Capture the RAT: Proximity-Based Attacks in 5G Using the Routine Activity Theory

Nieto, Ana; Acien, Antonio; López, Javier

doi:10.1109/dasc/picom/datacom/cyberscitec.2018.00100

Cited by 2 publications

(3 citation statements)

References 10 publications

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“…Other general solutions address the security of SDMN [Liyanage et al, 2015;Bouras et al, 2017a], security policies [Zhao et al, 2021b;Batalla et al, 2020], security schemes (models or protocols) [Ksentini and Frangoudis, 2020;Chaikalis et al, 2020;Dutta and Hammad, 2020;Angelogianni et al, 2020;Ghafoor et al, 2021;Settembre, 2021;Sharma et al, 2020a;Wazid et al, 2021;Ghosh et al, 2019;Kiyemba Edris et al, 2020;Preuß Mattsson and Nakarmi, 2021;Sun et al, 2019;Shang et al, 2019;Cho et al, 2019;Hsu et al, 2020b,a;Kim et al, 2020;Haddar et al, 2019;Boubakri et al, 2017;Namiot and Sneps-Sneppe, 2021;Letafati et al, 2020;Al-Musawi et al, 2020;Krzywiecki et al, 2021;Zhang et al, 2021;Su, 2021;Boubakri et al, 2019;Ren et al, 2022], security architectures (or frameworks) [Vijay and Umadevi, 2019;Siddiqui et al, 2016;Mantas et al, 2021;Monir Mansour, 2019;Kecskés et al, 2021;Kunz and Zhang, 2018;Mars et al, 2019;Nieto et al, 2018;…”

Section: Smart Agriculturementioning

confidence: 99%

“…Solutions in using 5G and other networks (e.g., Wi-Fi). Bhuyan et al, 2021;Ksentini and Frangoudis, 2020;Gonzalez et al, 2020;Liyanage et al, 2018;Wang and Yan, 2015;Tahir et al, 2020;Azzaoui et al, 2020;Nieto et al, 2017Nieto et al, , 2018Zhang and Lin, 2017;Compagno et al, 2017;Dik and Berger, 2021;Benzaid and Taleb, 2020;Zhao et al, 2021a;Bitsikas and Pöpper, 2021;Chaudhary et al, 2020;Gao et al, 2021;Sood et al, 2021;Cao et al, 2020;Ding et al, 2022b;Wu et al, 2018;Shi and Sagduyu, 2021;Sullivan et al, 2021;Mei et al, 2018;Gebremariam et al, 2021;Ginzboorg and Niemi, 2016;Rotinsulu and Fitri Sari, 2018;Vassilakis et al, 2017;Ar-joune and Faruque, 2020]. An adversary can maliciously (1) use legitimate orchestrator access to manipulate the configuration and run a compromised network function, (2) take advantage of malicious insiders attacks, (3) perform unauthorized access (e.g., to confidential data [Isaksson and Norrman, 2020] and to RFID tags [Rahimi et al, 2018]), (4) tampering, (5) perform resource exhaustion, (6) turn services unavailable, ( 7) analyze or modify traffic, (8) perform data leakage (e.g., capturing valuable personal information [Bordel et al, 2021;Annessi et al, 2018;Vreman and Maggio, 2019]), (…”

Section: Item Description Item Descriptionmentioning

confidence: 99%

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A Systematic Literature Mapping on the Security of 5G and Vertical Applications

Sobrinho,

Santos,

Silva

et al. 2023

Preprint

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The deployment of 5G infrastructure is one of the main vectors for new application scenarios since it enables enhanced data bandwidth, low latency, and comprehensive signal coverage. As a result, this communication system supports various vertical applications such as the Industrial Internet of Things, smart health, smart cities, smart grids, and transportation systems. However, these applications bring new challenges to 5G networks due to specific requirements for such scenarios. Furthermore, as software-based technologies, including network slicing, software-defined networks, network function virtualization, and multi-access edge computing are a fundamental part of the 5G architecture, the network can expose these applications to new security and privacy concerns. This study summarizes the existing literature on 5G vertical applications security. We highlight vulnerabilities, threats, attacks, and solutions for 5G vertical applications. We conducted a Systematic Literature Mapping (SLM) to discuss security and privacy challenges regarding the 5G vertical applications. The SLM answered the following research question: what is the state-of-the-art regarding security in 5G networks and vertical applications? We reviewed 389 papers from 2,349 produced by searching with a curated search query and discussed vulnerabilities, threats, attacks, and solutions for 5G vertical applications. Smart cities, Industry 4.0, smart transportation, public services, smart grids, and smart health are vertical applications with relevant security concerns. We observed the need for more research since the 5G and vertical applications continuously evolve. This review also uncovers research gaps and future research directions.

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Section: Smart Agriculturementioning

confidence: 99%

Section: Item Description Item Descriptionmentioning

confidence: 99%

A Systematic Literature Mapping on the Security of 5G and Vertical Applications

Sobrinho,

Santos,

Silva

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…routine activity theory [6]). This must be adapted to the cybersecurity context and also consider the scenarios where this is possible (e.g., proximity-based attacks [25]). Some factors that can influence this feature are, for example, the past actions (e.g., probability of re-offending) and the level of education to identify the specific threat to which the victim is exposed.…”

Section: Exposurementioning

confidence: 99%

Cybersecurity profiles based on human-centric IoT devices

Nieto

Rı́os

2019

Hum. Cent. Comput. Inf. Sci.

Self Cite

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Cybersecurity tools usually depend on huge amounts of data that must be processed in real time. Once these data have been processed, the information deduced from them must be presented to different experts, who may or may not be technicians. To facilitate understanding of how different actors are involved in a cybercrime, data related to individuals can be presented in the form of cybersecurity profiles. However, as the number of devices continues to grow with the development of the Internet of Things (IoT) [1] more data is available for interpretation. Note that in 2019 there are 7 billion internet-connected devices worldwide, according to IoT Analytics [2]. Clearly, this poses new challenges but also offers new opportunities. With data available from myriads of IoT devices, the complexity of the solutions increases but having so much data can be exploited to generate much more complete cybersecurity profiles, which in turn leads to a better understanding of the whole context of a digital investigation. Unfortunately, even though these data are readily available there is still no way to automate the process of gathering these data and linking them to users. Consequently, more research is necessary to unleash the full potential of cybersecurity profiles. This paper works precisely in this direction by proposing a new methodology for defining advanced cybersecurity profiles. This methodology considers, for the first time, the importance of IoT devices in the analysis of a cybercrime scene. In particular, we exploit the strong relationship between users and their devices. Moreover, the approach

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Capture the RAT: Proximity-Based Attacks in 5G Using the Routine Activity Theory

Cited by 2 publications

References 10 publications

A Systematic Literature Mapping on the Security of 5G and Vertical Applications

A Systematic Literature Mapping on the Security of 5G and Vertical Applications

Cybersecurity profiles based on human-centric IoT devices

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