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In this paper we propose a new method to anonymize (share relevant and detailed information while not naming names) and protect data sets (minimize the utility loss) based on Factor Analysis. The method basically consists of obtaining the factors, which are uncorrelated, protecting them and undoing the transformation in order to get interpretable protected variables. We first show how to proceed when...
Performing smart computations in a context of cloud computing and big data is highly appreciated today. Fully homomorphic encryption (FHE) is a smart category of encryption schemes that allows working with the data in its encrypted form. It permits us to preserve confidentiality of our sensible data and to benefit from cloud computing powers. Currently, it has been demonstrated by many existing schemes...
For a long time, the sensitivity and criticality of data storage, processing, and transmission have hindered the wide utilization of IT and networks in the health care systems. Recently, the high availability, reachability, reliability, efficiency, usability and automation provided by the different cloud computing models paved the way to integrate the e-health systems with these cloud services to...
We show that it is possible to achieve information theoretic location privacy for secondary users (SUs) in database-driven cognitive radio networks (CRNs) with an end-to-end delay less than a second, which is significantly better than that of the existing alternatives offering only a computational privacy. This is achieved based on a keen observation that, by the requirement of Federal Communications...
Internet of Things (IoT) is slowly but steadily becoming part of different aspects of our lives, with its applications ranging from smart homes, to wearable devices, to healthcare, etc. This wide spectrum of applications results in shared data containing large amount of users' private information. The security of such information becomes a paramount concern. The IoT security requirements include data...
The database-driven CRN has emerged as a promising solution for the spectrum scarcity issue. However, it also raises severe privacy concerns. Although there are some existing works on this topic, they are far from practical due to their restrict on particular database structures or extremely heavy computation and communication overhead. To address these issues, in this paper we develop two practical...
The increasing collection and use of sensitive datasets in science, coupled with the need for inter-institutional collaboration, poses new challenges for infrastructure and administrative models. While enclaves, such as CLOUD KOTTA, provide for the secure management and analysis of data, they do not yet support the administrative models needed by today's researcher practices. Current approaches often...
The iKaaS platform has been developed as a Horizon 2020 project to construct a multi-cloud environment in order to share data and knowledge. In this paper, we add a framework for knowledge sharing/reuse in the iKaaS platform. Furthermore, we design a revenue-sharing mechanism for knowledge sharing, which uses a blockchain for registration and use of data processing services.
Companies are obliged to have privacy policies in place to notify the users about their privacy practices. However, privacy policies are not generally efficient and they fail to help users make informed decisions. The privacy policy challenges get worse when dealing with Internet of Things (IoT) as these devices have access to very sensitive data about users. Much research have addressed these problems...
Mobile money is an upshot of the conventional banking system that creates an opportunity for the financially excluded group of people. It allows the unbanked in the rural areas and the underbanked in the urban centers to have access to financial services. User experience is all encompassing as it affects the emotion and the attitude of the user of a product or services. This study reviewed the related...
Use of smartphones in our everyday life has become widely popular. A large proportion of smartphones use Android OS, which supports third party software development, so there is increasing number of developers developing applications for the android platform. But this means there are significant privacy risks associated with the use of android based smartphone applications. In this paper the process...
The existing privacy-preserving data aggregation methods in wireless sensor networks (WSNs) generally rely on a network infrastructure, and data privacy is achieved by encryption techniques. However, such an infrastructure is very susceptible to the dynamic network topologies, and excessive encryption process causes a high energy consumption and re-duces the accuracy of the aggregation results. In...
Online professional social networks such as LinkedIn have enhanced the ability of job seekers to discover and assess career opportunities, and the ability of job providers to discover and assess potential candidates. For most job seekers, salary (or broadly compensation) is a crucial consideration in choosing a new job. At the same time, job seekers face challenges in learning the compensation associated...
Sharing and working on sensitive data in distributed settings from healthcare to finance is a major challenge due to security and privacy concerns. Secure multiparty computation (SMC) is a viable panacea for this, allowing distributed parties to make computations while the parties learn nothing about their data, but the final result. Although SMC is instrumental in such distributed settings, it does...
More data is currently being collected and shared by software applications than ever before. In many cases, the user is asked if either all or none of their data can be shared. We hypothesize that in some cases, users would like to share data in more complex ways. In order to implement the sharing of data using more complicated privacy preferences, complex data sharing policies must be used. These...
In distributed systems, there is often a need to combine the heterogeneous access control policies to offer more comprehensive services to users in the local or national level. A large scale healthcare system is usually distributed in a computer network and might require sophisticated access control policies to protect the system. Therefore, the need for integrating the electronic healthcare systems...
This paper aims to propose regulatory recommendations for IoT smart-health care service, by using the method of Privacy Impact Assessment (PIA). We utilize data from a relevant IoT smart-health care project in Indonesia. On structuring the final regulatory recommendations, we have conducted in-depth interview to the stake holders of Indonesian IoT smart-health care service. The results show that there...
Cloud Services have become an important part of the business world. Although public cloud services provide a range of advantages, it also creates concerns over security, network usage and the need for technical expertise in the management of the cloud. This paper describes a local private cloud which uses on-site hardware infrastructure and which incorporates a three tier management system. This device...
Patients' data security and privacy is fundamental in the perspective of moving clinical data over the Cloud. Indeed, this concern has slowed down the adoption of Cloud services in the healthcare context. In fact, clinical operators are reluctant to open Hospital Information Systems (HIS) to external Cloud services. In this paper, we discuss system developed at the IRCCS “Bonino Pulejo” clinical and...
There has been increasing interest in adopting BlockChain (BC), that underpins the crypto-currency Bitcoin, in Internet of Things (IoT) for security and privacy. However, BCs are computationally expensive and involve high bandwidth overhead and delays, which are not suitable for most IoT devices. This paper proposes a lightweight BC-based architecture for IoT that virtually eliminates the overheads...
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