scholarly journals An Efficient and Credible Multi-Source Trust Fusion Mechanism Based on Time Decay for Edge Computing

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 502
Author(s):  
Wenping Kong ◽  
Xiaoyong Li ◽  
Liyang Hou ◽  
Yanrong Li
Keyword(s):  
Cloud Computing ◽  
High Efficiency ◽  
Edge Computing ◽  
Third Party ◽  
Malicious Node ◽  
Time Decay ◽  
Fusion Algorithm ◽  
Trust Mechanism ◽  
Interactive Behavior ◽  
Source Trust

With the development of 5G, user terminal computing moves up and cloud computing sinks, thus forming a computing fusion at the edge. Edge computing with high-efficiency, real-time, and fast features will become part of 5G construction. Utilizing distributed computing and storage resources at the edge of the network to perform distributed data processing tasks can alleviate the load on the cloud computing center, which is also the development trend of edge computing. When a malicious node exists, the error information feedback by the node will affect the result of local perception decision. To solve the problem of malicious behavior of the node, a node trust evaluation mechanism of interactive behavior is introduced. The trust mechanism for edge computing network environments is introduced as a novel security solution. First, the key thought of the trust mechanism proposed in this paper is to establish a trust relationship between edge nodes in open edge computing environment. Then, a multi-source trust fusion algorithm based on time decay aggregates direct interaction trust and different third-party recommendation trust to calculate the global trust of the evaluated nodes. Finally, simulation experiments show that the algorithm has a certain degree of improvement in computational efficiency and interaction success rate over other existing models, which reduces the situation of malicious node deception.

scholarly journals Privacy in Cloud-Based Computing

2020 ◽  
pp. 239-252
Author(s):  
Monjur Ahmed ◽  
Nurul I. Sarkar
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Privacy ◽  
Fog Computing ◽  
Edge Computing ◽  
Third Party ◽  
Research Topics ◽  
Sensitive Data ◽  
Privacy Issues ◽  
Third Party Ownership

Cloud computing, internet of things (IoT), edge computing, and fog computing are gaining attention as emerging research topics and computing approaches in recent years. These computing approaches are rather conceptual and contextual strategies rather than being computing technologies themselves, and in practice, they often overlap. For example, an IoT architecture may incorporate cloud computing and fog computing. Cloud computing is a significant concept in contemporary computing and being adopted in almost every means of computing. All computing architectures incorporating cloud computing are termed as cloud-based computing (CbC) in general. However, cloud computing itself is the basis of CbC because it significantly depends on resources that are remote, and the remote resources are often under third-party ownership where the privacy of sensitive data is a big concern. This chapter investigates various privacy issues associated with CbC. The data privacy issues and possible solutions within the context of cloud computing, IoT, edge computing, and fog computing are also explored.

scholarly journals A Blockchain-Based Microgrid Data Disaster Backup Scheme in Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Lihua Zhang ◽  
Yu Cao ◽  
Ganzhe Zhang ◽  
Yang Huang ◽  
Chen Zheng
Keyword(s):  
High Efficiency ◽  
Distributed Storage ◽  
Current Data ◽  
Edge Computing ◽  
Third Party ◽  
Encryption Algorithm ◽  
Advanced Encryption Standard ◽  
Computing Environment ◽  
The Third ◽  
Traditional Proof

In view of the problems of low security, poor reliability, inability to backup automatically, and overreliance on the third party in traditional microgrid data disaster backup schemes based on cloud backup, the edge computing is used to preprocess power big data, and a microgrid data disaster backup scheme based on blockchain in edge computing environment is proposed in this paper. First, the honey encryption (HE) technology and advanced encryption standard (AES) are combined to propose a new encryption algorithm HE-AES, which is used to encrypt the preprocessed data. Second, the Kademlia algorithm is embedded in the edge server to realize the distributed storage and automatic recovery of microgrid data. Finally, the traditional proof of authority (PoA) consensus mechanism is improved partially, and the improved PoA is used to make each node reach consensus and pack blocks on the chain. The scheme can not only realize the data disaster backup automatically but also has high efficiency of data processing, which can provide a new idea for improving the current data disaster backup schemes.

scholarly journals Privacy in Cloud-Based Computing

2021 ◽  
pp. 154-168
Author(s):  
Monjur Ahmed ◽  
Nurul I. Sarkar
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Privacy ◽  
Fog Computing ◽  
Edge Computing ◽  
Third Party ◽  
Research Topics ◽  
Sensitive Data ◽  
Privacy Issues ◽  
Third Party Ownership

Cloud computing, internet of things (IoT), edge computing, and fog computing are gaining attention as emerging research topics and computing approaches in recent years. These computing approaches are rather conceptual and contextual strategies rather than being computing technologies themselves, and in practice, they often overlap. For example, an IoT architecture may incorporate cloud computing and fog computing. Cloud computing is a significant concept in contemporary computing and being adopted in almost every means of computing. All computing architectures incorporating cloud computing are termed as cloud-based computing (CbC) in general. However, cloud computing itself is the basis of CbC because it significantly depends on resources that are remote, and the remote resources are often under third-party ownership where the privacy of sensitive data is a big concern. This chapter investigates various privacy issues associated with CbC. The data privacy issues and possible solutions within the context of cloud computing, IoT, edge computing, and fog computing are also explored.

Issues in security and privacy of big data

2018 ◽  
Vol 7 (12) ◽  
pp. 1
Author(s):  
Shaveta Bhatia
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Approximate Method ◽  
Biomedical Research ◽  
Cyber Security ◽  
Data Science ◽  
Third Party ◽  
Security And Privacy ◽  
Security Threats ◽  
The Third

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

A Group Collaboratable Proof of Retrievability Scheme for Cloud Data Storage

2014 ◽  
Vol 13 (7) ◽  
pp. 4625-4632
Author(s):  
Jyh-Shyan Lin ◽  
Kuo-Hsiung Liao ◽  
Chao-Hsing Hsu
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Cloud Service ◽  
Third Party ◽  
Group Collaboration ◽  
Cloud Data ◽  
Cloud Data Storage ◽  
Important Trend ◽  
Data Update ◽  
Proof Of Retrievability

Cloud computing and cloud data storage have become important applications on the Internet. An important trend in cloud computing and cloud data storage is group collaboration since it is a great inducement for an entity to use a cloud service, especially for an international enterprise. In this paper we propose a cloud data storage scheme with some protocols to support group collaboration. A group of users can operate on a set of data collaboratively with dynamic data update supported. Every member of the group can access, update and verify the data independently. The verification can also be authorized to a third-party auditor for convenience.

scholarly journals A Survey on Mobile Edge Computing: Focusing on Service Adoption and Provision

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Kai Peng ◽  
Victor C. M. Leung ◽  
Xiaolong Xu ◽  
Lixin Zheng ◽  
Jiabin Wang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Mobile Networks ◽  
Edge Computing ◽  
Computation Offloading ◽  
Battery Life ◽  
Mobile Edge Computing ◽  
Service Adoption ◽  
Comprehensive Survey ◽  
And Storage ◽  
Execution Delay

Mobile cloud computing (MCC) integrates cloud computing (CC) into mobile networks, prolonging the battery life of the mobile users (MUs). However, this mode may cause significant execution delay. To address the delay issue, a new mode known as mobile edge computing (MEC) has been proposed. MEC provides computing and storage service for the edge of network, which enables MUs to execute applications efficiently and meet the delay requirements. In this paper, we present a comprehensive survey of the MEC research from the perspective of service adoption and provision. We first describe the overview of MEC, including the definition, architecture, and service of MEC. After that we review the existing MUs-oriented service adoption of MEC, i.e., offloading. More specifically, the study on offloading is divided into two key taxonomies: computation offloading and data offloading. In addition, each of them is further divided into single MU offloading scheme and multi-MU offloading scheme. Then we survey edge server- (ES-) oriented service provision, including technical indicators, ES placement, and resource allocation. In addition, other issues like applications on MEC and open issues are investigated. Finally, we conclude the paper.

scholarly journals Enabling Efficient Decentralized and Privacy Preserving Data Sharing in Mobile Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jiawei Zhang ◽  
Ning Lu ◽  
Teng Li ◽  
Jianfeng Ma
Keyword(s):  
Cloud Computing ◽  
Access Control ◽  
Mobile Devices ◽  
Data Sharing ◽  
Mobile Cloud Computing ◽  
High Efficiency ◽  
Mobile Cloud ◽  
User Privacy ◽  
Access Policy ◽  
Fine Grained

Mobile cloud computing (MCC) is embracing rapid development these days and able to provide data outsourcing and sharing services for cloud users with pervasively smart mobile devices. Although these services bring various conveniences, many security concerns such as illegally access and user privacy leakage are inflicted. Aiming to protect the security of cloud data sharing against unauthorized accesses, many studies have been conducted for fine-grained access control using ciphertext-policy attribute-based encryption (CP-ABE). However, a practical and secure data sharing scheme that simultaneously supports fine-grained access control, large university, key escrow free, and privacy protection in MCC with expressive access policy, high efficiency, verifiability, and exculpability on resource-limited mobile devices has not been fully explored yet. Therefore, we investigate the challenge and propose an Efficient and Multiauthority Large Universe Policy-Hiding Data Sharing (EMA-LUPHDS) scheme. In this scheme, we employ fully hidden policy to preserve the user privacy in access policy. To adapt to large scale and distributed MCC environment, we optimize multiauthority CP-ABE to be compatible with large attribute universe. Meanwhile, for the efficiency purpose, online/offline and verifiable outsourced decryption techniques with exculpability are leveraged in our scheme. In the end, we demonstrate the flexibility and high efficiency of our proposal for data sharing in MCC by extensive performance evaluation.

scholarly journals High Security Mechanism: Fragmentation and Replication in the Cloud with Auto Update in the System.

2020 ◽  
Vol 5 (2) ◽  
pp. 54-59
Author(s):  
Shrutika Khobragade ◽  
Rohini Bhosale ◽  
Rahul Jiwahe
Keyword(s):  
Cloud Computing ◽  
Low Cost ◽  
Vital Role ◽  
Third Party ◽  
Key Generation ◽  
Huge Amount ◽  
Security Issues ◽  
Hash Key ◽  
Use Of Internet ◽  
High Quality Service

Cloud Computing makes immense use of internet to store a huge amount of data. Cloud computing provides high quality service with low cost and scalability with less requirement of hardware and software management. Security plays a vital role in cloud as data is handled by third party hence security is the biggest concern to matter. This proposed mechanism focuses on the security issues on the cloud. As the file is stored at a particular location which might get affected due to attack and will lost the data. So, in this proposed work instead of storing a complete file at a particular location, the file is divided into fragments and each fragment is stored at various locations. Fragments are more secured by providing the hash key to each fragment. This mechanism will not reveal all the information regarding a particular file even after successful attack. Here, the replication of fragments is also generated with strong authentication process using key generation. The auto update of a fragment or any file is also done here. The concept of auto update of filles is done where a file or a fragment can be updated online. Instead of downloading the whole file, a fragment can be downloaded to update. More time is saved using this methodology.

Sign in / Sign up

Export Citation Format

Share Document