User's Personal Device Research Articles

PRScalc, a privacy-preserving calculation of raw polygenic risk scores from direct-to-consumer genomics data.

Currently, the Polygenic Score (PGS) Catalog curates over 400 publications on over 500 traits corresponding to over 3000 polygenic risk scores (PRSs). To assess the feasibility of privately calculating the underlying multivariate relative risk for individuals with consumer genomics data, we developed an in-browserPRS calculator for genomic data that does not circulate any data or engage in any computation outside of the user's personal device. A prototype personal risk score calculator, created for research purposes, was developed to demonstrate how the PGS Catalog can be privately and readily applied to readily available direct-to-consumer genetic testing services, such as 23andMe. No software download, installation, or configuration is needed. The PRS web calculator matches individual PGS catalog entries with an individual's 23andMe genome data composed of 600k to 1.4 M single-nucleotide polymorphisms (SNPs). Beta coefficients provide researchers with a convenient assessment of risk associated with matched SNPs. This in-browser application was tested in a variety of personal devices, including smartphones, establishing the feasibility of privately calculating personal risk scores with up to a few thousand reference genetic variations and from the full 23andMe SNP data file (compressed or not). The PRScalc web application is developed in JavaScript, HTML, and CSS and is available at GitHub repository (https://episphere.github.io/prs) under an MIT license. The datasets were derived from sources in the public domain: [PGS Catalog, Personal Genome Project].

FedCDR: Privacy-preserving federated cross-domain recommendation

Cross-Domain Recommendation (CDR) aims to solve data sparsity and cold-start problems by utilizing a relatively information-rich source domain to improve the recommendation performance of the data-sparse target domain. However, most existing approaches rely on the assumption of centralized storage of user data, which undoubtedly poses a significant risk of user privacy leakage because user data are highly privacy-sensitive. To this end, we propose a privacy-preserving Federated framework for Cross-Domain Recommendation, called FedCDR. In our method, to avoid leakage of user privacy, a general recommendation model is trained on each user's personal device to obtain embeddings of users and items, and each client uploads weights to the central server. The central server then aggregates the weights and distributes them to each client for updating. Furthermore, because the weights implicitly contain private information about the user, local differential privacy is adopted for the gradients before uploading them to the server for better protection of user privacy. To distill the relationship of user embedding between two domains, an embedding transformation mechanism is used on the server side to learn the cross-domain embedding transformation model. Extensive experiments on real-world datasets demonstrate that our method achieves performance comparable with that of existing data-centralized methods and effectively protects user privacy.

ProCMotive

In recent years, numerous vehicular technologies, e.g., cruise control and steering assistant, have been proposed and deployed to improve the driving experience, passenger safety, and vehicle performance. Despite the existence of several novel vehicular applications in the literature, there still exists a significant gap between resources needed for a variety of vehicular (in particular, data-dominant, latency-sensitive, and computationally-heavy) applications and the capabilities of already-in-market vehicles. To address this gap, different smartphone-/Cloud-based approaches have been proposed that utilize the external computational/storage resources to enable new applications. However, their acceptance and application domain are still very limited due to programmability, wireless connectivity, and performance limitations, along with several security/privacy concerns. In this paper, we present a novel reference architecture that can potentially enable rapid development of various vehicular applications while addressing shortcomings of smartphone-/Cloud-based approaches. The architecture is formed around a core component, called SmartCore, a privacy/security-friendly programmable dongle that brings general-purpose computational and storage resources to the vehicle and hosts in-vehicle applications. Based on the proposed architecture, we develop an application development framework for vehicles, that we call ProCMotive. ProCMotive enables developers to build customized vehicular applications along the Cloud-to-edge continuum, i.e., different functions of an application can be distributed across SmartCore, the user's personal devices, and the Cloud. In order to highlight potential benefits that the framework provides, we design and develop two different vehicular applications based on ProCMotive, namely, Amber Response and Insurance Monitor. We evaluate these applications using real-world data and compare them with state-of-the-art technologies.

Trusted computing and security for computer folders

Data security is an important term which plays a major role in computers as the cyber-crimes are constantly on the rise in today's world. Unauthorized access to user's personal data is a major problem of the computer users. In some cases, the user will not be able to protect their personal data from being transferred from the user's personal device to another device without their knowledge leading to exposure of personal data. Besides that, due to these problems the user might not be able to identify the person who tries to access into their files or folders which may contains the personal data of the user. Providing extra security measures for such devices is a solution, but it may exhaust system resources in the process of securing all data on the device regardless of its sensitivity. Another solution for the problems, Trusted Computing and Security for Computer Folders is suggested. The first feature is a login system using biometric (voice based password) to access into the system for securing folders and files. Second is the encryption and decryption of selected files using AES algorithm. Lastly, an unauthorized user access image capture. These features helps to solve the problem stated. As a result, there will be a high possibility of protecting personal data of the user from being leaked without the owner's knowledge.

Ownership-guaranteed security framework for the private data in the entrusted management environment

In the environment like the Cloud computing or the picture archiving and communications systems (PACS) of the hospital, the user's data is stored in the storage of a third party. In such entrusted management environment, security is an important issue for the user's private data. The most basic solution is to encrypt user's private data. However, if the encryption key is directly managed by cloud service provider (CSP) or PACS service provider (PSP), there is latent threat when it comes to the data loss or leakage which may be committed by malicious insiders. The ownership-guaranteed security framework (OGSF) divides encryption key into a single mandatory fragment and multiple optional fragments while mandating user to store the mandatory fragment in the user's personal device and mandating CSP or PSP to manage the optional fragments. Because of this division of the management on the encryption key, the OGSF can resolve both threat from the malicious insider and the user's mistake in same time.

Design and Evaluation of a Collaborative System That Supports Distributed User Interfaces

Group work is a fundamental human activity in all areas of life; it is a good exercise to enhance integration and communication among users. In addition, it is highly effective in increasing users´ creativity, thus yielding better and more satisfactory results. This task is very complex; however, thanks to the benefits offered by new technologies, today we can build systems designed to facilitate such collaboration. This paper proposes the “Co-Interactive Table”: an interactive and intuitive system developed to enhance the collaboration in meeting rooms. It is based on mobile devices, RFID technology integrated in panels. This solution offers Distributed User Interfaces and a new style of interaction, which consists of bringing the mobile device close to the panel. To improve collaboration, the workspaces are divided into two spaces, collaborative and public, which consist of a display projected on the wall, and the personal and private spaces, which consist of the user's personal device. An assessment has been carried out in order to verify user satisfaction in performing tasks with this system.

Nomadic gestures: A technique for reusing gesture commands for frequent ambient interactions

The age of ambient intelligence has already incorporated gestures into practical applications with the goal of delivering adaptive and personalized interactions. However, practitioners are faced with many problems when implementing gesture-based interfaces for such interactive ambient systems. Although gestures offer great opportunity for natural and intuitive interactions, there are currently little to no rules for creating the set of gestures for a given application. Therefore, designers associate gestures and functions by relying only on their own expertize and experience which leads to different systems exposing different standards. This approach does not only create the premises for confusion among users in a future world with such hundreds daily interactions but it also contradicts the goals of ambient intelligence in which interaction should be personalized and adapted to each user. This work introduces a novel concept (nomadic gestures) for reusing a set of user-defined gesture commands in the context of interacting with ambient systems. Nomadic gestures live on each user's personal mobile device and are uploaded to the ambient system prior to interaction. The concept relies on an important shift of perspective strictly adhering to the goals of ambient intelligence: it is not the users that adapt to the interface learning its commands but instead the interface employs the users' own gesture sets with their own preferred function associations.

Securing the Communication in Private Heterogeneous Mobile Ad hoc Networks

Mobile ad hoc networking has been a hot research topic for a decade or so, and many paradigms have been making use of it. One of these paradigms is the Personal Networks (PN). It is an emerging concept where the user's personal devices form a virtual network which is secure and private, and reacts to changing environment and context intelligently. A fundamental property of the PN is that personal devices form private multi-hop clusters in an ad hoc manner whenever they come across each other. To this end, this paper presents a pair-wise key based scheme for forming secured private clusters in mobile ad hoc networks. The solution tackles the problem of node authentication combined with traffic encryption in relatively small ad hoc networks using proactive neighbour discovery and authentication. Additionally, the paper proves the feasibility of this solution by means of prototyping and experimental performance analysis.

Standards, tools & best practices - The universal remote console: a universal access bus for pervasive computing

V2, a technical committee of the International Committee for information technology standards is developing standards for information technology access interfaces. As part of this endeavor, V2 is to issue the Universal Remote Console architecture, a set of draft standards for public review and comment. The five standards specify communications between a Target - a device or service the user wishes to access and a universal remote console-software that is typically hosted on a user's personal device. The standards specify mechanisms for the discovery, selection, configuration, and operation of user interfaces and its options.