The integration of low Earth orbit (LEO) satellite communication into 6G networks promises a transformative impact on global connectivity by expanding coverage to remote regions and enhancing service reliability. However, this new infrastructure also introduces significant security challenges due to its expansive attack surface. To address this concern, we propose a dynamic security functions allocation (SFA) model that optimizes the allocation of security functions (SFs) across satellites while considering computational resource limitations, dynamic topology changes, and the visibility constraints of satellite constellations. Our model leverages the flexibility of 6G network slicing (NS) to share non-critical SFs between slices, reducing resource overhead while maintaining essential security demands. To minimize the risk of sharing highly sensitive SFs between slices, our model employs a nonlinear penalty, which prioritizes minimizing risk by aggressively penalizing high-risk SFs sharing. This dynamic risk management framework assesses the probability and impact of security breaches, ensuring that SFs are shared only when the security risk is acceptable, balancing resource efficiency and security. By dynamically adapting to the network's operational conditions, our approach provides a robust framework for efficient and secure satellite communication in 6G networks. Simulation results demonstrate the model's flexibility in managing trade-offs across key network performance metrics.

The low Earth orbit (LEO) satellite megaconstellation can provide ubiquitous coverage and high-performance connectivity, supporting multi-slice applications with various key performance indicator (KPI) requirements. However, due to the dynamic nature of LEO satellites, limited resources, and the diverse demands of different slices, managing user association (UA) and resource allocation becomes an increasingly challenging task in areas with overlapping satellite coverage. This paper proposes a joint optimization model for UA and resource allocation in multi-slice LEO satellite networks (SLSNs). Based on mixed-integer non-linear programming (MILP), our model minimizes the total propagation delay and optimizes the demand satisfaction ratio (DSR) using a Max-Min approach to ensure each slice meets its unique throughput requirements. In addition, a visibility-aware component is incorporated to prioritize longer satellite visibility, reduce handovers, and improve network stability. Due to the computational complexity of the MILP model, we propose a heuristic-based balanced association with delay-aware bandwidth distribution (B-DAD) approach. B-DAD operates in two phases: the initial UA phase selects satellites based on a combined metric of delay, load, and visibility duration, while the residual bandwidth distribution phase reallocates unused bandwidth among associated users proportionally. Extensive simulations demonstrate that our approaches significantly improve DSR, propagation delays, transmission delays, and network stability compared to the widely adopted benchmark maximum sum of data rate (Max-SR) method under varying elevation angles. Our findings highlight the effectiveness of the MILP model in achieving optimal solutions and the efficiency of B-DAD as a scalable alternative for large-scale scenarios.

Virtualized Network Function (VNF) sharing among multiple Fifth Generation (5G) slices allows network operators to increase the efficiency and utilization of the network. However, this sharing of VNFs can result in a degradation of the performance of the slices in the presence of an attack. In this paper, we evaluate the impact of flooding attacks on the performance of 5G slices with different VNF sharing configurations. We consider two VNF sharing configurations, in the first configuration, the Session Management Function (SMF) and User Plane Function (UPF) are shared among the deployed slices, while the SMF and UPF of the slices are isolated in the second configuration. The performance of these configurations is evaluated using different traffic types under two flooding attack scenarios; a ping flood attack targeting the data plane of 5G network, and a registration request flood attack directed at the control plane of 5G network. Our results showed different responses in the control and data planes. In the data plane, isolating VNFs of the slices provides better performance and mitigates the adverse effects of the attacks studied.

A document by Mohammed Mahyoub . Click on the document to view its contents.