An efficient truthfulness privacy-preserving tendering framework for vehicular fog computing

Alamer, Abdulrahman; Basudan, Sultan

doi:10.1016/j.engappai.2020.103583

Cited by 28 publications

(8 citation statements)

References 14 publications

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“…Wei et al [125] and Alamer and Basudan [174] focused on the disadvantages of the existing cloud-based network. With the help of fog computing, the authors have built a privacy preserving system for vehicular crowd-sensing framework.…”

Section: ) Frameworkmentioning

confidence: 99%

Fog computing: A taxonomy, systematic review, current trends and research challenges

Singh

Gill

2021

Journal of Parallel and Distributed Computing

104

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Section: ) Frameworkmentioning

confidence: 99%

Fog computing: A taxonomy, systematic review, current trends and research challenges

Singh

Gill

2021

Journal of Parallel and Distributed Computing

104

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“…So, when it comes to SDC, these vehicles would require quick information of the surrounding so as to avoid any mishap. Many researches direct towards vehicular fogging [8,45,58,59,79,92,108,115,126,147]. Vehicleto-vehicle communication is achieved using fog-IoT infrastructure within the embedded computers in the automobiles.…”

Section: Applications Of Fog Computingmentioning

confidence: 99%

Application of IoT‐Fog based real‐time monitoring system for open‐cast mines—A survey

Yadav

Mishra²,

Jayanthu

et al. 2021

IET Wireless Sensor Systems

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Fog computing (FC) archetypes is in focus recently for its potential to utilise resources optimally by the Internet of Things (IoT) network bearing ample end-devices. This enhances the quality of service (QoS) to the proximity of end-users as latency-free processing is obtained in cloud-IoT-based environs. Mining industry will encounter a level-up due to these technological advancements like fog-IoT-based systems. Monitoring mining activities such as blasting, slope monitoring, and miner tracking are time-sensitive. Hence, instant response is demand of extreme mine environment so that life and property are not compromised. New opportunities emerge in mining since the FC approach addresses these demands depending on the demand of the situation/user. The parameters of integrating the state-of-art of fog, IoT, and cloud architectures are provided, and a Fog-IoT mines monitoring (FIoTMM) system for real-time monitoring of open-cast mines is proposed. This work also envisions the applications and future trends of FC concerning IoT and cloud. It emphasises how key features of fog help the system in achieving lower network influx, reduced latency, resource utilisation, and immediate data computation and storage because these services take place closer to point of data generation. This data can be immediately visualised/accessed and used to generate early warning in the mines. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…These applications are hosted in the cloud-server, which improves service efficiency. The cloud-server will cache most IoRT applications into the RSU-fog nodes to reduce any potential bandwidth and latency issues (Alamer and Basudan, 2020). It should be noted that this system model requires a trust authority (TA) to be in charge of IoRT device registration.…”

Section: System Model Attack Model and Design Goalmentioning

confidence: 99%

“…An effective solution to AI robotic application issues is to employ a fog computing (FC) network system (Yang et al , 2020a). An FC paradigm is introduced as a network edge to bring the provision of services closer to end devices that use fog-edge devices, such as roadside units (RSUs), to collaboratively execute a massive amount of processes, communication, storage and management (Alamer and Basudan, 2020) (Basudan et al , 2018). By using FC features, AI robotics will be upgraded for use in various applications and to communicate with other things through a fog node network.…”

Section: Introductionmentioning

confidence: 99%

A secure anonymous tracing fog-assisted method for the Internet of Robotic Things

Alamer

2020

LHT

Self Cite

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PurposeEmploying a fog computing (FC) network system in the robotic network system is an effective solution to support robotic application issues. The interconnection between robotic devices through an FC network can be referred as the Internet of Robotic Things (IoRT). Although the FC network system can provide number of services closer to IoRT devices, it still faces significant challenges including real-time tracing services and a secure tracing services. Therefore, this paper aims to provide a tracking mobile robot devices in a secure and private manner, with high efficiency performance, is considered essential to ensuring the success of IoRT network applications.Design/methodology/approachThis paper proposes a secure anonymous tracing (SAT) method to support the tracing of IoRT devices through a FC network system based on the Counting Bloom filter (CBF) and elliptic curve cryptography techniques. With the proposed SAT mechanism, a fog node can trace a particular robot device in a secure manner, which means that the fog node can provide a service to a particular robot device without revealing any private data such as the device's identity or location.FindingsAnalysis shows that the SAT mechanism is both efficient and resilient against tracing attacks. Simulation results are provided to show that the proposed mechanism is beneficial to support IoRT applications over an FC network system.Originality/valueThis paper represents a SAT method based on CBF and elliptic curve cryptography techniques as an efficient mechanism that is resilient against tracing attacks.

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An efficient truthfulness privacy-preserving tendering framework for vehicular fog computing

Cited by 28 publications

References 14 publications

Fog computing: A taxonomy, systematic review, current trends and research challenges

Fog computing: A taxonomy, systematic review, current trends and research challenges

Application of IoT‐Fog based real‐time monitoring system for open‐cast mines—A survey

A secure anonymous tracing fog-assisted method for the Internet of Robotic Things

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