Giving without Notifying: Assessing Compliance of Data Transmission in Android Apps

Now, the devices that can to be connected to internet are increasing, this has allowed to develop new technological innovations in automation and domotic fields. This paper presents an application of Internet of Things (IoT) applied to domotic, in which a domotic network for control and monitoring has been designed and implemented. In the implementation process different electronic modules low cost are used, the most important module is Arduino, connected with others mobile devices which have different communications interfaces. In this context, the TCP/IP protocol be used for data transmission over internet, thanks to easy access to internet on mobile devices, also it has implemented an android app using diferent plataforms as Android Studio and App Inventor. In android app implementation the manual and voice commands for controlling and monitoring all devices into domotic network since a smartphone has been included, at the same time a security network using a Global System Mobile (GSM) network through of Short Message Service (SMS) using the RS 232 protocol was developed and implemented, this process are doing when the user do not have a stable internet connection in the smartphone and needs to have control of impotant devices into domotic metwork.

Android apps rely on secure communication protocol to prove the confidentiality of sensitive data transmission. However, inexperienced developers tend to adopt insecure communication and introduce security risks. To study how prevalent the insecure communication protocols are used by real world Android apps, we conducted an in-depth analysis to examine popular apps from Google Play and MyApp Android app market. We collect 435 apps from major categories, such as gaming, shopping and social networks, and we monitored the communication of those apps and classified their used protocols into three categories: secure, insecure, and proprietary. Then we investigated those proprietary ones to find potential insecure implementation. We designed and implemented RawDroid, a protocol audit system combining network monitoring and program analysis technique to systematically inspect the security of proprietary protocol. We found that a large number of developers frequently use non-standard proprietary protocols. Among all analyzed apps, our security audit revealed that 36.7% apps adopted a proprietary protocol, and all those proprietary protocols fail to achieve confidentiality: some of them send sensitive data in the form of plaintext to servers; some misuse cryptographic algorithms and lead to the exposure of transferred privacy even if the content is encrypted. We believe this kind of protocols pose great security threats to Android ecosystem.

This paper presents a low-cost remote power-quality-failure monitoring system (RPMS) using Android App and TI MCU (micro-controller unit), which is appliable to a micro-grid. The designed RPMS testbed consists of smart nodes, a server, and Android APPs. Especially, the C2000-series MCU-based RPMS smart node that is low-cost compared to existing monitoring systems has both a signal processing function for power signal processing and a data transmission function for power-quality monitoring data transmission. The signal processing function implements both a wavelet-based power failure detection algorithm including sag, swell, and interruption, and a FFT-based power failure detection algorithm including harmonics such that reliable and real-time power quality monitoring is guaranteed. The data transmission function implements a low-complexity RPMS transmission protocol and defines a simple data format (msg_Diag) for power monitoring message transmission. We may watch the monitoring data in real time both at a server and Android phone Apps connected to the WiFi network (or WAN). We use RS-232 (or Bluetooth) as the wired (or wireless) communication media between a server and nodes. We program the RPMS power-quality-failure monitoring algorithm using C language in the CCS (Code Composer Studio) 3.3 environment.

Due to technical advances in mobile devices (e.g., smartphones, tablets) and wireless communications, people now can easily capture user-generated videos (UGVs) anywhere, anytime and instantly share their real-life experiences via social web sites. Enjoying videos has become very popular entertainment. One challenge is that many mobile videos do not have very appealing audio that was captured with the video. In this demonstration, to overcome this issue we propose a music video generation/creation system (Android app and backend system) that aims to make UGVs more attractive by generating scene-adaptive and user-preference aware music tracks. In our system, we take geographic categories, visual content and user listening history into account. In particular, the sequences of geographic categories and visual features are integrated into a SVMhmm model to predict video scene moods. The music genre, as a user preference is also exploited to personalize the recommended songs. We believe this is the first work that predicts scene moods from a real-world video dataset collected by users' daily outdoor recordings to facilitate user-preference aware music video generation. Our experiments confirm that our system can effectively combine objective scene moods and individual music tastes to recommend appealing soundtracks for videos. Our Android app only sends recorded sensor data and a few keyframes of a UGV to a cloud service (backend system) to retrieve recommended music tracks, therefore it is bandwidth efficient since the transmission of video data is not required for analysis.

Android applications (apps) are a combination of code written by the developers as well as third-party libraries that carry out most commonly used functionalities such as advertisement and payments. Running apps in a monitoring environment allows researchers to measure how much network traffic is exchanged between an app and remote endpoints. However, current systems currently do not have the ability to reliably distinguish traffic that is generated by different libraries. This is important, because while mobile users are paying for data traffic without distinctions, some of this traffic is useful (e.g., data for core app functionalities), whereas the rest of the traffic can be considered a nuisance (e.g., excessive advertisements). In this paper, we present Libspector, a system that precisely attributes network traffic coming from an Android app to the library that generated it. To this end, we instrument the Android Framework to inspect the network connections initiated by apps, provide fine-grained information on the libraries in use, and calculate method coverage information while performing dynamic analysis. We then perform a measurement on 25,000 popular Android apps and investigate the relation between different categories of apps with the use of specific libraries. We analyze the method coverage of our dynamic analysis method, and further characterize the endpoint connections established by the Android apps. Our results indicate that advertisement libraries account for over a quarter of the total data transmission. We further observe that there is no strict 1-to-1 correlation between the similar categories of network endpoints and libraries which initiated the data transfer.

In this digital era, integrating Internet of Things (IoT) technology with mobile applications has revolutionised various industries, including weather monitoring. This project presents the development of a weather monitoring app that harnesses the power of IoT and Kotlin programming language. The app utilizes a weather API to obtain real-time weather data and seamlessly communicates with an IoT device, enabling users to access and display weather information conveniently. project begins with a detailed analysis of requirements, outlining the desired features and functionalities of the app. The weather API selection process is discussed, and the chosen API is integrated into the Kotlin app to fetch weather data. Additionally, location services are implemented to offer location-based weather updates. An IoT device, such as a Raspberry Pi or Arduino, is selected for displaying the weather data. The IoT device is connected to the internet and programmed to fetch weather data from the app. Communication protocols between the Android app and the IoT device are established, ensuring smooth data exchange. The app's user interface is designed to provide an intuitive experience for users, with weather data and location information prominently displayed. Error handling mechanisms are implemented to deal with potential API downtimes or communication failures between the app and the IoT device. Through comprehensive testing, the app's functionality, performance, and reliability are assessed. Security measures are implemented to safeguard user data and privacy during data transmission. The result is a robust and user-friendly weather-monitoring app that seamlessly integrates IoT technology with Kotlin's efficiency and flexibility. The app empowers users to access real-time weather updates, enhancing their preparedness for weather changes and enabling informed decision-making for various outdoor activities. With the proliferation of IoT and its impact on various sectors, this project serves as a valuable example of leveraging IoT and Kotlin to develop innovative mobile applications for everyday use. Keywords – Weather Monitoring App, Kotlin, IoT, Real- time Weather Data, Weather API

Using the Android Internet APP and JAVA technology to build a new teaching management platform, the platform has the basic function of the Web server, and students can easily real-time browsing and querying various teaching information from the mobile phone. The platform adopts B/S framework and MVC software as the development environment to layout technology platform by using the Android APP, so the platform has good information querying and resource sharing function. In order to verify the effectiveness and reliability of the platform, we the number of the platform’s data transmission, flow use and flow queries can be real-time counted, which can obtain the platform operation curve and statistical results under three kinds of conditions, so the results can be seen that the platform of data transfer and flow usage are more stable in different period of time, it is no big fluctuations and complies with the design requirements, to provide technical reference for the research of students mobile phone internet teaching.

IoT enabled microfluidic colorimetric detection platform for continuous monitoring of nitrite and phosphate in soil

The high mortality rate associated with cardiovascular disease requires the establishment of a personalized and ubiquitous health monitoring system. With recent advances in wireless sensor network technology, this study provides real-time data collection. Electroencephalography (EEG) is widely used for the evaluation of drowsiness, but it is not practical for careful aerial surveillance due to discomfort caused by the number of electrodes that touch the scalp. In this paper, we proposed a hearing aid-type smart sensor device connected wirelessly to a smartphone for the transmission and display of physiological data. Health care is one of the main concerns of modern people and the demand for health care systems naturally increases. We also built a big data system in this project. Building big data systems has been found to be more efficient than existing systems. This study proposes an algorithm to detect driver drowsiness through analysis of heart rate variability and compares it with EEG-based sleep scores to verify the proposed method. The ECG sensor provides various detection methods to detect RR interval data from ECG data and only transmit abnormal data. The proposed method can reduce the transmission cost and energy consumption of the sensor. We also experimentally demonstrate the energy efficiency of our method. Monitoring results using the new android app and comprehensive dysfunction experiments have been shown to improve classification accuracy.KeywordsU-HealthCareBig dataUbiquitousMonitoring systemEEG

Internet of things (IoT) has captured a promising market in industrial electronics. Considering the scenario, we introduce a wearable wireless electrooculogram (EOG) recorder for IoT-based industrial applications. This device has advantages over existing EOG recorders concerning its ease of wearing, portability and usability. The recording software is an Android app which makes it useful for a common man as well as many researchers working on eye-tracking based IoT applications. The system consists of Ag plated Cu electrodes for capturing the bio-potential near the canthus and the forehead. The analog EOG signal is pre-amplified using a signal conditioning circuit, comprising of an instrumentation amplifier, a bandpass filter and a differential amplifier. An embedded Wi-Fi module is used for transmission of data. The system has been compared with standard EOG recorders, and the results show it has comparable SNR and sampling rates with the existing recorders.

An eye bank is a unit that administers and handles the requisition and distribution of corneas.The proposed system consists of three parts. The first part consists of temperature and humidity sensors, an array of infrared sensors installed on the shelf of the eye bank, and the eye bank, all of which are interconnected by a Microcontroller. The Wi-Fi module is included in the second section for data transmission to the server, and the third section displays the status of the available eye. The website displays the current status of the eye supply available in the eye bank, allowing eye seekers to obtain cornea from the closest eye bank. iBeacon is an Android app that assists users in finding the best eye donor at the right time.The application stores information about the user, such as name, age, blood type, address, etc.This can ensure the security of the application. The app helps users find the correct eye donor when needed by searching for the eye donor in the correct city/region. This helps reduce the time to manually search for donors.

The purpose of the General Data Protection Regulation (GDPR) is to provide improved privacy protection. If an app controls personal data from users, it needs to be compliant with GDPR. However, GDPR lists general rules rather than exact step-by-step guidelines about how to develop an app that fulfills the requirements. Therefore, there may exist GDPR compliance violations in existing apps, which would pose severe privacy threats to app users. In this paper, we take mobile health applications (mHealth apps) as a peephole to examine the status quo of GDPR compliance in Android apps. We first propose an automated system, named HPDROID, to bridge the semantic gap between the general rules of GDPR and the app implementations by identifying the data practices declared in the app privacy policy and the data relevant behaviors in the app code. Then, based on HPDROID, we detect three kinds of GDPR compliance violations, including the incompleteness of privacy policy, the inconsistency of data collections, and the insecurity of data transmission. We perform an empirical evaluation of 796 mHealth apps. The results reveal that 189 (23.7%) of them do not provide complete privacy policies. Moreover, 59 apps collect sensitive data through different measures, but 46 (77.9%) of them contain at least one inconsistent collection behavior. Even worse, among the 59 apps, only 8 apps try to ensure the transmission security of collected data. However, all of them contain at least one encryption or SSL misuse. Our work exposes severe privacy issues to raise awareness of privacy protection for app users and developers.

Communication between normal people and people with vocal and hearing troubles is a difficult task. The sign language used by these people is not understandable by the common people, so it creates a communication barrier. People who are paralyzed also require assistance regularly. For such people we have proposed Implementation of IOT based Smart assistance gloves for disabled people. The gloves we designed is very simple yet effective when compared to the existing system. With the help of flex sensors, the finger gesture is detected and the corresponding instructions are displayed in the android app with audio output. The proposed system is implemented by Arduino uno and Raspberry pi, where the communication between these two modules is done by wireless serial port module due to its secured data transmission. An alert message will be sent through the GSM module during emergency situation.

Forest and land fires are a recurrent issue in several Indonesian regions, necessitating advanced technological solutions for early detection and monitoring due to their significant impact. This research project focuses on developing a prototype system utilizing IoT-based Wireless Sensor Network (WSN) technology to detect forest and land fires. The prototype offers real-time remote monitoring of temperature, humidity, smoke levels, and wind speed in the forest through an Android app or web interface. To validate its performance, the prototype was compared to existing BMKG tools, with results showing minor temperature errors (2.41%) and a humidity error of 17.68%. The anemometer sensor exhibited a slight 4-second data transmission delay. Importantly, the prototype excelled in fire detection, effectively identifying temperature and humidity changes within a 2-meter radius or more indicative of fire outbreaks. This pioneering prototype promises to significantly enhance early warning and response mechanisms for forest and land fires in Indonesia, contributing to more effective environmental conservation and disaster management.

Traditional electrical metering still depends on manual reading, delayed billing and limited visibility of real time power usage, leading to problems such as billing errors, electricity theft, energy wastage and increased workload for utility providers. The reviewed research papers highlight similar limitation in existing systems and emphasize the need for smart, automated and communication enabled metering solution. Many studies propose IoT, GSM, Wi-Fi and Zigbee based smart meters that provide real time monitoring, remote data transmission, prepaid billing option, theft detection, renewable energy integration and automated alerts. Based on these finding, this project present a Smart Energy Meter with GSM Billing and Control that can continuously measure electricity consumption and send live usage update, billing information and notification directly to users through an android app. The system also supports remote load control for prepaid or unpaid billing situations, reducing manual intervention and improving billing accuracy. By offering real time access, automation and enough energy management, the proposed system benefits both consumers and electricity providers while contributing to a more modern, reliable and future ready power infrastructure