This context-aware emotion-based model can help design intelligent agents for group decision making processes. Experiments show that agents with emotional awareness reach agreement more quickly than those without it.

This paper explores the security challenges associated with network slicing in 5th Generation (5G) networks, a technology that enables the creation of virtual networks tailored to different use cases. This study contributes to network slicing research efforts by providing a comprehensive classification of attacks aligned with the architectural layers of 5G, complemented by practical mitigation approaches suitable for multi-tenant environments. The classification depicts specific attacks and categorizes vulnerabilities across layers such as orchestration, virtualization, and inter-slice communication. Additionally, mitigation strategies are discussed, emphasizing the importance of real-time monitoring and robust access controls. The proposed classification aims to support the development of advanced security mechanisms, including risk assessment models and automated mitigation strategies, tailored to the dynamic and heterogeneous nature of 5G slicing. The findings highlight the need for layered defenses, AI-driven monitoring, and architectural isolation as critical components to enhance the resilience of 5G slicing deployments.