Demo: Secure Edge Server for Network Slicing and Resource Allocation in Open RAN

• URL: http://arxiv.org/abs/2507.11499v1
• Date: Sun, 13 Jul 2025 03:55:04 GMT
• Title: Demo: Secure Edge Server for Network Slicing and Resource Allocation in Open RAN
• Authors: Adhwaa Alchaab, Ayman Younis, Dario Pompili,
• Abstract summary: Next-Generation Radio Access Networks (NGRAN) aim to support diverse vertical applications with strict security, latency, and Service-Level Agreement (SLA) requirements.<n>This demo presents SnSRIC, a secure and intelligent network slicing framework that mitigates a range of Distributed Denial-of-Service (DDoS) attacks in Open RAN environments.
• Score: 6.347093870433103
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Next-Generation Radio Access Networks (NGRAN) aim to support diverse vertical applications with strict security, latency, and Service-Level Agreement (SLA) requirements. These demands introduce challenges in securing the infrastructure, allocating resources dynamically, and enabling real-time reconfiguration. This demo presents SnSRIC, a secure and intelligent network slicing framework that mitigates a range of Distributed Denial-of-Service (DDoS) attacks in Open RAN environments. SnSRIC incorporates an AI-driven xApp that dynamically allocates Physical Resource Blocks (PRBs) to active users while enforcing slice-level security. The system detects anomalous behavior, distinguishes between benign and malicious devices, and uses the E2 interface to throttle rogue signaling while maintaining service continuity for legitimate users.

Related papers

• Rogue Cell: Adversarial Attack and Defense in Untrusted O-RAN Setup Exploiting the Traffic Steering xApp [24.941343115166436]
  Open Radio Access Network (O-RAN) architecture is revolutionizing cellular networks with its open, multi-vendor design and AI-driven management.<n>Previous studies have mainly examined vulnerabilities arising from O-RAN's intelligent components.<n>This paper is the first to focus on the security challenges and vulnerabilities introduced by transitioning from single-operator to multi-operator RAN architectures.
  arXiv  Detail & Related papers  (2025-05-03T13:19:44Z)
• Integrated LLM-Based Intrusion Detection with Secure Slicing xApp for Securing O-RAN-Enabled Wireless Network Deployments [2.943640991628177]
  The Open Radio Access Network (O-RAN) architecture is reshaping telecommunications by promoting openness, flexibility, and intelligent closed-loop optimization.<n>This research explores using large language models (LLMs) to generate security recommendations based on the temporal traffic patterns of connected UEs.
  arXiv  Detail & Related papers  (2025-04-01T01:45:07Z)
• SafeSlice: Enabling SLA-Compliant O-RAN Slicing via Safe Deep Reinforcement Learning [20.344810727033327]
  Deep reinforcement learning (DRL)-based slicing policies face challenges in physical systems such as open radio access networks (O-RANs)<n>These policies often lack safety guarantees to ensure compliance with service level agreements (SLAs)<n>We propose SafeSlice to address both the cumulative (trajectory-wise) and instantaneous (state-wise) latency constraints of O-RAN slices.
  arXiv  Detail & Related papers  (2025-03-17T02:41:49Z)
• Fundamental Limits of Hierarchical Secure Aggregation with Cyclic User Association [93.46811590752814]
  Hierarchical secure aggregation is motivated by federated learning (FL)<n>In this paper, we consider HSA with a cyclic association pattern where each user is connected to $B$ consecutive relays.<n>We propose an efficient aggregation scheme which includes a message design for the inputs inspired by gradient coding.
  arXiv  Detail & Related papers  (2025-03-06T15:53:37Z)
• Securing the Open RAN Infrastructure: Exploring Vulnerabilities in Kubernetes Deployments [60.51751612363882]
  We investigate the security implications of and software-based Open Radio Access Network (RAN) systems. We highlight the presence of potential vulnerabilities and misconfigurations in the infrastructure supporting the Near Real-Time RAN Controller (RIC) cluster.
  arXiv  Detail & Related papers  (2024-05-03T07:18:45Z)
• ZTRAN: Prototyping Zero Trust Security xApps for Open Radio Access Network Deployments [2.943640991628177]
  Open radio access network (O-RAN) offers new degrees of freedom for building and operating advanced cellular networks. This paper proposes leveraging zero trust principles for O-RAN security. We introduce zero trust RAN (ZTRAN), which embeds service authentication, intrusion detection, and secure slicing subsystems that are encapsulated as xApps.
  arXiv  Detail & Related papers  (2024-03-06T23:57:16Z)
• Sparsity-Aware Intelligent Massive Random Access Control in Open RAN: A Reinforcement Learning Based Approach [61.74489383629319]
  Massive random access of devices in the emerging Open Radio Access Network (O-RAN) brings great challenge to the access control and management. reinforcement-learning (RL)-assisted scheme of closed-loop access control is proposed to preserve sparsity of access requests. Deep-RL-assisted SAUD is proposed to resolve highly complex environments with continuous and high-dimensional state and action spaces.
  arXiv  Detail & Related papers  (2023-03-05T12:25:49Z)
• Artificial Intelligence Empowered Multiple Access for Ultra Reliable and Low Latency THz Wireless Networks [76.89730672544216]
  Terahertz (THz) wireless networks are expected to catalyze the beyond fifth generation (B5G) era. To satisfy the ultra-reliability and low-latency demands of several B5G applications, novel mobility management approaches are required. This article presents a holistic MAC layer approach that enables intelligent user association and resource allocation, as well as flexible and adaptive mobility management.
  arXiv  Detail & Related papers  (2022-08-17T03:00:24Z)
• Predictive Closed-Loop Service Automation in O-RAN based Network Slicing [35.23159175375706]
  Open radio access network (O-RAN) is perhaps the most promising RAN architecture that inherits all the aforementioned features. This article provides a closed-loop and intelligent resource provisioning scheme for O-RAN slicing to prevent SLA violations.
  arXiv  Detail & Related papers  (2022-02-04T04:34:00Z)
• Safe RAN control: A Symbolic Reinforcement Learning Approach [62.997667081978825]
  We present a Symbolic Reinforcement Learning (SRL) based architecture for safety control of Radio Access Network (RAN) applications. We provide a purely automated procedure in which a user can specify high-level logical safety specifications for a given cellular network topology. We introduce a user interface (UI) developed to help a user set intent specifications to the system, and inspect the difference in agent proposed actions.
  arXiv  Detail & Related papers  (2021-06-03T16:45:40Z)
• Symbolic Reinforcement Learning for Safe RAN Control [62.997667081978825]
  We show a Symbolic Reinforcement Learning (SRL) architecture for safe control in Radio Access Network (RAN) applications. In our tool, a user can select a high-level safety specifications expressed in Linear Temporal Logic (LTL) to shield an RL agent running in a given cellular network. We demonstrate the user interface (UI) helping the user set intent specifications to the architecture and inspect the difference in allowed and blocked actions.
  arXiv  Detail & Related papers  (2021-03-11T10:56:49Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.