scholarly journals EARS-DM: Efficient Auto Correction Retrieval Scheme for Data Management in Edge Computing

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3616 ◽  
Author(s):  
Kai Fan ◽  
Jie Yin ◽  
Kuan Zhang ◽  
Hui Li ◽  
Yintang Yang
Keyword(s):  
Cloud Computing ◽  
Data Management ◽  
Low Cost ◽  
Bloom Filter ◽  
Edge Computing ◽  
Security And Privacy ◽  
Network Bandwidth ◽  
Computing Model ◽  
Retrieval Scheme ◽  
Data Source

Edge computing is an extension of cloud computing that enables messages to be acquired and processed at low cost. Many terminal devices are being deployed in the edge network to sense and deal with the massive data. By migrating part of the computing tasks from the original cloud computing model to the edge device, the message is running on computing resources close to the data source. The edge computing model can effectively reduce the pressure on the cloud computing center and lower the network bandwidth consumption. However, the security and privacy issues in edge computing are worth noting. In this paper, we propose an efficient auto-correction retrieval scheme for data management in edge computing, named EARS-DM. With automatic error correction for the query keywords instead of similar words extension, EARS-DM can tolerate spelling mistakes and reduce the complexity of index storage space. By the combination of TF-IDF value of keywords and the syntactic weight of query keywords, keywords who are more important will obtain higher relevance scores. We construct an R-tree index building with the encrypted keywords and the children nodes of which are the encrypted identifier FID and Bloom filter BF of files who contain this keyword. The secure index will be uploaded to the edge computing and the search phrase will be performed by the edge computing which is close to the data source. Then EDs sort the matching encrypted file identifier FID by relevance scores and upload them to the cloud server (CS). Performance analysis with actual data indicated that our scheme is efficient and accurate.

scholarly journals An IoT-Based Fog Computing Model

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2783 ◽  
Author(s):  
Kun Ma ◽  
Antoine Bagula ◽  
Clement Nyirenda ◽  
Olasupo Ajayi
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Physical Distance ◽  
Cloud Services ◽  
Daily Lives ◽  
Service Computing ◽  
Network Bandwidth ◽  
Computing Model ◽  
Data Source ◽  
The Internet Of Things

The internet of things (IoT) and cloud computing are two technologies which have recently changed both the academia and industry and impacted our daily lives in different ways. However, despite their impact, both technologies have their shortcomings. Though being cheap and convenient, cloud services consume a huge amount of network bandwidth. Furthermore, the physical distance between data source(s) and the data centre makes delays a frequent problem in cloud computing infrastructures. Fog computing has been proposed as a distributed service computing model that provides a solution to these limitations. It is based on a para-virtualized architecture that fully utilizes the computing functions of terminal devices and the advantages of local proximity processing. This paper proposes a multi-layer IoT-based fog computing model called IoT-FCM, which uses a genetic algorithm for resource allocation between the terminal layer and fog layer and a multi-sink version of the least interference beaconing protocol (LIBP) called least interference multi-sink protocol (LIMP) to enhance the fault-tolerance/robustness and reduce energy consumption of a terminal layer. Simulation results show that compared to the popular max–min and fog-oriented max–min, IoT-FCM performs better by reducing the distance between terminals and fog nodes by at least 38% and reducing energy consumed by an average of 150 KWh while being at par with the other algorithms in terms of delay for high number of tasks.

A New Approach in Cloud Computing User Authentication

Web Services ◽  
2019 ◽  
pp. 1393-1410
Author(s):  
Alaa Hussein Al-Hamami ◽  
Rafal A. Al-Khashab
Keyword(s):  
Cloud Computing ◽  
High Performance ◽  
User Authentication ◽  
Low Cost ◽  
Remote Access ◽  
Security And Privacy ◽  
Main Concern ◽  
Security Measures ◽  
User Privacy ◽  
Is Security

Cloud computing provides the full scalability, reliability, high performance and relatively low cost feasible solution as compared to dedicated infrastructure. These features make cloud computing more attractive to users and intruders. It needs more and complex security measures to protect user privacy and data centers. The main concern in this chapter is security, privacy and trust. This chapter will give a discussion and a suggestion for using cloud computing to preserve security and privacy. The malicious hacker and other threats are considering the major cause of leaking security of the personal cloud due to centralized location and remote accesses to the cloud. According to attacks, a centralized location can be easier target rather than several goals and remote access is insecure technologies which offer a boundary of options for attackers to infiltrate enterprises. The biggest concern is attackers that will use the remote connection as a jumping point to get deeper into an organization.

Resource-Sharing Construction of Area E-Government Information Based on Cloud-Computing - Taking Hebei Cangzhou as an Example

2013 ◽  
Vol 347-350 ◽  
pp. 2793-2798
Author(s):  
Lin Na Huang ◽  
Bao Guo Gu
Keyword(s):  
Cloud Computing ◽  
Resource Sharing ◽  
Low Cost ◽  
Information Resource ◽  
Government Information ◽  
Computing Power ◽  
Computing Model ◽  
High Security

Cloud computing, with superior computing power, low-cost and high-security, will be applied to the resource-sharing area of E-government information with great significance and value. From the point of theory, technology and practice, it is scientifically feasible to build a cloud-based E-government information resource-sharing platform, and some areas are actively building this. This paper, through analysis of the problems existing in Cangzhou E-Government and through the design of the E-government cloud computing model, puts forward new ways to explore the development of regional E-government based on cloud computing.

scholarly journals Outsourcing Set Intersection Computation Based on Bloom Filter for Privacy Preservation in Multimedia Processing

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Hongliang Zhu ◽  
Meiqi Chen ◽  
Maohua Sun ◽  
Xin Liao ◽  
Lei Hu
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Low Cost ◽  
Bloom Filter ◽  
Privacy Preserving ◽  
Cloud Services ◽  
Multimedia Application ◽  
Computation Method ◽  
Multimedia Processing ◽  
Set Intersection

With the development of cloud computing, the advantages of low cost and high computation ability meet the demands of complicated computation of multimedia processing. Outsourcing computation of cloud could enable users with limited computing resources to store and process distributed multimedia application data without installing multimedia application software in local computer terminals, but the main problem is how to protect the security of user data in untrusted public cloud services. In recent years, the privacy-preserving outsourcing computation is one of the most common methods to solve the security problems of cloud computing. However, the existing computation cannot meet the needs for the large number of nodes and the dynamic topologies. In this paper, we introduce a novel privacy-preserving outsourcing computation method which combines GM homomorphic encryption scheme and Bloom filter together to solve this problem and propose a new privacy-preserving outsourcing set intersection computation protocol. Results show that the new protocol resolves the privacy-preserving outsourcing set intersection computation problem without increasing the complexity and the false positive probability. Besides, the number of participants, the size of input secret sets, and the online time of participants are not limited.

The Architecture and Analysis of a New Cloud Collaborative Commerce Model

2013 ◽  
Vol 3 (3) ◽  
pp. 1-19
Author(s):  
Hussein Al-Bahadili ◽  
Awad Al-Sabbah ◽  
Mohammed Abu Arqoub
Keyword(s):  
Cloud Computing ◽  
Response Times ◽  
Security And Privacy ◽  
It Infrastructure ◽  
Web Based ◽  
Collaborative Commerce ◽  
Test Tool ◽  
Computing Model ◽  
Architectural Model ◽  
Main Components

Cloud Computing IT infrastructure has the potential to be particularly suitable for collaborative commerce (c-commerce) applications; because it generally requires less efforts and interferences for development, customization, integration, operation, and maintenance than other traditional IT infrastructures (e.g., on-premises and data centers). However, upgrading c-commerce applications running on traditional IT infrastructures, to run efficiently on cloud computing infrastructure, faces a number of challenges, mainly, lack of effective and reliable architectural model. This paper presents a description of a new architectural model for developing cloud computing based c-commerce applications; which is denoted as cc-commerce model. The model is an basically based on the standard cloud computing model, and it consists of six main components; these are: client, provider, auditor, broker, security and privacy, and communications network. The new model is implemented in a simple and flexible Web-based test tool, namely, the cc-commerce test (3CT) tool, which is used to evaluate the performance of the model through measuring the response times for four different configurations. The analysis of the obtained results demonstrates that the cc-commerce model can provide better response time than equivalent c-commerce models.

A New Approach in Cloud Computing User Authentication

2016 ◽  
pp. 2402-2418
Author(s):  
Alaa Hussein Al-Hamami ◽  
Rafal A Al-Khashab
Keyword(s):  
Cloud Computing ◽  
High Performance ◽  
User Authentication ◽  
Low Cost ◽  
Remote Access ◽  
Security And Privacy ◽  
Main Concern ◽  
Security Measures ◽  
User Privacy ◽  
Is Security

Cloud computing provides the full scalability, reliability, high performance and relatively low cost feasible solution as compared to dedicated infrastructure. These features make cloud computing more attractive to users and intruders. It needs more and complex security measures to protect user privacy and data centers. The main concern in this chapter is security, privacy and trust. This chapter will give a discussion and a suggestion for using cloud computing to preserve security and privacy. The malicious hacker and other threats are considering the major cause of leaking security of the personal cloud due to centralized location and remote accesses to the cloud. According to attacks, a centralized location can be easier target rather than several goals and remote access is insecure technologies which offer a boundary of options for attackers to infiltrate enterprises. The biggest concern is attackers that will use the remote connection as a jumping point to get deeper into an organization.

scholarly journals Homomorphic Evaluation of the Integer Arithmetic Operations for Mobile Edge Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Changqing Gong ◽  
Mengfei Li ◽  
Liang Zhao ◽  
Zhenzhou Guo ◽  
Guangjie Han
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Rapid Development ◽  
Heterogeneous Data ◽  
Edge Computing ◽  
Security And Privacy ◽  
Mobile Edge Computing ◽  
Operation Rules ◽  
Original Scheme ◽  
Time Overhead

With the rapid development of the 5G network and Internet of Things (IoT), lots of mobile and IoT devices generate massive amounts of multisource heterogeneous data. Effective processing of such data becomes an urgent problem. However, traditional centralised models of cloud computing are challenging to process multisource heterogeneous data effectively. Mobile edge computing (MEC) emerges as a new technology to optimise applications or cloud computing systems. However, the features of MEC such as content perception, real-time computing, and parallel processing make the data security and privacy issues that exist in the cloud computing environment more prominent. Protecting sensitive data through traditional encryption is a very secure method, but this will make it impossible for the MEC to calculate the encrypted data. The fully homomorphic encryption (FHE) overcomes this limitation. FHE can be used to compute ciphertext directly. Therefore, we propose a ciphertext arithmetic operation that implements data with integer homomorphic encryption to ensure data privacy and computability. Our scheme refers to the integer operation rules of complement, addition, subtraction, multiplication, and division. First, we use Boolean polynomials (BP) of containing logical AND, XOR operations to represent the rulers. Second, we convert the BP into homomorphic polynomials (HP) to perform ciphertext operations. Then, we optimise our scheme. We divide the ciphertext vector of integer encryption into subvectors of length 2 and increase the length of private key of FHE to support the 3-multiplication level additional. We test our optimised scheme in DGHV and CMNT. In the number of ciphertext refreshes, the optimised scheme is reduced by 2/3 compared to the original scheme, and the time overhead of our scheme is reduced by 1/3. We also examine our scheme in CNT of without bootstrapping. The time overhead of optimised scheme over DGHV and CMNT is close to the original scheme over CNT.

scholarly journals When Sensor-Cloud Meets Mobile Edge Computing

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5324 ◽  
Author(s):  
Tian Wang ◽  
Yucheng Lu ◽  
Zhihan Cao ◽  
Lei Shu ◽  
Xi Zheng ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Edge Computing ◽  
Security And Privacy ◽  
Future Research ◽  
Mobile Edge Computing ◽  
Control Center ◽  
Computing Center ◽  
Sensor Cloud ◽  
Evaluation Mechanism ◽  
And Control

Sensor-clouds are a combination of wireless sensor networks (WSNs) and cloud computing. The emergence of sensor-clouds has greatly enhanced the computing power and storage capacity of traditional WSNs via exploiting the advantages of cloud computing in resource utilization. However, there are still many problems to be solved in sensor-clouds, such as the limitations of WSNs in terms of communication and energy, the high latency, and the security and privacy issues due to applying a cloud platform as the data processing and control center. In recent years, mobile edge computing has received increasing attention from industry and academia. The core of mobile edge computing is to migrate some or all of the computing tasks of the original cloud computing center to the vicinity of the data source, which gives mobile edge computing great potential in solving the shortcomings of sensor-clouds. In this paper, the latest research status of sensor-clouds is briefly analyzed and the characteristics of the existing sensor-clouds are summarized. After that we discuss the issues of sensor-clouds and propose some applications, especially a trust evaluation mechanism and trustworthy data collection which use mobile edge computing to solve the problems in sensor-clouds. Finally, we discuss research challenges and future research directions in leveraging mobile edge computing for sensor-clouds.

scholarly journals A Comprehensive Overview of Privacy and Data Security for Cloud Storage

2021 ◽  
pp. 113-152
Author(s):  
Dr. Nikhat Akhtar ◽  
Dr. Bedine Kerim ◽  
Dr. Yusuf Perwej ◽  
Dr. Anurag Tiwari ◽  
Dr. Sheeba Praveen
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Security ◽  
Cloud Storage ◽  
Low Cost ◽  
Network Connectivity ◽  
Data Encryption ◽  
Security And Privacy ◽  
Comprehensive Overview ◽  
Resource Pooling

People used to carry their documents about on CDs only a few years ago. Many people have recently turned to memory sticks. Cloud computing, in this case, refers to the capacity to access and edit data stored on remote servers from any Internet-connected platform. Cloud computing is a self-service Internet infrastructure that allows people to access computing resources at any location worldwide. The world has altered as a result of cloud computing. Cloud computing can be thought of as a new computing typology that can provide on-demand services at a low cost. By increasing the capacity and flexibility of data storage and providing scalable compute and processing power that fits the dynamic data requirements, cloud computing has aided the advancement of IT to higher heights. In the field of information technology, privacy and data security have long been a serious concern. It becomes more severe in the cloud computing environment because data is stored in multiple locations, often across the globe. Users' primary challenges regarding the cloud technology revolve around data security and privacy. We conduct a thorough assessment of the literature on data security and privacy issues, data encryption technologies, and related countermeasures in cloud storage systems in this study. Ubiquitous network connectivity, location-independent resource pooling, quick resource flexibility, usage-based pricing, and risk transference are all features of cloud computing.

scholarly journals Research on Digital Twin and Collaborative Cloud and Edge Computing Applied in Operations and Maintenance in Wind Turbines of Wind Power Farm

2021 ◽  
Author(s):  
Fuxing Li ◽  
Luxi Li ◽  
You Peng
Keyword(s):  
Cloud Computing ◽  
Wind Turbine ◽  
Wind Farm ◽  
Edge Computing ◽  
Fault Prediction ◽  
Cloud Data ◽  
Digital Twin ◽  
Operation And Maintenance ◽  
Data Source ◽  
Computing Node

For the increasingly prominent problems of wind turbine maintenance, using edge cloud collaboration technology to construct wind farm equipment operation and maintenance framework is proposed, digital twin is used for fault prediction and diagnosis. Framework consists of data source layer, edge computing node layer, public or private cloud. Data source layer solves acquisition and transmission of wind turbine operation and maintenance data, edge computing node layer is responsible for on-site data cloud computing, storage and data transmission to cloud computing layer, receiving cloud computing results, device driving and control. The cloud computing layer completes the big data calculation and storage from wind farm, except that, based on real-time data records, continuous simulation and optimization, correct failure prediction mode, expert database and its prediction software, and edge node interaction and shared intelligence. The research explains that wind turbine uses digital twin to do fault prediction and diagnosis model, condition assessment, feature analysis and diagnosis, life prediction, combining with the probabilistic digital twin model to make the maintenance plan and decision-making method.

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