scholarly journals Privacy Preservation of Healthcare Data in Hybrid Cloud using a Hybrid Meta-Heuristics Based Sanitization Technique

2019 ◽  
Vol 8 (4) ◽  
pp. 2882-2890
Keyword(s):  
Side Effects ◽  
Search Algorithm ◽  
Cloud Model ◽  
Gravitational Search Algorithm ◽  
Data Access ◽  
Privacy Preserving ◽  
Cloud Services ◽  
Sensitive Information ◽  
Hybrid Cloud ◽  
Healthcare Data

Over the recent years, the expansion of cloud computing services enable hospitals and institutions to transit their healthcare data to the cloud, thus it provides the worldwide data access and on-demand high quality services at a cheaper rate. Despite the benefits of healthcare cloud services, the associated privacy issues are widely concerned by individuals and governments. Privacy risks rise when outsourcing personal healthcare records to cloud due to the sensitive nature of health information and the social and legal implications for its disclosure. Over the recent years, a privacy-preserving data mining (PPDM) technique has become a critical issue for the problems. Our goal is to design a privacy-preserving outsourcing framework under the hybrid cloud model. In this work we propose a Hybrid Ant Colony Optimization and Gravitational Search Algorithm (ACOGSA) to express the problem of hiding sensitive data through transaction deletion. Thus, it reduces the side effects of the hybrid cloud. Substantive experiments will be carried to compare the performance of the designed algorithm with the state-of-the-art approaches in terms of the side effects and database similarity (integrity). Over the past to sanitize the databases used for hiding sensitive information, a few heuristic approaches have been proposed. The method used for the comparison involves GA, PSO, ACO, and Firefly framework.

Anonymization Based on Improved Bucketization (AIB): A Privacy-Preserving Data Publishing Technique for Improving Data Utility in Healthcare Data

2021 ◽  
Vol 11 (12) ◽  
pp. 3164-3173
Author(s):  
R. Indhumathi ◽  
S. Sathiya Devi
Keyword(s):  
Medical Information ◽  
Threshold Value ◽  
Privacy Preserving ◽  
Data Publishing ◽  
Published Data ◽  
Sensitive Information ◽  
Data Utility ◽  
Healthcare Data ◽  
Privacy Preserving Data Publishing ◽  
Horizontal Partitioning

Data sharing is essential in present biomedical research. A large quantity of medical information is gathered and for different objectives of analysis and study. Because of its large collection, anonymity is essential. Thus, it is quite important to preserve privacy and prevent leakage of sensitive information of patients. Most of the Anonymization methods such as generalisation, suppression and perturbation are proposed to overcome the information leak which degrades the utility of the collected data. During data sanitization, the utility is automatically diminished. Privacy Preserving Data Publishing faces the main drawback of maintaining tradeoff between privacy and data utility. To address this issue, an efficient algorithm called Anonymization based on Improved Bucketization (AIB) is proposed, which increases the utility of published data while maintaining privacy. The Bucketization technique is used in this paper with the intervention of the clustering method. The proposed work is divided into three stages: (i) Vertical and Horizontal partitioning (ii) Assigning Sensitive index to attributes in the cluster (iii) Verifying each cluster against privacy threshold (iv) Examining for privacy breach in Quasi Identifier (QI). To increase the utility of published data, the threshold value is determined based on the distribution of elements in each attribute, and the anonymization method is applied only to the specific QI element. As a result, the data utility has been improved. Finally, the evaluation results validated the design of paper and demonstrated that our design is effective in improving data utility.

scholarly journals Device-Based Security to Improve User Privacy in the Internet of Things †

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2664 ◽  
Author(s):  
Luis Belem Pacheco ◽  
Eduardo Pelinson Alchieri ◽  
Priscila Mendez Barreto
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Single Point ◽  
Data Access ◽  
Cloud Services ◽  
Sensitive Information ◽  
User Privacy ◽  
Privacy And Security ◽  
Iot Devices ◽  
And Control

The use of Internet of Things (IoT) is rapidly growing and a huge amount of data is being generated by IoT devices. Cloud computing is a natural candidate to handle this data since it has enough power and capacity to process, store and control data access. Moreover, this approach brings several benefits to the IoT, such as the aggregation of all IoT data in a common place and the use of cloud services to consume this data and provide useful applications. However, enforcing user privacy when sending sensitive information to the cloud is a challenge. This work presents and evaluates an architecture to provide privacy in the integration of IoT and cloud computing. The proposed architecture, called PROTeCt—Privacy aRquitecture for integratiOn of internet of Things and Cloud computing, improves user privacy by implementing privacy enforcement at the IoT devices instead of at the gateway, as is usually done. Consequently, the proposed approach improves both system security and fault tolerance, since it removes the single point of failure (gateway). The proposed architecture is evaluated through an analytical analysis and simulations with severely constrained devices, where delay and energy consumption are evaluated and compared to other architectures. The obtained results show the practical feasibility of the proposed solutions and demonstrate that the overheads introduced in the IoT devices are worthwhile considering the increased level of privacy and security.

An Architecture Paradigm for Providing Cloud Services in School Labs Based on Open Source Software to Enhance ICT in Education

2012 ◽  
Vol 2 (1) ◽  
pp. 44-57 ◽  
Author(s):  
Yannis Siahos ◽  
Iasonas Papanagiotou ◽  
Alkis Georgopoulos ◽  
Fotis Tsamis ◽  
Ioannis Papaioannou
Keyword(s):  
Classroom Management ◽  
Open Source ◽  
Open Source Software ◽  
Educational Software ◽  
Cloud Model ◽  
Cloud Services ◽  
Hybrid Cloud ◽  
Information Communication ◽  
Cloud Infrastructure ◽  
On Line

The authors present their experience and practices of introducing cloud services, as a means to simplify the adoption of ICT (Information Communication and Technology) in education, using Free/Open Source Software. The solution creates a hybrid cloud infrastructure, in order to provide a pre-installed (Ubuntu and Linux Terminal Server Project) virtual machine, acting as a server inside the school, providing desktop environment based on the Software as a Service cloud model, where legacy PCs act as stateless devices. Classroom management is accomplished using the application “Epoptes.” To minimize administration tasks, educational software is provided accordingly, either on-line or through repositories to automate software installation (including patches and updates). The advantages of the hybrid cloud implementation, include services that are not completely dependent on broadband connections’ state, minimal cost, reusability of obsolete equipment, ease of administration, centralized management, patches and educational software provisioning and, above all, facilitation of the educational procedure.

Implementing a Hybrid Cloud Infrastructure to Facilitate ICT in Education

2014 ◽  
pp. 1-18
Author(s):  
Yannis Siahos ◽  
Iasonas Papanagiotou ◽  
Alkis Georgopoulos ◽  
Fotis Tsamis ◽  
Lefteris Nikoltsios
Keyword(s):  
Classroom Management ◽  
Educational Software ◽  
Cloud Model ◽  
Cloud Services ◽  
Software As A Service ◽  
Hybrid Cloud ◽  
Ict In Education ◽  
Cloud Infrastructure ◽  
Modern School ◽  
Centralized Management

In this chapter, the authors present the methodology and the results of their effort towards the introduction of cloud services as a means to simplify the adoption of ICT in education using Free/Open Source Software. A hybrid cloud infrastructure is established in order to provide Linux and optionally MS-Windows desktop environments with the Software as a Service cloud model. Legacy and modern school PCs function as stateless devices. To achieve this, their “Sch-scripts” application performs an unattended installation of the Linux Terminal Server Project software to a school computer that also hosts centrally maintained virtual machines. Classroom management is accomplished using their “Epoptes” application. Administration is only required in the school server while the educational software is provided with the Software as a Service model either in online form or through repositories that automate software installation. Four-hundred-twenty schools have already implemented this architecture and 117 responded to the evaluation survey. The statistical analysis of these answers confirms the design principles, which include minimal cost, as well as reusability of obsolete equipment, ease of administration, centralized management, patches and educational software provisioning, classroom management, and above all, facilitation of the educational procedure.

scholarly journals A China Railway Express-Based Model for Designing a Cross-Border Logistics Information Cloud Platform Scheme

2020 ◽  
Vol 10 (12) ◽  
pp. 4110
Author(s):  
Qian Huang ◽  
Weichuan Yin ◽  
Jiuyu An ◽  
Yuanxiang Zhou
Keyword(s):  
Service Management ◽  
Cloud Model ◽  
Value Added ◽  
Cloud Services ◽  
Hybrid Cloud ◽  
Cloud Platform ◽  
Cross Border ◽  
China Railway ◽  
Logistics Information ◽  
Management Functions

This paper describes the development and plans for the implementation of a cloud-based logistics platform to enable and optimize cross-border shipping, using the China Railway Express (CR Express) in the context of China’s recent One Belt and One Road (OBOR) initiative as an example of an extremely complex system that is running at suboptimal efficiency. We design a cross-border logistics information cloud platform (CLICP) and its architecture. The proposed CLICP comprises a hybrid cloud model with three layers of cloud services. We also examine the CLICP’s operation and the design of the platform’s functions, including core business and value-added service functions, such as real-time bidding, freight information push, and carrier one-stop service management functions. Finally, we propose a model for deploying our CLICP. Our study makes a significant contribution to the literature because of its hybrid cloud model architecture and for the completeness of its functionality. The study also has a good application prospect for the operation of CR Express and will play a better supporting role in cross-border logistics.

Privacy Preserving Through Fireworks Algorithm Based Model for Image Perturbation in Big Data

2015 ◽  
Vol 6 (3) ◽  
pp. 41-58 ◽  
Author(s):  
Amine Rahmani ◽  
Abdelmalek Amine ◽  
Reda Mohamed Hamou ◽  
Mohamed Elhadi Rahmani ◽  
Hadj Ahmed Bouarara
Keyword(s):  
Big Data ◽  
Search Algorithm ◽  
Iterated Local Search ◽  
Privacy Preserving ◽  
Cloud Services ◽  
Local Search Algorithm ◽  
Medical Studies ◽  
Fireworks Algorithm ◽  
The Third ◽  
Highly Sensitive

Nowadays, Social networks and cloud services contain billions of users over the planet. Instagram, Facebook and other networks give the opportunity to share images. Users upload millions of pictures each day, including personal images. Another domain, which concerns medical studies, requires a highly sensitive medical images that retain personal details close to patients. Image perturbation have attracted a great deal of attention in the last few years. Many works concerning image ciphering and perturbing have been published. This paper deals with the problem of image perturbation for privacy preserving. The authors build three new systems that consist of hiding small details in pictures by rotating some pixels. Their models use two algorithms: the first one involves a simulation of the firework algorithm in which they place fireworks on selected pixels then represents sparks as rotation processes. The second system consists of a model of rotation based perturbation using iterated local search algorithm (ILS) with 2 optimization stages. Meanwhile, the third one consists of using the same principle of the previous system except by using the ILS algorithm with 3 optimization stages.

scholarly journals A Privacy Preserving Cloud-Based K-NN Search Scheme with Lightweight User Loads

Computers ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 1 ◽  
Author(s):  
Yeong-Cherng Hsu ◽  
Chih-Hsin Hsueh ◽  
Ja-Ling Wu
Keyword(s):  
Data Privacy ◽  
Nearest Neighbor ◽  
Search Algorithm ◽  
Data Access ◽  
Privacy Preserving ◽  
Secret Key ◽  
K Nearest Neighbor ◽  
Sensitive Data ◽  
Cloud Data ◽  
Cloud Server

With the growing popularity of cloud computing, it is convenient for data owners to outsource their data to a cloud server. By utilizing the massive storage and computational resources in cloud, data owners can also provide a platform for users to make query requests. However, due to the privacy concerns, sensitive data should be encrypted before outsourcing. In this work, a novel privacy preserving K-nearest neighbor (K-NN) search scheme over the encrypted outsourced cloud dataset is proposed. The problem is about letting the cloud server find K nearest points with respect to an encrypted query on the encrypted dataset, which was outsourced by data owners, and return the searched results to the querying user. Comparing with other existing methods, our approach leverages the resources of the cloud more by shifting most of the required computational loads, from data owners and query users, to the cloud server. In addition, there is no need for data owners to share their secret key with others. In a nutshell, in the proposed scheme, data points and user queries are encrypted attribute-wise and the entire search algorithm is performed in the encrypted domain; therefore, our approach not only preserves the data privacy and query privacy but also hides the data access pattern from the cloud server. Moreover, by using a tree structure, the proposed scheme could accomplish query requests in sub-liner time, according to our performance analysis. Finally, experimental results demonstrate the practicability and the efficiency of our method.

scholarly journals Secured Processing of Data Over Cloud using Disjoint Multi Attribute Authority Scheme for Key Generation

2020 ◽  
Vol 9 (5) ◽  
pp. 2230-2233
Keyword(s):  
Data Access ◽  
Cloud Services ◽  
Third Party ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Key Generation ◽  
Multiple Attribute ◽  
Efficient Data ◽  
Small File ◽  
Selection Of

Cloud computing being the extensive technology used across globe for data sharing. The data may vary from small file to a highly confidential file consisting of various sensitive information stored in it. Since the cloud services are provided by the third party vendors, users are very much concerned about the security and privacy of the data and data access details. The users wants their traceability to be hidden by the cloud vendors. The biggest challenge is to share the data in a most secured way by encrypting and also preserving the anonymity of the users in cloud from the vendors. This paper addresses the issue by proposing a multi attribute authority in key generations of users, where the few sub sets of attributes will be used by multiple attribute authorities randomly and hence masking of the selection of attributes from various authorities and providing a mechanism for efficient data distribution in cloud by preserving the anonymity of the users.

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