Vehicular Fog Computing: Architecture, Use Case, and Security and Forensic Challenges

Huang, Cheng; Lu, Rongxing; Choo, Kim‐Kwang Raymond

doi:10.1109/mcom.2017.1700322

Cited by 284 publications

(126 citation statements)

References 10 publications

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“…Vehicles serve as the infrastructure for vehicular communication . Huang et al proposed an architecture consisting of three layers for vehicular fog networks. Content distribution networks Content distribution/delivery networks (CDN) consist of geographically distributed servers that are capable of delivering the web pages as information. CDN uses edge caching approaches for speeding up the delivery of the web contents.…”

Section: Fog Computing Aspectsmentioning

confidence: 99%

Elucidating the challenges for the praxis of fog computing: An aspect‐based study

Martin

Kandasamy

Chandrasekaran

et al. 2019

Int J Communication

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Summary The evolutionary advancements in the field of technology have led to the instigation of cloud computing. The Internet of Things paradigm stimulated the extensive use of sensors distributed across the network edges. The cloud datacenters are assigned the responsibility for processing the collected sensor data. Recently, fog computing was conceptuated as a solution for the overwhelmed narrow bandwidth. The fog acts as a complementary layer that interplays with the cloud and edge computing layers, for processing the data streams. The fog paradigm, as any distributed paradigm, has its set of inherent challenges. The fog environment necessitates the development of management platforms that effectuates the orchestration of fog entities. Owing to the plenitude of research efforts directed toward these issues in a relatively young field, there is a need to organize the different research works. In this study, we provide a compendious review of the research approaches in the domain, with special emphasis on the approaches for orchestration and propose a multilevel taxonomy to classify the existing research. The study also highlights the application realms of fog computing and delineates the open research challenges in the domain.

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Section: Fog Computing Aspectsmentioning

confidence: 99%

Elucidating the challenges for the praxis of fog computing: An aspect‐based study

Martin

Kandasamy

Chandrasekaran

et al. 2019

Int J Communication

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“…23,24 Roadside units (RSUs), 25 cellular network, 26,27 mobile cloud computing, 28 and fog vehicular computing 29 are examples of solutions that have been presented recently. In many of these studies, information security breaches and privacy violation have been mentioned as one of the main concerns that originates from resource-constraint.…”

Section: Case Studymentioning

confidence: 99%

“…29 Real-time decision-making is vital in this system. These data have been estimated to be about 25 GB per day.…”

Section: Fog Vehicle Computing Architecturementioning

confidence: 99%

An opportunistic resource management model to overcome resource‐constraint in the Internet of Things

Safa

Maple

Haghparast

et al. 2018

Concurrency and Computation

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Experts believe that the Internet of Things (IoT) is a new revolution in technology and has brought many advantages for our society. However, there are serious challenges in terms of information security and privacy protection. Smart objects usually do not have malware detection due to resource limitations and their intrusion detection work on a particular network. Low computation power, low bandwidth, low battery, storage, and memory contribute to a resource-constrained effect on information security and privacy protection in the domain of IoT. The capacity of fog and cloud computing such as efficient computing, data access, network and storage, supporting mobility, location awareness, heterogeneity, scalability, and low latency in secure communication positively influence information security and privacy protection in IoT. This study illustrates the positive effect of fog and cloud computing on the security of IoT systems and presents a decision-making model based on the object's characteristics such as computational power, storage, memory, energy consumption, bandwidth, packet delivery, hop-count, etc. This helps an IoT system choose the best nodes for creating the fog that we need in the IoT system. Our experiment shows that the proposed approach has less computational, communicational cost, and more productivity in compare with the situation that we choose the smart objects randomly to create a fog.KEYWORDS cloud, Fog, information security, Internet of Things, privacy, resource INTRODUCTIONThe Internet has provided a backbone for connecting different objects to each other and has changed human life significantly. The ubiquitous things is a new concept that has been created by the interconnection and intercommunication amongst smart objects. 1 We are faced with a huge volume of data in this environment. Network traffic, increasing demands of real time, latency-sensitive applications, resource-constraints (computational power, storage, memory, etc) in actuators, mobility and geo-distribution of smart objects, and heterogeneity that are new challenges in the domain of IoT. 2 These weaknesses directly or indirectly influence information security and privacy violation in IoT systems. 3Resource-constraint in actuators jeopardises secure communication between different smart objects. 4 Messages need to be sent encrypted;they will be decrypted for process in the target. The result of the process should be encrypted and send to the same object or other smart objects.We have latency; this delays not only creates risk for information security, but it may also impact human safety in some applications of IoT, such as smart vehicles. Lightweight cryptography has been presented to overcome this challenge in vehicle-to-vehicle (V2V) communication and in many other secure communications in IoT. 5 Smart objects usually do not have malware detection due to limitation in resources; their intrusion detection only can detect attacks in particular networks (not hybrid). These are examples of common problems in the IoT domain.Cloud...

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“…As fog nodes are deployed at the roadside and due to its location awareness nature fog nodes can typically face physical attacks which are not possible in the cloud. Due to public accesses of fog nodes attackers can attack many types of attacks like data injection attack, black/grey hole attack etc., [12] by gaining administrative accesses or by altering the function. Some techniques are summarized below to overcome these challenges are…”

Section: Security Issues In Vfcmentioning

confidence: 99%

“…For example, if vehicle reports traffic jam to fog node, due to the location awareness nature of fog node it is easy to locate the vehicle based on the accessing fog node [12]. This creates a privacy issue one of the promising methods to protect vehicle privacy is to use anonymity techniques [12] such as pseudonyms, group signatures, and k-anonymity. The anonymity techniques help in hiding the user identity by fulfilling the tasks given to vehicle with the high-quality output.…”

Section: Privacymentioning

confidence: 99%

Vehicular Fog Computing: The Need for a New Paradigm and its Issues

Deepika¹,

Kiran²

2018

IJET

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Smart vehicles participating in VANET have high computing capabilities which lead the demand to support more applications that give safety and effective measures to people. The vehicles in VANET are taking the help of cloud services for communication, computation and storage which benefits in economical way and we call that as vehicular cloud computing (VCC). Due to certain limitations in VCC and also demand for more quality of service applications in smart vehicles a new paradigm called vehicular fog computing (VFC) is proposed which helps to overcome limitations in VCC and provide more quality services to users participating in VANET. Some of the security challenges and possible attacks in VFC are also stated.

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Vehicular Fog Computing: Architecture, Use Case, and Security and Forensic Challenges

Cited by 284 publications

References 10 publications

Elucidating the challenges for the praxis of fog computing: An aspect‐based study

Elucidating the challenges for the praxis of fog computing: An aspect‐based study

An opportunistic resource management model to overcome resource‐constraint in the Internet of Things

Vehicular Fog Computing: The Need for a New Paradigm and its Issues

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