A Sub Chunk-Confusion Based Privacy Protection Mechanism for Association Rules in Cloud Services

2016 ◽  
Vol 26 (04) ◽  
pp. 539-562 ◽  
Author(s):  
Yuliang Shi ◽  
Zhongmin Zhou ◽  
Lizhen Cui ◽  
Shijun Liu
Keyword(s):  
Association Rules ◽  
Privacy Protection ◽  
Data Privacy ◽  
Cloud Services ◽  
Protection Mechanism ◽  
Security Issues ◽  
Computing Services ◽  
Real World Applications ◽  
Protection Technology ◽  
Cloud Computing Services

In cloud computing services, according to the customized privacy protection policy by the tenant and the sub chunk-confusion based on privacy protection technology, we can partition the tenant’s data into many chunks and confuse the relationships among chunks, which makes the attacker cannot infer tenant’s information by simply combining attributes. But it still has security issues. For example, with the amount of data growing, there may be a few hidden association rules among some attributes of the data chunks. Through these rules, it is possible to get some of the privacy information of the tenant. To address this issue, the paper proposes a privacy protection mechanism based on chunk-confusion privacy protection technology for association rules. The mechanism can detect unidimensional and multidimensional attributes association rules, hide them by adding fake data, re-chunking and re-grouping, and then ensure the privacy of tenant’s data. In addition, this mechanism also provides evaluation formulas. They filter detected association rules, remove the invalid and improve system performance. They also evaluate the effect of privacy protection. The experimental evaluation proves that the mechanism proposed in this paper can better protect the data privacy of tenant and has feasibility and practicality in real world applications.

scholarly journals A Comprehensive Review on Cloud Computing and Cloud Security Issues

2020 ◽  
pp. 483-490
Author(s):  
Supongmen Walling
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Primary Objective ◽  
Cloud Services ◽  
It Infrastructure ◽  
Security Issues ◽  
Computing Services ◽  
Processing Power ◽  
Wide Range ◽  
Cloud Computing Services

Cloud computing is a type of computing where computing services such as applications, storage, infrastructure, processing power are hosted by some vendors (cloud vendors) over the Internet and delivered to users on on-demand basis. A company can benefit from cloud computing in the sense that they can rent access to anything from applications to storage to processing power rather than owning their own IT infrastructure. By using cloud-computing services, companies can avoid the various costs and complexities associated with owning and maintaining their own IT infrastructure as everything is taken care of by the service providers. Cloud computing is a paradigm in which both the users and the service providers are benefited. Service providers are greatly benefited from cloud computing by providing cloud services to a wide range of customers. The primary objective of this paper is to give an overview on cloud computing encompassing its features, the pros and cons of cloud computing and the challenges that comes with it. Furthermore, this paper also presents a list of security concerns in cloud computing which stands in the way of wide spread adoption of cloud computing thereby motivating researchers to devise competent solutions to tackle these ongoing security issues.

An enhanced algorithm for scheduling dependent tasks in cloud computing environment

2021 ◽  
Vol 27 (2) ◽  
Author(s):  
H. Hamza ◽  
A.F.D Kana ◽  
M.Y. Tanko ◽  
S. Aliyu
Keyword(s):  
Cloud Computing ◽  
Turnaround Time ◽  
Cloud Services ◽  
Computing Environment ◽  
Computing Services ◽  
Average Improvement ◽  
Cloud Computing Services ◽  
User Tasks ◽  
Search Approach ◽  
Dependent Tasks

Cloud computing is a model that aims to deliver a reliable, customizable and scalable computing environment for end-users. Cloud computing is one of the most widely used technologies embraced by sectors and academia, offering a versatile and effective way to store and retrieve documents. The performance and efficiency of cloud computing services always depend upon the performance of the execution of user tasks submitted to the cloud system. Scheduling of user tasks plays a significant role in improving the performance of cloud services. Accordingly, many dependent task scheduling algorithms have been proposed to improve the performance of cloud services and resource utilization; however, most of the techniques for determining which task should be scheduled next are inefficient. This research provided an enhanced algorithm for scheduling dependent tasks in cloud that aims at improving the overall performance of the system. The Dependent tasks were represented as a directed acyclic graph (DAG) and the number of dependent tasks and their total running time were used as a heuristic for determining which path should be explored first. Best first search approach based on the defined heuristic was used to traverse the graph to determine which task should be scheduled next. The results of the simulation using WorkflowSim toolkit showed an average improvement of 18% and 19% on waiting time and turnaround time were achieved respectively.

Privacy Preserving and Efficient Outsourcing Algorithm to Public Cloud

2021 ◽  
pp. 857-878
Author(s):  
Malay Kumar ◽  
Manu Vardhan
Keyword(s):  
Data Privacy ◽  
Classification Systems ◽  
Third Party ◽  
Cloud Data ◽  
Computing Services ◽  
Cloud Server ◽  
Cloud Computing Services ◽  
Cloud Data Centers ◽  
Outsourcing Algorithm ◽  
Direct Implementation

The growth of the cloud computing services and its proliferation in business and academia has triggered enormous opportunities for computation in third-party data management settings. This computing model allows the client to outsource their large computations to cloud data centers, where the cloud server conducts the computation on their behalf. But data privacy and computational integrity are the biggest concern for the client. In this article, the authors attempt to present an algorithm for secure outsourcing of a covariance matrix, which is the basic building block for many automatic classification systems. The algorithm first performs some efficient transformation to protect the privacy and verify the computed result produced by the cloud server. Further, an analytical and experimental analysis shows that the algorithm is simultaneously meeting the design goals of privacy, verifiability and efficiency. Also, found that the proposed algorithm is about 7.8276 times more efficient than the direct implementation.

The Empirical Analysis of Cloud Computing Services among the Hungarian Enterprises

2016 ◽  
pp. 1162-1190
Author(s):  
Peter Sasvari ◽  
Zoltán Nagymate
Keyword(s):  
Cloud Computing ◽  
Information Flow ◽  
Data Security ◽  
Basic Concept ◽  
Remote Access ◽  
Security Issues ◽  
Computing Services ◽  
Cloud Computing Services ◽  
System Breakdown ◽  
The Empirical Analysis

Innovation capability has increasingly been searched by the ICT sector in cloud computing applications recently. This chapter describes the economic potentials of cloud computing and explores the characteristics of its usage among Hungarian enterprises. Although enterprises are aware of the basic concept of cloud computing, they have concerns about its application mainly due to data security issues and the lack of education. The chance of using cloud computing services is mainly facilitated by the creation of easier application and consultation would positively affect their usage. According to microenterprises and corporations, faster information flow and remote access are the key benefits of cloud usage. In the case of small-sized enterprises, the two main advantages are easier system recoverability and a higher level of mobility in case of a system breakdown. For the medium-sized enterprises, remote access and greater data security were the key benefits of using cloud computing services in 2014.

Emerging Cloud Computing Services

2016 ◽  
Vol 6 (4) ◽  
pp. 98-102
Author(s):  
Yulin Yao
Keyword(s):  
Cloud Computing ◽  
Mobile Services ◽  
Cloud Services ◽  
Software As A Service ◽  
Current Status ◽  
Computing Services ◽  
The Future ◽  
Cloud Computing Services ◽  
Future Direction ◽  
Positive Impacts

Cloud Computing has offered many services to organizations and individuals. The emerging types of services such as analytics, mobile services and emerging software as a service have been offered but there is a lack of analysis on the current status. Core technologies for emerging Cloud services have been identified and presented. This brief opinion paper provides an overview of the current emerging Cloud services and explains the benefits for several disciplines. Four areas have been identified that may bring in more positive impacts for the future direction.

Privacy Preserving and Efficient Outsourcing Algorithm to Public Cloud

2018 ◽  
Vol 12 (2) ◽  
pp. 1-25 ◽  
Author(s):  
Malay Kumar ◽  
Manu Vardhan
Keyword(s):  
Data Privacy ◽  
Classification Systems ◽  
Third Party ◽  
Cloud Data ◽  
Computing Model ◽  
Computing Services ◽  
Cloud Server ◽  
Cloud Computing Services ◽  
Cloud Data Centers ◽  
Outsourcing Algorithm

The growth of the cloud computing services and its proliferation in business and academia has triggered enormous opportunities for computation in third-party data management settings. This computing model allows the client to outsource their large computations to cloud data centers, where the cloud server conducts the computation on their behalf. But data privacy and computational integrity are the biggest concern for the client. In this article, the authors attempt to present an algorithm for secure outsourcing of a covariance matrix, which is the basic building block for many automatic classification systems. The algorithm first performs some efficient transformation to protect the privacy and verify the computed result produced by the cloud server. Further, an analytical and experimental analysis shows that the algorithm is simultaneously meeting the design goals of privacy, verifiability and efficiency. Also, found that the proposed algorithm is about 7.8276 times more efficient than the direct implementation.

SLA (Service Level Agreement) Driven Orchestration Based New Methodology for Cloud Computing Services

2013 ◽  
Vol 660 ◽  
pp. 196-201 ◽  
Author(s):  
Muhammad Irfan ◽  
Zhu Hong ◽  
Nueraimaiti Aimaier ◽  
Zhu Guo Li
Keyword(s):  
Cloud Computing ◽  
Computer Science ◽  
Service Providers ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Computing Services ◽  
Cloud Service Providers ◽  
Cloud Computing Services

Cloud Computing is not a revolution; it’s an evolution of computer science and technology emerging by leaps and bounds, in order to merge all computer science tools and technologies. Cloud Computing technology is hottest to do research and explore new horizons of next generations of Computer Science. There are number of cloud services providers (Amazon EC2), Rackspace Cloud, Terremark and Google Compute Engine) but still enterprises and common users have a number of concerns over cloud service providers. Still there is lot of weakness, challenges and issues are barrier for cloud service providers in order to provide cloud services according to SLA (Service Level agreement). Especially, service provisioning according to SLAs is core objective of each cloud service provider with maximum performance as per SLA. We have identified those challenges issues, as well as proposed new methodology as “SLA (Service Level Agreement) Driven Orchestration Based New Methodology for Cloud Computing Services”. Currently, cloud service providers are using “orchestrations” fully or partially to automate service provisioning but we are trying to integrate and drive orchestration flows from SLAs. It would be new approach to provision cloud service and deliver cloud service as per SLA, satisfying QoS standards.

scholarly journals Privacy and Security in Data-Driven Urban Mobility

2019 ◽  
pp. 106-128 ◽  
Author(s):  
Rajendra Akerkar
Keyword(s):  
Privacy Protection ◽  
Data Privacy ◽  
Evidence Base ◽  
Urban Mobility ◽  
Privacy And Security ◽  
Security Issues ◽  
Wide Range ◽  
Beneficial Uses ◽  
Smart Mobility ◽  
Data Privacy Protection

A wide range of smart mobility technologies are being deployed within urban environment. These technologies generate huge quantities of data, much of them in real-time and at a highly granular scale. Such data about mobility, transport, and citizens can be put to many beneficial uses and, if shared, for uses beyond the system and purposes for which they were generated. Jointly, these data create the evidence base to run mobility services more efficiently, effectively, and sustainably. However, generating, processing, analyzing, sharing, and storing vast amounts of actionable data also raises several concerns and challenges. For example, data privacy, data protection, and data security issues arise from the creation of smart mobility. This chapter highlights the various privacy and security concerns and harms related to the deployment and use of smart mobility technologies and initiatives, and makes suggestions for addressing apprehensions about and harms arising from data privacy, protection, and security issues.

scholarly journals Building a Reputation Attack Detector for Effective Trust Evaluation in a Cloud Services Environment

2021 ◽  
Vol 11 (18) ◽  
pp. 8496
Author(s):  
Salah T. Alshammari ◽  
Khalid Alsubhi
Keyword(s):  
Cloud Computing ◽  
Trust Management ◽  
Trust Model ◽  
Cloud Services ◽  
Security Risk ◽  
Privacy And Security ◽  
Collusion Attack ◽  
Inappropriate Behaviors ◽  
Computing Services ◽  
Cloud Computing Services

Cloud computing is a widely used technology that has changed the way people and organizations store and access information. This technology is versatile, and extensive amounts of data can be stored in the cloud. Businesses can access various services over the cloud without having to install applications. However, cloud computing services are provided over a public domain, which means that both trusted and non-trusted users can access the services. Although there are a number of advantages to cloud computing services, especially for business owners, various challenges are posed in terms of the privacy and security of information and online services. A threat that is widely faced in the cloud environment is the on/off attack, in which entities exhibit proper behavior for a given time period to develop a positive reputation and gather trust, after which they exhibit deception. Another threat often faced by trust management services is a collusion attack, which is also known as collusive malicious feedback behavior. This is carried out when a group of people work together to make false recommendations with the intention of damaging the reputation of another party, which is referred to as a slandering attack, or to enhance their own reputation, which is referred to as a self-promoting attack. In this paper, a viable solution is provided with the given trust model for preventing these attacks. This method works by providing effective security to cloud services by identifying malicious and inappropriate behaviors through the application of trust algorithms that can identify on/off attacks and collusion attacks by applying different security criteria. Finally, the results show that the proposed trust model system can provide high security by decreasing security risk and improving the quality of decisions of data owners and cloud operators.

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