## 1 Introduction
### Methodology  
This study is based on a multidimensional literature review focusing on emerging security solutions at the intersection of AI, IoE, Blockchain, and Quantum Computing technologies. The methodological approach is based on both the selection of technical literature and the structuring of content along specific thematic axes. The methodological framework is explained step by step below:  
1. _Database and Publication Selection_: Studies published in peer-reviewed journals indexed in leading academic databases such as IEEE Xplore, Elsevier ScienceDirect, Springer, MDPI, Wiley, ACM, and Taylor & Francis were selected. In the selection process, no publisher priority was applied; instead, the content relevance, contribution value, and recency of the studies were prioritized. 2. _Inclusion Criteria_: The following criteria were used to include literature in the study: * Studies analyzing multi-layered security threats (physical, network, data, application layers) in IoE environments, * Architectures integrating blockchain-based decentralized security solutions into IoE, * AI-supported security models (particularly Edge AI, Federated Learning, Anomaly Detection), * Studies focusing on post-quantum cryptography (PQC) and quantum-resilient system solutions, * Literature examining methods such as ABAC, SMPC, and Zero-Knowledge Proof in the context of data privacy and access control, * Publications that include systematic proposals, architectural models, and comparative analyses at the intersection of multiple technologies. 3. _Keyword-Based Search_: The literature review was conducted using keyword combinations. Prominent terms include: \"Edge AI security\", \"Blockchain-enabled IoT\", \"quantum-resistant cryptography\", \"ABAC in IoT\", \"Federated Learning for edge devices\", \"IoE security threats\", \"IoT anomaly detection\", \"zero-trust IoT architecture\", \"quantum-safe identity\", \"cross-domain healthcare blockchain\", and similar expressions. 4. _Thematic Structuring of Content_: The content of the study was designed based on a predefined thematic plan (table of content). The main topics of the review, IoE security, privacy, and quantum-resilient solutions, have been systematically structured within a multi-layered content framework. In the first stage, the security vulnerabilities and new-generation attack types in IoE environments were addressed. Threats such as identity management, data privacy, centralized and decentralized security structures, and adversarial AI-based threats were systematically classified. Subsequently, the solution methods developed against these threats were examined under three main axes: blockchain-based architectures, end-to-end security through edge AI systems, and quantum-resilient cryptographic approaches. In this context, not only theoretical models but also technical applications based on sectoral scenarios were analyzed. Additionally, within the scope of this study, a multi-layered security architecture is proposed that integrates the mentioned security technologies both horizontally by functional layers and vertically by application domains. In the subsequent sections, comparative analyses of the security technologies were conducted based on criteria such as performance, applicability, and integration level. Various solutions were thematically classified according to security layers and system architectures. Finally, in the last section of the study, the limitations of current security systems were comprehensively evaluated. The increasing security demands and systemic bottlenecks arising from the scaling of IoE were revealed. In this context, areas requiring architectural transformation to address post-quantum threats were highlighted, and new research topics were proposed both on technological and interdisciplinary levels. Thus, the study provides a holistic assessment that not only classifies existing solutions but also presents long-term strategic approaches to IoE security. 5.