Security Issues in Fog Computing and ML-Based Solutions

2021 ◽  
pp. 209-234
Author(s):  
Himanshu Sahu ◽  
Gaytri
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Data Processing ◽  
Fog Computing ◽  
Machine Learning Techniques ◽  
Special Focus ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Security Issues ◽  
Learning Techniques

IoT requires data processing, which is provided by the cloud and fog computing. Fog computing shifts centralized data processing from the cloud data center to the edge, thereby supporting faster response due to reduced communication latencies. Its distributed architecture raises security and privacy issues; some are inherited from the cloud, IoT, and network whereas others are unique. Securing fog computing is equally important as securing cloud computing and IoT infrastructure. Security solutions used for cloud computing and IoT are similar but are not directly applicable in fog scenarios. Machine learning techniques are useful in security such as anomaly detection, intrusion detection, etc. So, to provide a systematic study, the chapter will cover fog computing architecture, parallel technologies, security requirements attacks, and security solutions with a special focus on machine learning techniques.

scholarly journals Development of a Server for the Implementation of Data Processing Pipelines and ANN Training

2021 ◽  
Vol 7 (1) ◽  
pp. 38
Author(s):  
Brais Galdo ◽  
Daniel Rivero ◽  
Enrique Fernandez-Blanco
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Data Processing ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Enormous Amount

Data processing and the use of machine learning techniques make it possible to solve a wide variety of problems. The great disadvantage of using this type of technology is the enormous amount of computation involved. This is why we have tried to develop an architecture that makes the best possible use of the resources available on each machine. The growth of cloud computing and the rise of virtualization techniques have led to a development that allows these tasks to be carried out in a more optimized way.

An Extension-Based Classification System of Cloud Computing Patents

2020 ◽  
Vol 19 (04) ◽  
pp. 1149-1172
Author(s):  
Jia-Yen Huang ◽  
Ke-Wei Tan
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Classification System ◽  
Machine Learning Techniques ◽  
Special Focus ◽  
Patent Classification ◽  
Learning Techniques ◽  
Compound Method ◽  
Classification Quality

Owing to the large number of professional glossaries and unknown patent classification, analysts usually fail to collect and analyze patents efficiently. One solution to this problem is to conduct patent analysis using a patent classification system. However, in a corpus such as cloud patents, many keywords are common among different classes, making it difficult to classify the unknown class documents using the machine learning techniques proposed by previous studies. To remedy this problem, this study aims to establish an efficient classification system with a special focus on features extraction and application of extension theory. We first propose a compound method to determine the features, and then, we propose an extension-based classification method to develop an efficient patent classification system. Using cloud computing patents as the database, the experimental results show that our proposed scheme can outperform the classification quality of the traditional classifiers.

A Comprehensive Study of Security in Cloud Computing

2017 ◽  
pp. 386-412
Author(s):  
Prasanta K. Manohari ◽  
Niranjan K. Ray
Keyword(s):  
Cloud Computing ◽  
Data Center ◽  
Emerging Technology ◽  
Security Risk ◽  
Computing Environment ◽  
Cloud Data Center ◽  
Cloud Computing Environment ◽  
Cloud Computing Security ◽  
Cloud Data ◽  
Security Issues

Cloud computing is one of the emerging technology in the recent times which has varieties of applications at different fields. It is an Internet dependent technology and it store and maintain the data in a cloud data center. Cloud center usually supports more numbers of user, applications and data. In the same time, it also suffered with numerous challenges. Security is a key requirement for cloud data center. Different security mechanisms are proposed for cloud computing environment. In this chapter, we address the background of cloud computing, security risk, requirements, issues, and some of the security techniques are discussed. We discuss different security issues and focus on some existing solutions.

scholarly journals Machine Learning Techniques for Ophthalmic Data Processing: A Review

2020 ◽  
pp. 1-1 ◽  
Author(s):  
Mhd Hasan Sarhan ◽  
Mohammad Ali Nasseri ◽  
Daniel Zapp ◽  
Mathias Maier ◽  
Chris Lohmann ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Processing ◽  
Machine Learning Techniques ◽  
Learning Techniques

scholarly journals A Novel UDT-Based Transfer Speed-Up Protocol for Fog Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Zhijie Han ◽  
Weibei Fan ◽  
Jie Li ◽  
Miaoxin Xu
Keyword(s):  
Cloud Computing ◽  
Data Transfer ◽  
Evaluation Model ◽  
Fog Computing ◽  
Middle Layer ◽  
Transport Layer ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Data Transfer Protocol ◽  
Bit Error Ratio

Fog computing is a distributed computing model as the middle layer between the cloud data center and the IoT device/sensor. It provides computing, network, and storage devices so that cloud based services can be closer to IOT devices and sensors. Cloud computing requires a lot of bandwidth, and the bandwidth of the wireless network is limited. In contrast, the amount of bandwidth required for “fog computing” is much less. In this paper, we improved a new protocol Peer Assistant UDT-Based Data Transfer Protocol (PaUDT), applied to Iot-Cloud computing. Furthermore, we compared the efficiency of the congestion control algorithm of UDT with the Adobe’s Secure Real-Time Media Flow Protocol (RTMFP), based on UDP completely at the transport layer. At last, we built an evaluation model of UDT in RTT and bit error ratio which describes the performance. The theoretical analysis and experiment result have shown that UDT has good performance in IoT-Cloud computing.

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