LiFi/WiFi Authentication and Handover Protocols: Survey, Evaluation, and Recommendation

Sulayman, Iman I. M. Abu; He, Rongji; Manka, Marlin; Ning, Andrew; Ouda, Abdelkader

doi:10.1109/isncc52172.2021.9615853

Cited by 6 publications

(3 citation statements)

References 13 publications

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“…Moreover, the attacker can predict which vulnerabilities are available to exploit depending on the type of IoT devices in the network. However, extensive research has been conducted on fingerprinting the IoT devices using eavesdropping from the inside network [24]. This research performs a detailed investigation and proves that fingerprinting the IoT devices eaves-dropping from outside the network is not only possible but also a straightforward process.…”

Section: Problem Statementmentioning

confidence: 81%

Profiling Attack on WiFi-based IoT Devices using an Eavesdropping of an Encrypted Data Frames

Alharbi¹,

Almalki²,

Alyami³

et al. 2022

Adv. sci. technol. eng. syst. j.

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The rapid advancement of the Internet of Things (IoT) is distinguished by heterogeneous technologies that provide cutting-edge services across a range of application domains. However, by eavesdropping on encrypted WiFi network traflc, attackers can infer private information such as the types and working status of IoT devices in a business or residential home. Moreover, since attackers do not need to join a WiFi network, such a privacy attack is very easy for attackers to conduct while at the same time invisible and leaving no trace to the network owner. In this paper, we extend our preliminary work originally presented at the CCNC'22 conference by using a new set of time series monitored WiFi data frames with extended machine learning algorithms. We instrument a testbed of 10 IoT devices and conduct a detailed evaluation using multiple machine learning techniques for fingerprinting, achieving high accuracy up to 95% in identifying what IoT devices exist and their working status. Compared with our previous work in , the new approach could achieve IoT device profiling much quicker while maintaining the same level of classification accuracy. Moreover, the experimental results show that outside intruders can significantly harm the IoT devices without joining a WiFi network and can launch the attack within a minimum time without leaving any detectable footprints.

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Section: Problem Statementmentioning

confidence: 81%

Profiling Attack on WiFi-based IoT Devices using an Eavesdropping of an Encrypted Data Frames

Alharbi¹,

Almalki²,

Alyami³

et al. 2022

Adv. sci. technol. eng. syst. j.

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“…Because of this, the data signal must be secured by other means, such as encryption. Standards have been set out for the implementation of security features at both the physical and data link layer in visible light communication, such as ITU-TG.9991, IEEE P802.15.7 and IEEE802.11 bb [38].…”

Section: Path For Further Development Of Proof-of-concept Li-fi Syste...mentioning

confidence: 99%

Hybrid mmWave-Li-Fi 5G Architecture for Reconfigurable Variable Latency and Data Rate Communications

et al. 2023

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Despite modern vehicles having the necessary advanced driver assistance systems (ADAS) for autonomous operation, current implementations rely solely on sensor information from the surrounding environment or data from smart infrastructure. However, shortcomings in current implementations and standards around cost-effective variable latency and data rate have prevented widespread adoption of the technology to enable autonomous operation. This paper presents a proof-of-concept (PoC) reconfigurable design and performance of a hybrid high-ultra-high bands [i.e., millimetre-Wave (mmWave)-light fidelity (Li-Fi)] fifth generation (5G) architecture for autonomous vehicular communication applications. The hybrid multiple input multiple output (MIMO) system architecture design is mathematically modelled and presented. The reported prelim PoC validation focuses on the Li-Fi experiment and results. The proposed hybrid system's effectiveness was evaluated using the open-source "Model-based Autonomous Traffic Simulation" (MOBATSim). The simulation results of a potential Li-Fi system and a PoC prototype are presented to demonstrate the role of the Li-Fi system in the proposed hybrid mmWave-Li-Fi 5G architecture. Three models of LED/lamp and two models of photodiode were simulated at three different vehicle speeds to ascertain the potential of the system. Promising results are reported at low speeds with received power values of up to -8.39 dBm and signal to noise ratios of up to 29.39 dB. Practical prototype simulations showed auspicious results including received power of -24.6 dBm to -34.12 dBm at the vehicle speeds of 10 MPH to 30 MPH respectively. The implemented PoC Li-Fi technology component has demonstrated the ability to transmit information with a theoretical output of 333 bits per second at 1.92 m, without the use of any highpower processors, components, and modulation techniques. The proposed system yields high data rates due to reconfigurable high bandwidth channels; many simultaneous multimedia mmWave-Li-Fi connections enabled due to spatial reuse with narrow beams; and easier mmWave-Li-Fi ultra-low latency support occasioned by smaller packet sizes. This holds a great promise for the hybrid 5G/6G mmWave-Li-Fi autonomous vehicular communication use case and/or applications.

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“…The three PHY modes can coexist with each other, thereby mitigating LED flicker and reducing dimming [10]. In 2019, the ITU-T Telecommunication Standardization Sector finalized recommendation G.9991 that established the first commercially ready light fidelity (Li-Fi) standard [11]. Both IEEE 802.…”

Section: Introductionmentioning

confidence: 99%

A Review of Hybrid VLC/RF Networks: Features, Applications, and Future Directions

Bravo Alvarez,

Montejo-Sánchez,

Rodríguez-López

et al. 2023

Sensors

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The expectation for communication systems beyond 5G/6G is to provide high reliability, high throughput, low latency, and high energy efficiency services. The integration between systems based on radio frequency (RF) and visible light communication (VLC) promises the design of hybrid systems capable of addressing and largely satisfying these requirements. Hybrid network design enables complementary cooperation without interference between the two technologies, thereby increasing the overall system data rate, improving load balancing, and reducing non-coverage areas. VLC/RF hybrid networks can offer reliable and efficient communication solutions for Internet of Things (IoT) applications such as smart lighting, location-based services, home automation, smart healthcare, and industrial IoT. Therefore, hybrid VLC/RF networks are key technologies for next-generation communication systems. In this paper, a comprehensive state-of-the-art study of hybrid VLC/RF networks is carried out, divided into four areas. First, indoor scenarios are studied considering lighting requirements, hybrid channel models, load balancing, resource allocation, and hybrid network topologies. Second, the characteristics and implementation of these hybrid networks in outdoor scenarios with adverse conditions are analyzed. Third, we address the main applications of hybrid VLC/RF networks in technological, economic, and socio-environmental domains. Finally, we outline the main challenges and future research lines of hybrid VLC/RF networks.

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LiFi/WiFi Authentication and Handover Protocols: Survey, Evaluation, and Recommendation

Cited by 6 publications

References 13 publications

Profiling Attack on WiFi-based IoT Devices using an Eavesdropping of an Encrypted Data Frames

Profiling Attack on WiFi-based IoT Devices using an Eavesdropping of an Encrypted Data Frames

Hybrid mmWave-Li-Fi 5G Architecture for Reconfigurable Variable Latency and Data Rate Communications

A Review of Hybrid VLC/RF Networks: Features, Applications, and Future Directions

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