNN architecture on the MNIST dataset, and an accuracy of 85.25% with an AUC of 0.9459 on the UCI Heart Disease dataset during ciphertext inference. These results underscore the estimator’s practical effectiveness and computational feasibility, making it suitable for secure and efficient ANN inference in encrypted environments.Yayın A hierarchical key assignment scheme: a unified approach for ccalability and efficiency(IEEE, 2024-05-24) Çelikbilek, İbrahim; Çeliktaş, Barış; Özdemir, EnverThis study introduces a hierarchical key assignment scheme (HKAS) based on the closest vector problem in an inner product space (CVP-IPS). The proposed scheme offers a comprehensive solution with scalability, flexibility, cost-effectiveness, and high performance. The key features of the scheme include CVP-IPS based construction, the utilization of two public keys by the scheme, a distinct basis set designated for each class, a direct access scheme to enhance user convenience, and a rigorous mathematical and algorithmic presentation of all processes. This scheme eliminates the need for top-down structures and offers a significant benefit in that the lengths of the basis sets defined for classes are the same and the costs associated with key derivation are the same for all classes, unlike top-down approaches, where the higher class in the hierarchy generally incurs much higher costs. The scheme excels in both vertical and horizontal scalability due to its utilization of the access graph and is formally proven to achieve strong key indistinguishability security (S-KI-security). This research represents a significant advancement in HKAS systems, providing tangible benefits and improved security for a wide range of use cases.Yayın Relationships among organizational-level maturities in artificial intelligence, cybersecurity, and digital transformation: a survey-based analysis(Institute of Electrical and Electronics Engineers Inc., 2025-05-19) Kubilay, Burak; Çeliktaş, BarışThe rapid development of digital technology across industries has highlighted the growing need for enhanced competencies in Artificial Intelligence (AI), Cyber security (CS), and Digital Transformation (DT). While there is extensive research on each of these domains in isolation, few studies have investigated their relationship and joint impact on organizational maturity. This study aims to address this gap by analyzing the relationships among the maturity levels of AI, CS, and DT at the organizational level using Structural Equation Modeling (SEM) and descriptive statistical methods. A mixed-methods design combines quantitative survey data with synthetic modeling techniques to assess organizational preparedness. The findings demonstrate significant bidirectional correlations among AI, CS, and DT, with technology and finance being more advanced than government and education. The research highlights the necessity of an integrated AI-CS strategy and provides actionable recommendations to increase investments in these domains. In contrast to the preceding fragmented evaluations, the current research establishes a comprehensive, empirically grounded framework that acts as a strategic reference point for digital resilience. Follow-up studies will involve collecting real-world industry data in support of empirical validation and predictive ability in measuring AI and CS maturity. This research adds to the existing literature by filling the gaps among fragmented digital maturity models and providing a consistent empirical base for organizations to thrive in an evolving technological environment.Yayın Analyst-aware incident assignment in security operations centers: a multi-factor prioritization and optimization framework(Uğur Şen, 2025-07-15) Kılınçdemir, Eyüp Can; Çeliktaş, BarışIn this paper, we propose a comprehensive and scalable framework for incident assignment and prioritization in Security Operations Centers (SOCs). The proposed model aims to optimize SOC workflows by addressing key operational challenges such as analyst fatigue, alert overload, and inconsistent incident handling. Our framework evaluates each incident using a multi-factor scoring model that incorporates incident severity, service-level agreement (SLA) urgency, incident type, asset criticality, threat intelligence indicators, frequency of repetition, and a correlation score derived from historical incident data. We formalize this evaluation through a set of mathematical functions that compute a dynamic incident score and derive incident complexity. In parallel, analyst profiles are quantified using Analyst Load Factor (ALF) and Experience Match Factor (EMF), two novel metrics that account for both workload distribution and expertise alignment. The incident–analyst matching process is expressed as a constrained optimization problem, where the final assignment score is computed by balancing incident priority with analyst suitability. This formulation enables automated, real-time assignment of incidents to the most appropriate analysts, while ensuring both operational fairness and triage precision. The model is validated using algorithmic pseudocode, scoring tables, and a simplified case study, which illustrates the realworld applicability and decision logic of the framework in large-scale SOC environments. To validate the framework under real-world conditions, an empirical case study was conducted using 10 attack scenarios from the CICIDS2017 benchmark dataset. Overall, our contributions lie in the formalization of a dual-factor analyst scoring scheme and the integration of contextual incident features into an adaptive, rule-based assignment framework. To further strengthen operational value, future work will explore adaptive weighting mechanisms and integration with real-time SIEM pipelines. Additionally, feedback loops and supervised learning models will be incorporated to continuously refine analyst-incident matching and prioritization.Yayın Evaluation of password hashing competition finalists: performance, security, compliance mapping, and post-quantum readiness(Karyay Karadeniz Yayımcılık Ve Organizasyon Ticaret Limited Şirketi, 2025-11-15) Ulutaş, Erdem; Çeliktaş, BarışPassword hashes and key derivation functions (KDFs) are central to authentication and cryptographic security schemes crafted to defend user credentials from brute-force attacks and unauthorized access. Password hashing algorithms, for example PBKDF2, bcrypt, or scrypt, are very popular today, but are lacking in the face of modern hardware acceleration, parallel processing, and advanced cryptanalytic attacks. To contest these shortcomings, the Password Hashing Competition (PHC) was started in 2013 and had 22 candidates for functions for hashing passwords. After thorough evaluation, 9 finalists were selected based on how secure, fast, memory-friendly, flexible, and efficient these functions were. This study evaluates the nine PHC finalists—Argon2, battcrypt, Catena, Lyra2, MAKWA, Parallel, POMELO, Pufferfish, and yescrypt—through survey findings and performance benchmarks. We have evaluated these functions from an architectural standpoint and studied their security features, memory hardness, performance tradeoff, and practical usage. We also compare these finalists with traditional password hashing functions to highlight their advantages and limitations. We also investigate the post-quantum assumption for password hashing – the effectiveness of these functions against quantum assaults, their position in a new cryptography set, and the role of peppering as an additional security measure. In addition, we perform a comprehensive compliance mapping of the PHC finalists against major global standards and regulations such as NIST SP 800-63B, OWASP ASVS, PCI DSS, GDPR, KVKK, and ISO/IEC 27001, highlighting their practical suitability for secure deployment in regulated environments. Finally, we provide usage recommendations for these functions for web authentication, KDFs, and embedded platforms. This paper serves as a reference for researchers, developers, and security engineers, while also introducing a complianceaware, post-quantum-ready framework that bridges cryptographic design with regulatory and deployment needs.Yayın An analysis of enterprise-level cloud transition barriers within the Technology-Organization-Environment (TOE) framework and strategic solution proposals(Gazi Üniversitesi, 2025-10-31) Çeliktaş, Barış; Birgin, Berat; Tok, Mevlüt SerkanEnterprise-level transitions to cloud service providers are frequently delayed or disrupted due to the multilayered nature of technical, organizational, and legal barriers. This study classifies these obstacles within the TechnologyOrganization-Environment (TOE) theoretical framework and provides a comprehensive analysis. Methodologically, a triangulated data source approach was adopted, combining systematic literature review, the 2025 Flexera Cloud Report, and Cloud Adoption Framework (CAF) documentation from major providers such as AWS, Azure, and Google Cloud. Findings indicate that technological barriers particularly cryptographic complexity, cost unpredictability, and weak system integration, are the most dominant. These barriers were visually modeled, and the structural interdependencies among five core cryptographic components (key management, secure computation, algorithm selection, access control, and regulatory compliance) were illustrated through a flow diagram. By aligning FinOps and compliance-oriented solution strategies with the TOE framework, the study offers a strategic roadmap for decision-makers and cloud architects planning cloud adoption. It links conceptual models to applied practices, providing structured support for organizations seeking to mature their cloud strategy.Yayın A multi-criteria evaluation of cybersecurity incident management frameworks: integrating AHP, CMMI and SWOT(Karyay Karadeniz Yayımcılık Ve Organizasyon Ticaret Limited Şirketi, 2026-01-15) Ağar, Hasan Çağlar; Çeliktaş, BarışWith the growing complexity and frequency of cybersecurity incidents, the selection of an appropriate incident management framework has emerged as a strategic imperative and a nontrivial decision-making problem for organizations operating across diverse sectors. This study presents a multi-dimensional evaluation of four globally recognized frameworks and standards—ISO 27035, NIST 800-61, ITIL v4, and PCI DSS—to determine their effectiveness across 10 rigorously selected key performance parameters. The initial stage of the study involved the identification of 20 preliminary parameters through expert input and literature synthesis. These were then evaluated by 70 cybersecurity professionals using a hybrid decision-making model combining Likert scale scoring, standard deviation filtering, CV score, Z-score normalization and the Analytic Hierarchy Process (AHP) for pairwise comparisons. The top 10 key parameters were derived based on calculated priority weights. To assess each framework, we applied the Capability Maturity Model Integration (CMMI) and visualized results via radar charts and heatmaps, offering comparative insights into operational maturity. Additionally, SWOT analysis was conducted to examine strategic positioning and identify opportunities for improvement. The outcomes not only provide a practical benchmarking guide for practitioners but also introduce a replicable, evidence-based methodology for academic and industry adoption. This work offers a novel and structured lens to evaluate incident management maturity, addressing the pressing need for strategic alignment, automation integration, and adaptive resilience in cybersecurity operations.Yayın Hierarchical secure key assignment scheme(Public Library of Science, 2026-02-18) Çeliktaş, Barış; Çelikbilek, İbrahim; Güzey, Süeda; Özdemir, EnverThis work presents a novel hierarchical key assignment mechanism for access control, designed to be computationally lightweight and optimized for digital environments with structured access policies. By leveraging orthogonal projection and distributing a basis to each group, it enables flexible and efficient left-to-right and top-down access structures. The scheme ensures that parent groups can derive the secret keys of their child groups while preventing unauthorized reverse access. It is resilient against collusion attacks and privilege escalation, offering robust key recovery and indistinguishability properties. Moreover, it guarantees strong key indistinguishability under adversarial models and facilitates a secure rekeying process without reliance on a trusted third party. To demonstrate practical efficiency, we provide a full analytical complexity evaluation showing that key derivation requires at most ∂(n2i ) operations, where ni is the dimension of the assigned subspace. For typical deployment parameters used in the experiments, the total key material per user remains compact (≈ 3,072 bits), significantly smaller than well-known post-quantum schemes such as Dilithium-5 (38,912 bits). The storage requirement scales linearly with the number of groups (ck+1 bases for c groups with at most k members), ensuring that even large hierarchies remain lightweight. Our evaluation further shows that selective rekeying affects only the descendants of the modified group, resulting in communication overhead of ∂(m′λ) bits, where m′ is the number of affected users and λ is the key length. These results collectively highlight the scheme’s scalability, low storage footprint, and suitability for large access hierarchies.
