Cloudlet Mesh for Securing Mobile Clouds from Intrusions and Network Attacks

Shi, Yue; Abhilash, S; Hwang, Kai

doi:10.1109/mobilecloud.2015.15

Cited by 47 publications

(20 citation statements)

References 20 publications

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“…The data stored on the cloud are safeguarded from illegal access by the proposed protocol safeguard. Moreover, Shi et al [10] proposed a new cloudlet architecture for security enforcement. The new architecture was established to enforce security by specifying authentication, encryption, and authorization for trusted mobile cloud computing.…”

Section: Related Workmentioning

confidence: 99%

Can cloudlet coordination support cloud computing infrastructure?

Alsaleh

2018

J Cloud Comp

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The popularity of mobile applications on smartphones requires mobile devices to perform high-performing processing tasks. The computational resources of these devices are limited due to memory, battery life, heat, and weight dissipation. To overcome the limitations of mobile devices, cloud computing is considered the best solution. The major issues faced by cloud computing are expensive roaming charges and growing demand for radio access. However, some major benefits associated with cloud computing are fast application processing, fast transfer of data, and substantial reduction in the use of mobile resources. This study evaluated the association between the distance of cloud servers and cloudlets with and without coordination and data latency. Fast communication in the cloudlet environment is facilitated by coordinated cloudlets, which have a positive influence on the infrastructure of cloud computing. The coordinated cloudlets can be efficiently accessed in different areas, such as vehicular networks, vehicular fog computing, and fog computing.

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Section: Related Workmentioning

confidence: 99%

Can cloudlet coordination support cloud computing infrastructure?

Alsaleh

2018

J Cloud Comp

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“…Prospective issues diminished with the deployment of fog computing [14] that are authentication, intrusion attack, security, and privacy. A designed work distributes the cloudlets as a mesh based intrusion recognition system for security of micro clouds (fog nodes) from interferences and network attacks [53]. Previously predicted ideas [13] about security issues that are currently related to a VM based environment might create probable security anxiety at fog devices.…”

Section: Security and Privacymentioning

confidence: 99%

Fog Computing: An Overview of Big IoT Data Analytics

Anawar

Wang

Zia

et al. 2018

Wireless Communications and Mobile Computing

145

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A huge amount of data, generated by Internet of Things (IoT), is growing up exponentially based on nonstop operational states. Those IoT devices are generating an avalanche of information that is disruptive for predictable data processing and analytics functionality, which is perfectly handled by the cloud before explosion growth of IoT. Fog computing structure confronts those disruptions, with powerful complement functionality of cloud framework, based on deployment of micro clouds (fog nodes) at proximity edge of data sources. Particularly big IoT data analytics by fog computing structure is on emerging phase and requires extensive research to produce more proficient knowledge and smart decisions. This survey summarizes the fog challenges and opportunities in the context of big IoT data analytics on fog networking. In addition, it emphasizes that the key characteristics in some proposed research works make the fog computing a suitable platform for new proliferating IoT devices, services, and applications. Most significant fog applications (e.g., health care monitoring, smart cities, connected vehicles, and smart grid) will be discussed here to create a well-organized green computing paradigm to support the next generation of IoT applications.

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“…There are some studies related to intrusion detection in FC/MEC [5,15,16]. The security of edge computing has previously been reviewed [5], and the author suggested that FC/MEC is a paradigm of edge computing.…”

Section: Related Workmentioning

confidence: 99%

“…It has been noted that an IDS can be deployed on the fog node/MEC host side (host-side detection) or fog network/MEC network side (network-side detection) to monitor host-side intrusions or network-side attacks [15]. A new cloudlet mesh security architecture was proposed based on cloudlets [16], and this architecture is used to protect the mobile cloud network. If cloudlet servers are treated as fog nodes/MEC hosts, then such architecture constitutes a host-side IDS.…”

Section: Related Workmentioning

confidence: 99%

Sample Selected Extreme Learning Machine Based Intrusion Detection in Fog Computing and MEC

Zhou

Xing

et al. 2018

Wireless Communications and Mobile Computing

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Fog computing, as a new paradigm, has many characteristics that are different from cloud computing. Due to the resources being limited, fog nodes/MEC hosts are vulnerable to cyberattacks. Lightweight intrusion detection system (IDS) is a key technique to solve the problem. Because extreme learning machine (ELM) has the characteristics of fast training speed and good generalization ability, we present a new lightweight IDS called sample selected extreme learning machine (SS-ELM). The reason why we propose "sample selected extreme learning machine" is that fog nodes/MEC hosts do not have the ability to store extremely large amounts of training data sets. Accordingly, they are stored, computed, and sampled by the cloud servers. Then, the selected sample is given to the fog nodes/MEC hosts for training. This design can bring down the training time and increase the detection accuracy. Experimental simulation verifies that SS-ELM performs well in intrusion detection in terms of accuracy, training time, and the receiver operating characteristic (ROC) value.

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Cloudlet Mesh for Securing Mobile Clouds from Intrusions and Network Attacks

Cited by 47 publications

References 20 publications

Can cloudlet coordination support cloud computing infrastructure?

Can cloudlet coordination support cloud computing infrastructure?

Fog Computing: An Overview of Big IoT Data Analytics

Sample Selected Extreme Learning Machine Based Intrusion Detection in Fog Computing and MEC

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