Umcloud: a user-oriented security scheme for mobile cloud storage

Attribute-based encryption (ABE) is suitable for mobile cloud storage to protect data confidentiality and realize fine-grained data access control. It is essential for ABE schemes to achieve attribute revocation as users’ attributes may be changed frequently. Keyword search over encrypted data also needs to be solved in the mobile cloud storage. In addition, computational efficiency is a consideration for the resource-constrained mobile device. Focusing on the above-mentioned problems, an efficiently revocable and searchable ABE (RSABE) scheme for the mobile cloud storage is proposed. In our scheme, the function of attribute revocation is efficiently achieved by delegating the update of secret key and ciphertext to the powerful cloud server. Keyword search is also supported, in which data owners and users can generate the keywords index and search trapdoor, respectively, without relying on always online trusted authority. Furthermore, an outsourced decryption technology is used to reduce the computational load of decryption on user side. Our RSABE scheme is proven to be semantically secure against selective ciphertext policy and chosen plaintext attack, and to be secure against chosen keyword attack in the random oracle model. Finally, performance evaluation demonstrates that our scheme is highly efficient.

Outsourcing heavy storage and computation to the cloud servers now becomes more and more popular. How to secure share the cloud storage is an important problem for many mobile users. Proxy re-encryption is such a cryptographic primitive which can be used to secure share cloud data. Until now there are many kinds of proxy re-encryption schemes with various properties, such as conditional proxy re-encryption, proxy re-encryption with keyword search etc. However until now there exists no work focus on proxy re-encryption for mobile cloud storage sharing. In mobile cloud storage, almost all the users are mobile ones, they only have resource-restricted equipments. In this paper we try to initialize this research, we give a very basic outsourced online/offline proxy re-encryption scheme for mobile cloud storage sharing and leave many interesting open problems as the future work.

Efficient personalized search over encrypted data for mobile edge-assisted cloud storage

The number of networked “smart devices” available in everyday environments is rapidly increasing; however, most adopt mutually incompatible networks, protocols, and application programming interfaces. In previous work, we introduced a variety of adaptive middleware techniques that enables a user's commodity mobile device (e.g., a smartphone) to serve as an adaptive gateway between mutually incompatible devices — providing service adaptation and protocol translation services through plug-ins that can be installed on-the-fly. In this paper, we present a complementary set of novel smart space design tools, which enable non-programmers to visually “remix” their ambient environments in new, playful and potentially unforeseen ways using an intuitive flow-graph model. Visual designs can be sent over the network to the user's mobile device, which instantiates them during runtime. This paper presents a detailed overview of the approach, introduces our fully functional prototype, and presents a user study that provides encouraging first results.

Smart sensor-equipped mobile devices sense, collect, and process data generated by the edge network to achieve intelligent control, but such mobile devices usually have limited storage and computing resources. Mobile cloud storage provides a promising solution owing to its rich storage resources, great accessibility, and low cost. But it also brings a risk of information leakage. The encryption of sensitive data is the basic step to resist the risk. However, deploying a high complexity encryption and decryption algorithm on mobile devices will greatly increase the burden of terminal operation and the difficulty to implement the necessary privacy protection algorithm. In this paper, we propose ENSURE (EfficieNt and SecURE), an efficient and secure encrypted search architecture over mobile cloud storage. ENSURE is inspired by edge computing. It allows mobile devices to offload the computation intensive task onto the edge server to achieve a high efficiency. Besides, to protect data security, it reduces the information acquisition of untrusted cloud by hiding the relevance between query keyword and search results from the cloud. Experiments on a real data set show that ENSURE reduces the computation time by 15% to 49% and saves the energy consumption by 38% to 69% per query.

It is often challenging to access a pool of mobile device users and instruct them to perform an interactive task. Yet such data is often vital to provide design insight at various stages of the design process of a mobile application, service or system. We propose accessing a pool of mobile device users via the microtask market Amazon Mechanical Turk (MTurk). While mobile device users are still a minority on MTurk, they provide unique opportunities for requesters. Not only does catering to mobile device users expand the potential worker pool, but also offers access to realistic in situ mobile sensor data for a variety of pervasive computing applications. We present a design pattern that makes it easy to crowdsource tasks to mobile device users. We demonstrate this pattern to obtain sensor availability information for some of the most popular mobile device sensors, using HTML5 web APIs to access them. We find that there is a sizable pool of mobile workers and we present two design strategies for efficiently accessing them. The first enables direct fast access to a small pool of mobile-only device users. The second strategy exploits our finding that a large number of desktop-based crowd workers are prepared to switch to their mobile device if prompted by a well-designed mobile task. Finally we discuss solution principles for sensor-dependent mobile systems and studies that will be underpinned by mobile device crowd workers.

Nurses Need Training and Policies to Address Barriers to Use of Mobile Devices and Apps for Direct Patient Care in Hospital Settings

With the rapid growth of mobile applications, the user is increasingly confronted with a lot of information and tend to reject notifications sent by applications installed within his/her mobile device. This rejection affects the performance of many systems, especially proactive recommender systems. Therefore, it is no longer enough for a recommender system to determine what to recommend according to users' needs, but it also has to deal with the risk of disturbing the user during the recommendation process. We believe that the several embedded applications within the user's device along with other parameters could help understand and assess the user's interruptibility in some situations. In this paper, we address intrusiveness within a proactive recommendation approach that makes use of the user's context and the applications embedded within the user's mobile device in order to assess the intrusiveness level of a given situation before recommending.

High-frequency sound waves have a wide spectrum of application in multifarious fields making them an ideal choice for short distance data transmission. A trigger system based on audio beacon uses inaudible high-frequency sound waves to trigger an action on the target user's mobile device. The fundamental idea is to encode the information bits in the sound waves by varying the phase property of the carrier wave, for which phase shift keying is implemented. The beacon emits specific inaudible audio signals, which when received by the device results into some action on the target device. There is no such requirement of special hardware as the audio signals can be played on any traditional speaker set and received by most of the current mobile devices having a microphone. The accuracy of the system strongly relies on the proximity and the amount of noise interference between the beacon and user device. Few of the use cases for such systems include customer tracking inside a shopping mall i.e. in which shop the customer is and showcase of relevant ads based on how long the customer has been in there, approximate location tracking of the user within a premise, using the trigger system as a secondary authentication factor, invoking a certain function or a combination of functions on a mobile device by triggering audio signals.

The increasing use of mobile devices among health sciences students presents both opportunities and challenges to problem-based learning (PBL) in face-to-face tutorials and during self-directed learning. The purpose of the present study was to find out how common the use of mobile devices is among students in PBL, how they are used, and whether some general recommendations can be made to help students make more effective use of mobile devices during PBL. Based on the findings of focus interviews of students and facilitators (Chan et al., 2015), the authors developed a self-administered online questionnaire to examine students’ usage of mobile devices in PBL. The students from three healthcare professional programmes in a university in Hong Kong were invited to take part in the online survey. A total of 346 students (response rate of 31.89 %) completed the online questionnaire. It was found that almost all of them (99 %) own one or more mobile devices. Most of them (98 %) used their mobile devices in PBL, usually for educational purposes, such as the search and synthesis of information and the use of specific software on these devices, especially those for the visualization of knowledge (like atlases or software for creation of concept maps). There was a small percentage of students who never used mobile devices in PBL. The reasons included the facilitators’ explicit discouragement of their use, and the desire to focus on the discussion instead of searching for information. Based on the findings of the survey, the authors arrived at four recommendations aiming at more effective use of mobile devices in PBL: students should be free to choose to use mobile devices; mobile devices should be used for educational purposes only, such as the search for factual information or multimedia files; PBL tutorial time should mostly be spent on discussion, instead of searching for information; students should be encouraged to use cloud-based services for collaborative activities such as note-making and concept mapping in PBL.

Purpose – This paper aims to identify systematic ways of linking club members’ behavioral and demographic characteristics to their use of mobile devices in clubs. While the traditional private club experience is characterized by intensive personalization and face-to-face interactions, clubs are increasingly deploying information technology (IT) tools to optimize some of their internal processes and offer a better value proposition to their members. Design/methodology/approach – Based on data from 737 actual club members from the USA, this research used a series of logistic regressions to reveal the manner in which a series of behavioral and demographic variables can be used to predict the likelihood of use of mobile devices in clubs for specific club-related tasks. Findings – This research revealed that there are differences between the two main types of clubs (i.e. golf/country and city/athletic), as well as differences among club members residing in different regions of the USA in the manner in which members use mobile devices for club-related tasks. Research limitations/implications – This research offers a number of notable theoretical contributions. This research uses actual mobile device use data from actual club members in the USA. In addition, this research offers a comprehensive operationalization of the actual mobile use behaviors in clubs, and offers a methodological blueprint for predicting mobile device user behavior using easily collectable variables. Practical implications – This research provides specific suggestions to pinpoint the mobile technology deployment in clubs according to behavioral and demographic profile criteria. Social implications – This research could lead to feasible segmentation procedures and explicates the increasing role of mobile devices within the contemporary society. Originality/value – This research addresses a novel research topic in an industry characterized by a grave lack of research on IT.

“Security begins at home”: Determinants of home computer and mobile device security behavior

Nowadays, mobile users are not just content with a quick access to Internet when they are watching various types of videos, but also expecting a better video viewing experience. The reality is that decoding videos will consume very large resources of mobile devices. However, the resources of mobile devices are limited in terms of CPU, the main memory and so on, which impedes the performance enhancement. Fortunately, the emergence of mobile media cloud makes it possible to lighten decoding load on mobile devices. Cloud computing has an outstanding performance in rendering diverse services, strong computation ability, and great storage capacity in a relatively lower cost, which provides an effective channel out for the present dilemma. In this paper, we focus on the experimental study of video fusion method for multi-view video streaming under mobile media cloud environment. Firstly, we conduct a large quantity of collection experiments and find that decoding load of videos follows the power function model, which demonstrates that video fusion of multi-view videos at cloud side may effectively reduce the CPU usage of decoding at mobile side. Secondly, we further quantify the condition when the video fusion method can reduce the CPU usage of mobile devices along with its corresponding reduction rates.

Mobile cloud storage provides benefits for educational institutions. Several researchers have researched cloud computing adoption, but only a few studies related to how users experience using Personal Cloud Storage Services. This research aims to investigate the adoption of the mobile cloud storage factors following the theory, as well as research that has been previously proven related to user interest in using mobile cloud storage among higher education students. This quantitative research uses data analysis techniques using GSCA to prove the theory and achieve the research goals. The research methodology consists of five main stages, namely the stage of model development and research design, the stage of preparing the instrument and its measurement, the stage of testing the instrument, the stage of survey and results, as well as the stages of analysis and discussion as well as conclusions. Five variables are investigated in this research: knowledge sharing, perceived usefulness, attitude toward using a system, trust, and intention to use. The results of hypothesis testing were conducted using GSCA; three proposed hypotheses were accepted, and one was rejected. The variables the research model can explain are 68%, and the remaining 32% are other variables not used in this study. The characteristics of respondents can provide several ways to increase the adoption of mobile cloud computing by linking research results from inferential analysis and descriptive analysis. Future research can focus on extracting these variables through user interviews regarding students' intentions to use mobile cloud computing.

BackgroundHealth care provider usage of mobile devices is increasing globally; however, there is little understanding of patient perceptions on this behavior in a health care setting.ObjectiveThe aim of this study was to assess patients’ attitudes toward mobile device usage by health care providers in the emergency department and to identify predictors of these attitudes.MethodsThe study was carried out at the emergency department of a large academic tertiary care medical center in Lebanon. A cross-sectional survey design was adopted by administering a questionnaire to medically stable adult patients who presented to the emergency department with an emergency severity index of 3, 4, or 5 between January 2017 and March 2018. The questionnaire collected relevant patient demographic information and included questions related to their mobile device usage along with those evaluating attitudes for the use of mobile devices by health care providers with respect to six major domains: role in health care, distraction potential, impact on communication, empathy, privacy, and professionalism. The attitude toward mobile device usage by health care providers in the emergency department was the main outcome variable. A stepwise logistic regression model was used to assess the association between the outcome variable and the demographic and attitude-related independent variables.ResultsAmong the 438 eligible patients, 338 patients responded to the questionnaire for a response rate of 70.0%. Overall, 313/338 (92.6%) respondents agreed that mobile devices improve health care delivery, whereas 132/338 (39.1%) respondents were opposed to their usage by health care providers in the emergency department (95% CI: 34.0-44.4). The majority (240/338, 71.0%) of patients agreed that mobile devices are a source of distraction to health care providers in the workplace. Females (odds ratio [OR]=1.67, 95% CI: 1.00-2.78) as well as all patients (OR=2.54, 95% CI 1.36-4.76) who believed that mobile devices were a source of distraction, reflecting a lack of professionalism (OR=2.77, 95% CI 1.59-4.82) and impacting the provider’s ability to relate to the patient (OR=2.93, 95% CI 1.72-4.99), were more likely to agree that mobile devices should not be used in the emergency department.ConclusionsPatients’ negative attitude toward mobile device use in the emergency department is largely driven by patient gender (females), patient perception of the distraction potential of the devices, and their negative impact on the health care provider’s empathy and professionalism. The findings of this study shed light on the importance of encouraging stakeholders to impose a digital professionalism code of conduct for providers working in acute health care settings.