Showing papers on "Smart device published in 2018"

Healthcare Blockchain System Using Smart Contracts for Secure Automated Remote Patient Monitoring

Abstract: As Internet of Things (IoT) devices and other remote patient monitoring systems increase in popularity, security concerns about the transfer and logging of data transactions arise. In order to handle the protected health information (PHI) generated by these devices, we propose utilizing blockchain-based smart contracts to facilitate secure analysis and management of medical sensors. Using a private blockchain based on the Ethereum protocol, we created a system where the sensors communicate with a smart device that calls smart contracts and writes records of all events on the blockchain. This smart contract system would support real-time patient monitoring and medical interventions by sending notifications to patients and medical professionals, while also maintaining a secure record of who has initiated these activities. This would resolve many security vulnerabilities associated with remote patient monitoring and automate the delivery of notifications to all involved parties in a HIPAA compliant manner.

Searching for the IoT Resources: Fundamentals, Requirements, Comprehensive Review, and Future Directions

Abstract: Internet of Things (IoT) paradigm links physical objects in the real world to cyber world and enables the creation of smart environments and applications. A physical object is the fundamental building block of the IoT, known as a Smart Device , that can monitor the environment. These devices can communicate with each other and have data processing abilities. When deployed, smart devices collect real-time data and publish the gathered data on the Web. The functionality of smart devices can be abstracted as a service and an IoT application can be built by combining the smart devices with these services that help to address challenges of day-to-day activities. The IoT comprises billions of these intelligent communicating devices that generate enormous amount of data, and hence performing analysis on this data is a significant task. Using search techniques, the size and extent of data can be reduced and limited, so that an application can choose just the most important and valuable data items as per its necessities. It is, however, a tedious task to effectively seek and select a proper device and/or its data among a large number of available devices for a specific application. Search techniques are fundamental to IoT and poses various challenges like a large number of devices, dynamic availability, restrictions on resource utilization, real time data in various types and formats, past and historical monitoring. In the recent past, various methods and techniques have been developed by the research community to address these issues. In this paper, we present a review of the state-of-the-art search methods for the IoT, classifying them according to their design principle and search approaches as: IoT data and IoT object-based techniques. Under each classification, we describe the method adopted, their advantages and disadvantages. Finally, we identify and discuss key challenges and future research directions that will allow the next generation search techniques to recognize and respond to user queries and satisfy the information needs of users.

Optimized Big Data Management across Multi-Cloud Data Centers: Software-Defined-Network-Based Analysis

Abstract: With an exponential increase in smart device users, there is an increase in the bulk amount of data generation from various smart devices, which varies with respect to all the essential V's used to categorize it as big data. Generally, most service providers, including Google, Amazon, Microsoft and so on, have deployed a large number of geographically distributed data centers to process this huge amount of data generated from various smart devices so that users can get quick response time. For this purpose, Hadoop, and SPARK are widely used by these service providers for processing large datasets. However, less emphasis has been given on the underlying infrastructure (the network through which data flows), which is one of the most important components for successful implementation of any designed solution in this environment. In the worst case, due to heavy network traffic with respect to data migrations across different data centers, the underlying network infrastructure may not be able to transfer data packets from source to destination, resulting in performance degradation. Focusing on all these issues, in this article, we propose a novel SDN-based big data management approach with respect to the optimized network resource consumption such as network bandwidth and data storage units. We analyze various components at both the data and control planes that can enhance the optimized big data analytics across multiple cloud data centers. For example, we analyze the performance of the proposed solution using Bloom-filter-based insertion and deletion of an element in the flow table maintained at the OpenFlow controller, which makes most of the decisions for network traffic classification using the rule-and-action-based mechanism. Using the proposed solution, developers can deploy and analyze real-time traffic behavior for the future big data applications in MCE.

A Smart System for Sleep Monitoring by Integrating IoT With Big Data Analytics

Abstract: Obtrusive sleep apnea (OSA) is one of the most important sleep disorders because it has a direct adverse impact on the quality of life. Intellectual deterioration, decreased psychomotor performance, behavior, and personality disorders are some of the consequences of OSA. Therefore, a real-time monitoring of this disorder is a critical need in healthcare solutions. There are several systems for OSA detection. Nevertheless, despite their promising results, these systems not guiding their treatment. For these reasons, this research presents an innovative system for both to detect and support of treatment of OSA of elderly people by monitoring multiple factors such as sleep environment, sleep status, physical activities, and physiological parameters as well as the use of open data available in smart cities. Our system architecture performs two types of processing. On the one hand, a pre-processing based on rules that enables the sending of real-time notifications to responsible for the care of elderly, in the event of an emergency situation. This pre-processing is essentially based on a fog computing approach implemented in a smart device operating at the edge of the network that additionally offers advanced interoperability services: technical, syntactic, and semantic. On the other hand, a batch data processing that enables a descriptive analysis that statistically details the behavior of the data and a predictive analysis for the development of services, such as predicting the least polluted place to perform outdoor activities. This processing uses big data tools on cloud computing. The performed experiments show a 93.3% of effectivity in the air quality index prediction to guide the OSA treatment. The system’s performance has been evaluated in terms of latency. The achieved results clearly demonstrate that the pre-processing of data at the edge of the network improves the efficiency of the system.

What is a smart device? - a conceptualisation within the paradigm of the internet of things

Abstract: The Internet of Things (IoT) is an interconnected network of objects which range from simple sensors to smartphones and tablets; it is a relatively novel paradigm that has been rapidly gaining ground in the scenario of modern wireless telecommunications with an expected growth of 25 to 50 billion of connected devices for 2020 Due to the recent rise of this paradigm, authors across the literature use inconsistent terms to address the devices present in the IoT, such as mobile device, smart device, mobile technologies or mobile smart device. Based on the existing literature, this paper chooses the term smart device as a starting point towards the development of an appropriate definition for the devices present in the IoT. This investigation aims at exploring the concept and main features of smart devices as well as their role in the IoT. This paper follows a systematic approach for reviewing compendium of literature to explore the current research in this field. It has been identified smart devices as the primary objects interconnected in the network of IoT, having an essential role in this paradigm. The developed concept for defining smart device is based on three main features, namely context-awareness, autonomy and device connectivity. Other features such as mobility and user-interaction were highly mentioned in the literature, but were not considered because of the nature of the IoT as a network mainly oriented to device-to-device connectivity whether they are mobile or not and whether they interact with people or not. What emerges from this paper is a concept which can be used to homogenise the terminology used on further research in the Field of digitalisation and smart technologies.

Electronic Media Exposure and Use among Toddlers

Abstract: Objective These days, young children are exposed to a wide range of smart devices and their usage of smart devices is rapidly increasing worldwide. However, the use of smart devices by young children has not been studied in detail yet because smart device is relatively recent. The purpose of this study was to investigate the exposure status of smart devices among 2-5 years old children in Korea. Methods Four hundred parents of 2- to 5-year-old children were invited to enroll. Data on demographic information and the frequency of media use, time of media use, age at first use of media was self-reported. Results Among 390 toddlers, 39.3% watched TV almost every day, while 12.0% of children used smartphone on a daily basis. During weekdays, 48% of the children watched TV for over an hour. On weekends, 63.1% of the children watched TV for over an hour. On weekends, 23.4% of children use their smartphones for over an hour. Children using smartphones before 24 months of age were 31.3%. Conclusion Research has shown that TV and smartphones are the most popular digital devices used by toddlers. Most toddlers began using smart devices at 12-24 months. This study provides comprehensive information on children's contemporary use of media.

Understanding Travelers’ Behavior for Sustainable Smart Tourism: A Technology Readiness Perspective

Abstract: Smart tourism has contributed to making people’s travels easier and more enjoyable, but sometimes has a negative impact on their travel experience. The challenges travelers face while using smart devices have not been researched in detail and are relatively unknown. While most studies have considered the usefulness of smart devices in tourism, negative perceptions of smart tourism have rarely been discussed. Thus, this study investigates travelers’ risk perceptions of smart tourism from a technology readiness perspective. It examines the impact of optimism, innovativeness, insecurity, and discomfort on travelers’ usage intentions of smart devices through their perceived risks and benefits. To test the proposed model and corresponding hypotheses, a partial least squares analysis was performed on data collected from 250 survey respondents. The results showed that the perceived benefits of smart devices had a significant effect on usage intentions of smart devices while traveling. It was also confirmed that the influence of perceived risks depends on the characteristics of travelers. This study is significant as it is the first empirical study applying the TRI (Technology Readiness Index) model that examines the negative effects of smart devices on tourists during travel. The results of this study provide meaningful insights into smart tourism to companies and governments.

An approach to secure smart homes in cyber-physical systems/Internet-of-Things

Abstract: Home automation plays an important role in our daily life to control home appliances from a single touch or click. In this case, users are able to check home appliances from laptops, iPhone, iPod or other smart phone devices which supports to swap household appliances. Sensors are one of the mode important parts for smart home technology. Smart homes also help elderly people; they can handle the home with simplicity from their remote or smart device which is linked up to central device that is connected to home automation. Security is the main concern while maintains the smart homes, nowadays hackers don't need to travel to targeted homes, they can approach virtually to attack smart homes easily. In this paper, we propose a secure architecture for smart homes. We added a sicher firewall system between a central hub (LAN) that are linked to the cyberspace and other end that is connected to home appliances. In this way security threats become dejected and attackers are unable to reach home automation systems. A sicher firewall also protects system from internet threats. It generates a warning and protect system from external threats. Applying a sicher firewall, it enforces security system and increase security and concealment to smart homes. This experience will enhance user trustworthiness for using smart homes technology.

T2FA: Transparent Two-Factor Authentication

Abstract: Traditional username and password-based single-factor authentication is easy to deploy but vulnerable to dictionary attacks, snooping, and brute force attacks. Two-factor authentication (2FA) has been proposed to improve the security, where smart devices are used as the second authentication factor. However, the interaction between human and the smart device is required, which is inconvenient to users. In addition, an attacker is able to get the second authentication factor through fraud, thus invalidating current 2FA mechanisms. In order to solve these problems, we propose a transparent two-factor authentication (T2FA) based on physical unclonable function (PUF) and voiceprint. The second authentication authenticates the user’s mobile phone through the PUF. The third one is to determine whether the login terminal and the user’s mobile phone are in the same environment with the environment voiceprint. The second and third authentication in the second factor is completely transparent to users. Therefore, T2FA avoids the tedious interaction and provides the same high user experience satisfaction as the single-factor authentication and exhibits high security simultaneously. Moreover, the fraud is eliminated technically due to the transparency of the authentication.

Energy monitoring and control using Internet of Things (IoT) system

Abstract: The use of technology has become an essential part of improving lifestyle, work efficiency, and a catalyst for economic growth. The benefit of the Internet of Things (IoT) and connected nodes has been on a steep incline in recent years. This paper aims to research, build, test and implement a low-cost energy monitoring and control system using IoT devices. Electrical appliances (e.g., air conditioning units and overhead lighting) can be controlled and monitored using IoT technology from any place in the world. In order to accomplish this goal, a complete front-end to back-end system that includes a smart device application (iOS platform), a cloud-based database, an Application Programming Interface (API), and a hardware development is proposed. A small programmable specialized computing device (e.g., Raspberry Pi) for preliminary testing. This smart node was chosen due to familiarity, and its capabilities, such as general purpose pins and built-in Wi-Fi chip. The end goal is to observe energy efficiency by monitoring and controlling air conditioning appliances and standard overhead lighting units. These smart IoT devices allow for the usage energy data from each unit to be collected and stored in a Cloud-based database that can be analyzed and reported for energy conservation and analysis.

Intelligent and Energy Efficient Mobile Smartphone Gateway for Healthcare Smart Devices Based on 5G

Abstract: The healthcare sector is now blending with Information and Communications Technology (ICT) using Internet of Things (IoT) to potentially minimise medical errors and reduce healthcare cost. Patients are now embedded with smart devices like body sensors and wearable devices which can monitor their health without the need for a doctor in physical contact. Such smart devices have the downside of low battery power and are unable to transmit their data to the medical personnel when the patient is on the move away from the smart home/smart clinic fixed gateway. A mobile gateway is required which moves with the patient to process the smart device data without depleting the smartphone battery. This paper proposes an Intelligent and Energy Efficient SG based smartphone Gateway for healthcare smart devices (IEE5GG). In IEE5GG, the 5G architecture is adopted and the patient's smartphone is used as a gateway where multiple smart devices are connected e.g. via Bluetooth. To save energy, requests to the smartphone can either be executed on the smartphone gateway or offloaded and executed in the Mobile Edge Computing (MEC) cloud at close proximity to the smartphone in the 5G Base Station (BS) central Unit (gNB-CU) while considering the transmission power, Quality of Service (QoS), smartphone battery level and Central Processing Unit (CPU) load. Results show that the proposed IEE5GG framework saves up to 38% of energy in the healthcare mobile gateway smartphone and reduces healthcare application service time by up to 41%.

The Role of Cloud-MANET Framework in the Internet of Things (IoT)

Abstract: In the next generation of computing, Mobile ad-hoc network (MANET) will play a very important role in the Internet of Things (IoT). The MANET is a kind of wireless networks that are self-organizing and auto connected in a decentralized system. Every device in MANET can be moved freely from one location to another in any direction. They can create a network with their neighbors’ smart devices and forward data to another device. The IoT-Cloud-MANET framework of smart devices is composed of IoT, cloud computing, and MANET. This framework can access and deliver cloud services to the MANET users through their smart devices in the IoT framework where all computations, data handling, and resource management are performed. The smart devices can move from one location to another within the range of the MANET network. Various MANETs can connect to the same cloud, they can use cloud service in a real time. For connecting the smart device of MANET to cloud needs integration with mobile apps. My main contribution in this research links a new methodology for providing secure communication on the internet of smart devices using MANET Concept in 5G. The research methodology uses the correct and efficient simulation of the desired study and can be implemented in a framework of the Internet of Things in 5G.

A Semantic Theory of the Internet of Things

Abstract: We propose a process calculus for modelling and reasoning on systems in the Internet of Things paradigm. Our systems interact both with the physical environment, via sensors and actuators, and with smart devices, via short-range and Internet channels. The calculus is equipped with a standard notion of labelled bisimilarity which represents a fully abstract characterisation of a well-known contextual equivalence. We use our semantic proof-methods to prove run-time properties of a non-trivial case study as well as system equalities.

Authenticating On-Body Backscatter by Exploiting Propagation Signatures

Abstract: The vision of battery-free communication has made backscatter a compelling technology for on-body wearable and implantable devices. Recent advances have facilitated the communication between backscatter tags and on-body smart devices. These studies have focused on the communication dimension, while the security dimension remains vulnerable. It has been demonstrated that wireless connectivity can be exploited to send unauthorized commands or fake messages that result in device malfunctioning. The key challenge in defending these attacks stems from the minimalist design in backscatter. Thus, in this paper, we explore the feasibility of authenticating an on-body backscatter tag without modifying its signal or protocol. We present SecureScatter, a physical-layer solution that delegates the security of backscatter to an on-body smart device. To this end, we profile the on-body propagation paths of backscatter links, and construct highly sensitive propagation signatures to identify on-body backscatter links. We implement our design in a software radio and evaluate it with different backscatter tags that work at 2.4 GHz and 900 MHz. Results show that our system can identify on-body devices at 93.23% average true positive rate and 3.18% average false positive rate.

The Personal Stun-A Smart Device For Women's Safety

Abstract: Women security is need of the hour now-a-days. In India, there are many cases of women harassment and molestation. Safety of women matters let be whether at home, outdoor or it be their work place. The literature surveyed shows that there are many mobile applications that are used for women safety purpose. One recent research study shows that there is a footwear chip which is sticked to the footwear that gets activated when the person taps one leg behind the other 4 times. We focus on developing a prototype that is a smart band which gets activated by tapping on the screen twice. Once the device is activated it starts sending the GPS location to the ICE contacts and police control rooms. There is a pulse rate sensor embedded in the device that senses the pulse rate of the person and a temperature senor that senses body temperature of the person. The band when thrown with force the force sensor will get activated and sends the current location of the victim. A Piezo buzzer siren will get activated after 1–2 mins of the actual device getting turned on. The range of the buzzer is of 80–110 dB which can be heard from a distance of 50 feet long. An electric shock circuit is designed that emits electric current. On the top of the band screen there are two metal points that generates the shock when the two metal points come in contact with any surface or anybody. The device supports a micro usb charging. A smart application will be developed on the android platform which is connected with the device via bluetooth interface that shows the sensed data of the subject to the ICE contacts. Until the device is turned off it will send the location on the interval of 5 mins and will keep on beeping continuously.

Exploiting Small World Problems in a SIoT Environment

Abstract: Internet of Things (IoT) has been at the center of attention among researchers for the last two decades. Their aim was to convert each real-world object into a virtual object. Recently, a new idea of integrating the Social Networking concept into the Internet of Things has merged and is gaining popularity and attention in the research society due to its vast and flexible nature. It comprises of the potential to provide a platform for innovative applications and network services with efficient and effective manners. In this paper, we provide the sustenance for the Social Internet of Things (SIoT) paradigm to jump to the next level. Currently, the SIoT technique has been proven to be efficient, but heterogeneous smart devices are growing exponentially. This can develop a problematic scenario while searching for the right objects or services from billions of devices. Small world phenomena have revealed some interesting facts and motivated many researchers to find the hidden links between acquaintances in order to reach someone across the world. The contribution of this research is to integrate the SIoT paradigm with the small world concept. By integrating the small world properties in SIoT smart devices, we empower the Smart Social Agent (SSA). The Smart Social Agent ensures the finding of appropriate friends (i.e., the IoT devices used by our friend circle) and services that are required by the user, without human intervention. The Smart Social Agent can be any smart device in SIoTs, e.g., mobile phones.

HomePad: A Privacy-Aware Smart Hub for Home Environments

Abstract: The adoption of smart home devices is hindered today by the privacy concerns users have regarding their personal data. Since these devices depend on remote service providers, users remain oblivious about how and when their data is disclosed and processed. In this paper we present HomePad, a privacy-aware smart hub for home environments. Our system aims to empower users with the ability to determine how applications can access and process sensitive data collected by smart devices (e.g., web cams) and to prevent applications from executing unless they abide by the privacy restrictions specified by the users. To achieve this goal, HomePad applications are implemented as directed graphs of elements, which consist of instances of functions that process data in isolation. By modeling elements and the flow graph using Prolog rules, HomePad allows for automatic verification of the application's flow graph against user-defined privacy policies. Homepad incurs a negligible performance overhead, requires a modest programming effort, and provides flexible policy support to address the privacy concerns most commonly expressed by potential smart device consumers.

Radiobeacon data sharing by forwarding low energy transmissions to a cloud host

Abstract: Remote actuation of machines or machine systems is realized by a system for coupling a radiobeacon to a smart device and in turn to a broader network. The smart device is configured as a proximity-actuated “community nodal device” by an application that operates as part of the system. The community nodal device is given instructions to function as a “soft switch”: to automatically “upswitch”, amplify, and broadcast low energy, local area radiobeacon “messages” to a cloud-based server, where the message is interpreted according to rules or policies established by an operator, and a command is transmitted for execution to a remote device. Conventional smart devices generally discard data not addressed to the owner of the smart device. Instead of discarding third party messages, the system preempts their handling, and using a soft switch formed from background resources, anonymously, without access to the message by a user interface of the proxy device, and without waiting for a network query from the host, engineers an “upswitched transmission” of radiobeacon-generated data to a cloud host. Advantageously, confidential sharing of ad hoc community resources results in a negligible load on background resources of the community nodal device. Messages may include a sensor data payload. Bit overloading enables a sensor data payload to be compressed into a few hundred bytes or less.

Building vital conditions monitoring

Abstract: Apparatus and methods for ongoing assessment of a condition of a building structure combined with determination of a direction of a particular condition assessed by a digital sensor proximate to the structure. A user or other agent supporting a smart device is made aware of a condition and directed towards a site of the condition. Conditions may also be remotely monitored and an appropriate response technician deployed to address conditions monitored with directional input to the condition within the structure.

Blockchain-Based Secure Equipment Diagnosis Mechanism of Smart Grid

Abstract: The smart terminal and grid protection devices play a very important role in the safe operation of the smart grid. Traditional maintenance and renewal of the center node wastes a lot of manpower and material resources and have huge safety implications. This paper proposes a safety equipment diagnosis mechanism based on consortium blockchain technology to realize more efficient, convenient, and secure device maintenance. When a device has problems or notices improper operation, it can make a device diagnosis request in the consortium blockchain network, and receive a diagnosis response from a vendor or non-original supplier nodes. This scheme designs a decentralized safety equipment diagnosis smart contract, combining response node bid price and credit, and applies a multi-dimensional reverse auction mechanism to determine bid node and transaction price. After a smart device diagnosed, the relevant message will be packaged and sent to a smartphone, which can use the client to set up the smart contract of equipment operation policy. Paillier encryption arithmetic can be used to ensure device diagnosis mechanism safety. The proposed scheme is guaranteed not to reveal sensitive information in the process of device interaction.

Security Analysis of Smartphone and Cloud Computing Authentication Frameworks and Protocols

Abstract: We live in a digital world where every detail of our information is being transferred from one smart device to another via cross-platform, third-party cloud services. Smart technologies, such as, smartphones are playing dynamic roles in order to successfully complete our daily routines and official tasks that require access to all types of critical data. Before the advent of these smart technologies, securing critical information was quite a challenge. However, after the advent and global adoption of such technologies, information security has become one of the primary and most fundamental task for security professionals. The integration of social media has made this task even more challenging to undertake successfully. To this day, there are plentiful studies in which numerous authentication and security techniques were proposed and developed for smartphone and cloud computing technologies. These studies have successfully addressed multiple authentication threats and other related issues in existing the smartphone and cloud computing technologies. However, to the best of our understanding and knowledge, these studies lack many aspects in terms of authentication attacks, logical authentication analysis, and the absence of authentication implementation scenarios. Due to these authentication anomalies and ambiguities, such studies cannot be fully considered for successful implementation. Therefore, in this paper, we have performed a comprehensive security analysis and review of various smartphone and cloud computing authentication frameworks and protocols to outline up-to-date authentication threats and issues in the literature. These authentication challenges are further summarized and presented in the form of different graphs to illustrate where the research is currently heading. Finally, based on those outcomes, we identify the latest and existing authentication uncertainties, threats, and other related issues to address future directions and open research issues in the domain of the smartphone-and cloud-computing authentication.

Enabling the Automatic Generation of User Interfaces for Remote Laboratories

Abstract: Remote laboratories are an important component of blended and distance science and engineering education. By definition, they provide access to a physical lab in a distant location. Many architectures enabling remote laboratory systems exist, the most common of which are Client-Server based. In this context, the Server interfaces the physical setup and makes it software-accessible. The Smart Device Specifications revisit a Client-Server architecture, with the main aim of cancelling the dependencies which inherently exist between a Client and a Server. This is done by describing the Server as a set of services, which are exposed as well-defined APIs. If a remote laboratory is built following the Smart Device Specifications, any person with programming skills can create a personalized client application to access the lab. But in practice, teachers rely on the mediated contact with a lab provider to have information about what kind of experiment(s) the lab in question implements. Even though there is a complete description of the available sensors and actuators making up a lab and how to be accessed, it is not clear how they are connected (relationships). In this sense, a list of sensors and actuators are not enough to make a guided selection of components to create the interface to an experiment. Therefore, the aim of this work is to support teachers in choosing the experiments and creating the respective UI on their own, in a pedagogically oriented scenario and by taking into consideration the target online learning environment. This is done by revisiting the Smart Device Specifications and extending them, in addition to proposing a tool that will automatically generate the user interface of the chosen experiment(s).

Preference Elicitation with Interdependency and User Bother Cost

Abstract: Agent-based scheduling systems, such as automated systems that schedule meetings for users and systems that schedule smart devices in smart homes, require the elicitation of user preferences in oder to operate in a manner that is consistent with user expectations. Unfortunately, interactions between such systems and users can be limited as human users prefer to not be overly bothered by such systems. As such, a key challenge is for the system to efficiently elicit key preferences without bothering the users too much. To tackle this problem, we propose a cost model that captures the cognitive or bother cost associated with asking a question. We incorporate this model into our iPLEASE system, an interactive preference elicitation approach. iPLEASE represents a user's preferences as a matrix, called preference matrix, and uses heuristics to select, from a given set of questions, an efficient sequence of questions to ask the user such that the total bother cost incurred to the user does not exceed a given bother cost budget. The user's response to those questions will partially populate the preference matrix. It then performs an exact matrix completion via convex optimization to approximate the remaining preferences that are not directly elicited. We empirically apply iPLEASE on randomly-generated problems as well as on a real-world dataset for the smart device scheduling problem to demonstrate that our approach outperforms other non-trivial benchmarks in eliciting user preferences.

Kid on The Phone! Toward Automatic Detection of Children on Mobile Devices

Abstract: Studies have shown that children can be exposed to smart devices at a very early age. This has important implications on research in children-computer interaction, children online safety and early education. Many systems have been built based on such research. In this work, we present multiple techniques to automatically detect the presence of a child on a smart device, which could be used as the first step on such systems. Our methods distinguish children from adults based on behavioral differences while operating a touch-enabled modern computing device. Behavioral differences are extracted from data recorded by the touchscreen and built-in sensors. To evaluate the effectiveness of the proposed methods, a new data set has been created from 50 children and adults who interacted with off-the-shelf applications on smart phones. Results show that it is possible to achieve 99% accuracy and less than 0.5% error rate after 8 consecutive touch gestures using only touch information or 5 seconds of sensor reading. If information is used from multiple sensors, then only after 3 gestures, similar performance could be achieved.

Towards Intelligent Edge Storage Management: Determining and Predicting Mobile File Popularity

Abstract: The exponential growth in smart device usage and mobile applications markets, coupled with the increased complexity of these applications has outpaced the storage typically available on these devices. As a result, developers and end-users have both started pursuing cloud solutions for the storage and caching of application data, as well as personal user data. Such solutions, however, require a great deal of manual intervention from the user to first determine which files need to be offloaded, and then perform the actual task of offloading them. Given the time, attention, and effort required for such manual tasks, there is a need for automated storage management systems that make these decisions in an intelligent manner. In this paper, we analyze the access traces of 28 different mobile device users, and show that there are discernible access patterns to both popular and unpopular files on a user's device. We leverage this knowledge of access patterns to develop our Pattern Based Popularity Assessor (PBPA) algorithm. Our evaluation shows that PBPA can predict file popularity with high accuracy, making it a promising candidate for future automated mobile storage offloading systems.

TwistIn: Tangible Authentication of Smart Devices via Motion Co-analysis with a Smartwatch

Abstract: Smart devices contain sensitive information that has to be guarded against unauthorized access through authentication. Existing authentication methods become obsolete as they are designed either for logging-in one device at a time or are ineffective in a multi-user multi-device environment. This paper presents TwistIn, a simple gesture that takes a smartwatch as an authentication token for fast access and control of other smart devices. Our mechanism is particularly useful for devices such as smartphones, smart glasses, and small IoT objects. To log in a device, one simply need to pick it up and twist it a few times. Then, by co-analyzing the motion data from the device and the watch, our method can extend the user authentication on the watch to the device. This is a simple and tangible interaction that takes only one to two seconds to perform. Furthermore, to account for user variation in wrist bending, we decompose wrist and forearm rotations via an optimization to improve the method accuracy. We implemented TwistIn, collected thousands of gesture samples, and conducted various experiments to evaluate our prototype system and show that it achieved over 95% detection accuracy.