The Fog computing paradigm: Scenarios and security issues

By Ivan Stojmenovic, Sheng Wen. 2014

984 citations recorded by the source corpus.

Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. In this article, we elaborate the motivation and advantages of Fog computing, and analyse its applications in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks. We discuss the state-of-the-art of Fog computing and similar work under the same umbrella. Security and privacy issues are further disclosed according to current Fog computing paradigm. As an example, we study a typical attack, man-in-the-middle attack, for the discussion of security in Fog computing. We investigate the stealthy features of this attack by examining its CPU and memory consumption on Fog device.

Subfields: Computer Networks and Communications, Control and Systems Engineering, Electrical and Electronic Engineering

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Citations in the corpus

A survey on data fusion in internet of things: Towards secure and privacy-preserving fusion (2019, background): “Different from cloud computing, edge computing [123-126] as a decentralized paradigm is proposed to support real-time services, location awareness and mobility, which is appropriate for various real-time application scenarios, such as smart gird and smart traffic [127], etc.”
Toward Edge Intelligence: Multiaccess Edge Computing for 5G and Internet of Things (2020, methodology): “Together with other edge computing paradigms, such as cloudlets [123] and fog computing [124], [125], MEC can be regarded as a bridge between numerous IoT devices and the centralized cloud.”
A Survey of IoT-Enabled Cyberattacks: Assessing Attack Paths to Critical Infrastructures and Services (2018, background): “Even though more secure protocols are employed, e.g., WiFi, in a HAN or a NAN network, a strongly motivated attacker can crack the supported encryption scheme and perform Man-in-the-Middle (MiTM) attacks [33], [113].”
Fog Computing: Platform and Applications (2015, background): “Later, Stojmenovic et al. [8], [9] have emphasised previous scenarios and expanded fog computing on smart building.”
Fog computing security: a review of current applications and security solutions (2017, background): “2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original”
Optimal Workload Allocation in Fog-Cloud Computing Toward Balanced Delay and Power Consumption (2016, background): “Stojmenovic and Wen [27] and Stojmenovic [28] reviewed a handful of literatures that expand the applications of fog computing to a series of real scenarios, such as smart grid, vehicular networks, cyber-physical systems, etc. Security and privacy issues are further disclosed according to current…”
Computing Resource Allocation in Three-Tier IoT Fog Networks: A Joint Optimization Approach Combining Stackelberg Game and Matching (2017, neutral): “Stojmenovic and Wen [22] elaborated the”
TON_IoT Telemetry Dataset: A New Generation Dataset of IoT and IIoT for Data-Driven Intrusion Detection Systems (2020, background): “The original idea of this layer is to extend the Cloud computing and services to the Edge of the network to provide limited computing capacity and storage near to the data sources [40], [43].”
Fog Computing for Sustainable Smart Cities (2017, methodology): “Connecting to the cloud is less reliable due to a variety of different connectivity issues [Stojmenovic and Wen 2014].”
Software defined networking-based vehicular Adhoc Network with Fog Computing (2015, background): “Fog is considered as a cloud server operating at the edge of the network; offering special services which require network context information, location awareness, and ultra-low latency; which could be satisfy the demands of future VANETs scenarios [9, 10, 11].”
All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey (2018, background): “Stojmenovic and Wen in [82] highlight privacy and security concerns of fog computing gateways as major issues.”
Survey of Fog Computing: Fundamental, Network Applications, and Research Challenges (2018, background): “[42], [47], discussed the application of fog computing to real scenarios, such as smart grid, vehic-”
A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges (2017, background): “Several surveys have also been published on fog computing at large [4], [19], [20] and also in the context of speciﬁc application domains, i.e., vehicular Ad-hoc NETworks (VANETs) [21], Radio Access Networks (RAN) [22], [23], and Internet of Things [24].”
Fog Computing: Focusing on Mobile Users at the Edge (2015, positive): “[1], [15] present the examples of adopting Fog computing in the applications of smartgrid, vehicular networks and sensor networks.”
Security and Privacy in Fog Computing: Challenges (2017, background): “[17], [18], discussed the security and privacy issues.”
A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications (2017, background): “To fulﬁll the gap, fog/edge computing is able to extend cloud computing to be closer to the things it supports [120].”