Murat: Multi-RAT False Base Station Detector

Nakarmi, Prajwol Kumar; Ersoy, Mehmet Akif; Soykan, Elif Üstündağ; Norrman, Karl

doi:10.48550/arxiv.2102.08780

Cited by 4 publications

(8 citation statements)

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“…While we can employ learning-based frameworks (e.g., automata-based [22] and machine-learningbased [2]), they fall short due to the availability of abundant adversary training samples in public [22]. Besides, existing cellular IDS frameworks are mostly static with relatively low flexibility [24], [23], [26], [42]. To achieve this design goal, we build a flexible rule-based expert system that enables users (e.g., network operators) to easily integrate exploit detection signatures in a programmatic manner.…”

Section: B Design Goals and Challengesmentioning

confidence: 99%

“…CELLDAM provides a root-less defense by using a companion data-plane signal analyzer [54]. On the other hand, such monitors can also be deployed at the networks (RAN), such as heuristics-based fake base station detectors [24], [55], [56], [25], [26], [57], [58], and anomalous traffic classifiers [59], [60], [61]. While our system can be viewed as a run-time monitor, it is distinguished from the above works for being the first defense at the 5G O-RAN control plane that offers programmability and extensibility.…”

Section: Related Workmentioning

confidence: 99%

“…After luring nearby victim UE to connect, the FBS then transmits malicious messages to perform DoS or privacy leakage attacks, which are also known as IMSI catchers in legacy 2G and 3G networks [42], [23]. We consider these attacks can be detected by using existing FBS detection (or IMSI catcher detection) techniques [42], [23], [24], [57], [26]. Such techniques, which rely on signal strengths, measurement reports, and other heuristics, can also be deployed at the O-RAN control plane.…”

Section: Other Cellular L3 Attacksmentioning

confidence: 99%

“…We consider this a general limitation for all defenses deployed at the RAN and not unique to 5G-SPECTOR, since the current vulnerable cellular standard lacks verification mechanisms on unprotected L3 messages. set, : Not detectable, ▲: Has been addressed by fake base station detection techniques [24], [26], [42]).…”

Section: Other Cellular L3 Attacksmentioning

confidence: 99%

“…These attacks originate from the vulnerabilities in earlier generations of cellular protocols but most of them still apply in 5G standards [10], [18]. However, while there are existing defenses that address a subset of these attacks from either the UE side [22], [23] or the network side [24], [25], [26], they fall short in having a limited view (e.g., UE-centric defenses cannot detect RAN-targeted attacks [22], [23]) or poor extensibility (e.g., network-based solutions with static defense mechanisms [24], [25], [26]).…”

Section: Introductionmentioning

confidence: 99%

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5G-Spector: An O-RAN Compliant Layer-3 Cellular Attack Detection Service

Wen,

Porras,

Yegneswaran

et al. 2024

Proceedings 2024 Network and Distributed System Security Symposium

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Over the past several years, the mobile security community has discovered a wide variety of exploits against link and session-establishment protocols. These exploits can be implemented on software-defined radios (SDRs) that disrupt, spoof, or flood layer-3 (L3) messages to compromise security and privacy, which still apply to the latest 5G mobile network standard. Interestingly, unlike the prior generations of closed (proprietary) mobile network infrastructures, 5G networks are migrating toward a more intelligent and open-standards-based fully interoperable mobile architecture, called Open RAN or O-RAN. The implications of transitioning mobile infrastructures to a software-defined architectural abstraction are quite significant to the INFOSEC community, as it allows us to extend the mobile data plane and control plane with security-focused protocol auditing services and exploit detection. Based on this design, we present 5G-SPECTOR, the first comprehensive framework for detecting the wide spectrum of L3 protocol exploits on O-RAN. It features a novel security audit stream called MOBIFLOW that transfers fine-grained cellular network telemetry, and a programmable control-plane xApp called MOBIEXPERT. We present an extensible prototype of 5G-SPECTOR which can detect 7 types of cellular attacks in real-time. We also demonstrate its scalability to 11 unknown attacks as well as 31 real-world cellular traces, with effective performance (high accuracy, no false alarms) and low (<2% CPU, <100 MB memory) overhead.

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Section: B Design Goals and Challengesmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Other Cellular L3 Attacksmentioning

confidence: 99%

Section: Other Cellular L3 Attacksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

5G-Spector: An O-RAN Compliant Layer-3 Cellular Attack Detection Service

Wen,

Porras,

Yegneswaran

et al. 2024

Proceedings 2024 Network and Distributed System Security Symposium

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You have been warned: Abusing 5G’s Warning and Emergency Systems

Bitsikas

Pöpper

2022

Proceedings of the 38th Annual Computer Security Applications Conference

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A survey on the handover management in 5G-NR cellular networks: aspects, approaches and challenges

Haghrah

Abdollahi

Azarhava

et al. 2023

J Wireless Com Network

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With the purpose of providing higher data rate and ultra-reliable and low-latency communications for the users, employing the small cells in the upcoming Fifth-Generation-New Radio (5G-NR) cellular networks and beyond is leading to the serious challenges in mobility management due to dynamicity of the user equipments (UEs). Among different issues related to the mobility of the UEs, the handover management is one of the key procedures to let the UEs experience a high quality of service (QoS)/quality of experience (QoE). So far, many protocols and algorithms have been proposed to enhance the mobility management in 5G-NR from various aspects, but still a thorough survey has not been incorporated to summarize the recent advances and future directions of the mentioned issue. Thus, the handover management and the corresponding challenges stand in the center of concentrations in this paper, with a glance on 4G to the advancements of 5G-NR. The challenges include QoS/QoE, throughput, delay, traffic load, the attacks during authentication process and resource allocation. To overcome the mentioned challenges, the handover procedure is evaluated by some key performance indicators such as handover ratio, handover failure, radio link failure and such like which depend on the received signal quality. The lack of new advancements and novel aspects of handover plus the separation of security and handover issues in previous works are perceived as research gaps and motivations for the current paper. In this regard, this paper aims to specify and analyze the technical issues, to provide an overview on the proposed methods and recent advances and to bring the future directions into the limelight. We categorize the concurrent standards and methods about the handover, and then, we survey the proposed algorithms including theoretical, algorithm-based and pattern-capturing approaches following the authentication process along with the vulnerabilities and the algorithms to counteract the attacks during handover. Also, we study various issues corresponding to network performance during the handover procedure. Finally, we discuss the open problems and future research directions.

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Murat: Multi-RAT False Base Station Detector

Cited by 4 publications

References 0 publications

5G-Spector: An O-RAN Compliant Layer-3 Cellular Attack Detection Service

5G-Spector: An O-RAN Compliant Layer-3 Cellular Attack Detection Service

You have been warned: Abusing 5G’s Warning and Emergency Systems

A survey on the handover management in 5G-NR cellular networks: aspects, approaches and challenges

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