Empirical Overview of Benchmark Datasets for Geomagnetic Field-Based Indoor Positioning

Indoor positioning and localization have been regarded as some of the most widely researched areas during the last decade. The wide proliferation of smartphones and the availability of fast-speed internet have initiated several location-based services. Concerning the importance of precise location information, many sensors are embedded into modern smartphones. Besides Wi-Fi positioning, a rich variety of technologies have been introduced or adopted for indoor positioning such as ultrawideband, infrared, radio frequency identification, Bluetooth beacons, pedestrian dead reckoning, and magnetic field, etc. However, special emphasis is put on infrastructureless approaches like Wi-Fi and magnetic field-based positioning, as they do not require additional infrastructure. Magnetic field positioning is an attractive solution for indoors; yet lack of public benchmarks and selection of suitable benchmarks are among the big challenges. While several benchmarks have been introduced over time, the selection criteria of a benchmark are not properly defined, which leads to positioning results that lack generalization. This study aims at analyzing various public benchmarks for magnetic field positioning and highlights their pros and cons for evaluation positioning algorithms. The concept of DUST (device, user, space, time) and DOWTS (dynamicity, orientation, walk, trajectory, and sensor fusion) is introduced which divides the characteristics of the magnetic field dataset into basic and advanced groups and discusses the publicly available datasets accordingly.

Interference-aware Coordinated Access Control for Heterogeneous Cellular D2D Communication Networks

Device-to-Device (D2D) communications is expected to be a key technology of the forthcoming mobile communication networks because of its benefits in terms of spectral efficiency, energy efficiency, and system capacity. To mitigate frequency collisions as well as reduce the effects of co-channel interference between user's connections, we propose an interference-aware coordinated access control (IaCAC) mechanism for heterogeneous cellular D2D communication networks with dense device deployment of user equipment (UEs). In the proposed network setting, we consider the co-existence of both macro base stations (MBSs) and smallcell base stations (SBSs). In the proposed IaCAC mechanism, MBSs and SBSs are coordinated to perform access control to their UEs while MBSs allocate bandwidth parts dynamically to SBSs based on the interference levels measured at SBSs. Besides, to reduce D2D-to-cellular interference, device user equipments (DUEs) can perform power control autonomously. Simulation results show that the proposed IaCAC can provide higher system throughput and user throughput than those achieved by the network-assisted device-decided scheme proposed in [21]. Moreover, simulation results also reveal that the proposed IaCAC also significantly improve SINR of MUE’s and SUE’s uplink connections.

Dc Motor Control System Through Android Application Using Arduino Nano

The study aims for the development of a control system for D.C motors through an application made for Android mobile devices. The D.C motors are represented by a robot model car and the control application communicates with the system via Bluetooth technology. The Android mobile device user must install an application on his mobile device, then, the user must turn on the Bluetooth communication on the mobile device. The user can use various commands to control the robot model car such as front, back, stop, left, right. These commands are sent from the Android mobile device to the Bluetooth receiver, which is interfaced with the control system. The control system has a Bluetooth HC-06 receiver that receives commands from the control application and sends them to the Arduino Nano microcontroller to control the motors through two L298N drivers.

Game Theory based Cyber-Insurance to Cover Potential Loss from Mobile Malware Exploitation

Potential for huge loss from malicious exploitation of software calls for development of principles of cyber-insurance. Estimating what to insure and for how much and what might be the premiums poses challenges because of the uncertainties, such as the timings of emergence and lethality of malicious apps, human propensity to favor ease by giving more privilege to downloaded apps over inconvenience of delay or functionality, the chance of infection determined by the lifestyle of the mobile device user, and the monetary value of the compromise of software, and so on. We provide a theoretical framework for cyber-insurance backed by game-theoretic formulation to calculate monetary value of risk and the insurance premiums associated with software compromise. By establishing the conditions for Nash equilibrium between strategies of an adversary and software we derive probabilities for risk, potential loss, gain to adversary from app categories, such as lifestyles, entertainment, education, and so on, and their prevalence ratios. Using simulations over a range of possibilities, and using publicly available malware statistics, we provide insights about the strategies that can be taken by the software and the adversary. We show the application of our framework on the most recent mobile malware data (2018 ISTR report—data for the year 2017) that consists of the top five Android malware apps: Malapp, Fakeinst, Premiumtext, Maldownloader , and Simplelocker and the resulting leaked phone number, location information, and installed app information. Uniqueness of our work stems from developing mathematical framework and providing insights of estimating cyber-insurance parameters through game-theoretic choice of strategies and by showing its efficacy on a recent real malicious app data . These insights will be of tremendous help to researchers and practitioners in the security community.

Effects on Children’s Health by Excessive Use of Online Devices: A Study from the Parents Perspectives

This paper aims to identify the patterns of excessive use of online devices by children and its physical and behavioural impact on children's health of five different age groups: 0- less than 3, 3-7, 7-10, 10- 13 and over 13years of age. A survey was conducted with 42 respondents by using an on-line Google form in Pokhara. The purposive sampling method was used to select the sample and an online questionnaire was used to accumulate data from the parents. The target sample groups are parents who have children with age below 14 years. It is not a surprising matter that children have become good operators of any online devices these days. Therefore, this research paper attempts to find out any relationships that exist between online device user children and physical problems that they suffer. So a hypothesis has been developed to test whether “excessive online devices uses affects children’s health?” A hypothesis was tested through Kendall's tau-b (τb) correlation coefficient, a non-parametric test. This paper concludes that the time is managed by the parent to their children for the use of the internet. Due to this effort of the parents, there is no serious physical health problem arising in the children and the parents are also not worried about their excessive engagement on electronic gadgets.

A egis +

The introduction of modern Smart Home Systems (SHSs) is redefining the way we perform everyday activities. Today, myriad SHS applications and the devices they control are widely available to users. Specifically, users can easily download and install the apps from vendor-specific app markets, or develop their own, to effectively implement their SHS solutions. However, despite their benefits, app-based SHSs unfold diverse security risks. Several attacks have already been reported to SHSs and current security solutions only consider smart home devices and apps individually to detect malicious actions, rather than the context of the SHS as a whole. Thus, the current security solutions applied to SHSs cannot capture user activities and sensor-device-user interactions in a holistic fashion. To address these limitations, in this article, we introduce A egis +, a novel context-aware platform-independent security framework to detect malicious behavior in an SHS. Specifically, A egis + observes the states of the connected smart home entities (sensors and devices) for different user activities and usage patterns in an SHS and builds a contextual model to differentiate between malicious and benign behavior. We evaluated the efficacy and performance of A egis + in multiple smart home settings (i.e., single bedroom, double bedroom, duplex) and platforms (i.e., Samsung SmartThings, Amazon Alexa) where real users perform day-to-day activities using real SHS devices. We also measured the performance of A egis + against five different malicious behaviors. Our detailed evaluation shows that A egis + can detect malicious behavior in SHS with high accuracy (over 95%) and secure the SHS regardless of the smart home layout and platforms, device configurations, installed apps, controller devices, and enforced user policies. Finally, A egis + yields minimum overhead to the SHS, ensuring effective deployability in real-life smart environments.

Realizing a Ultra-Low Latency M-CORD Model for Real-Time Traffic Settings in Smart Cities

At present, the need for an ultra-high speed and efficient communication through mobile and wireless devices is gaining significant popularity. The users are expecting their network to offer real-time streaming without much latency. In turn, this will result in a considerable rise in network bandwidth utilization. The live streaming has to reach the end users mobile devices after traveling through the base station nodes, core network, routers, switches, and other equipment. Further, this will lead to a scenario of content latency and thereby causing the rejection of the mobile devices users' request due to congestion of the network and mobile service providers' core network witnessing an extreme load. In order to overcome such problems in the contemporary 5G mobile networks, an architectural framework is essential, which offers instantaneous, ultra-low latency, high-bandwidth access to applications that are available at the network edge and also making the task processing in close proximity with the mobile device user.