Faculty Publications
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Item Performance evaluation of web browsers in Android(2013) Harsha Prabha, E.; Piraviperumal, D.; Naik, D.; Kamath S․, S.; Prasad, G.In this day and age, smart phones are fast becoming ubiquitous. They have evolved from their traditional use of solely being a device for communication between people, to a multipurpose device. With the advent of Android smart phones, the number of people accessing the Internet through their mobile phones is on a steep rise. Hence, web browsers play a major role in providing a highly enjoyable browsing experience for its users. As such, the objective of this paper is to analyze the performance of five major mobile web browsers available in the Android platform. In this paper, we present the results of a study conducted based on several parameters that assess these mobile browsers' functionalities. Based on this evaluation, we also propose the best among these browsers to further enrich user experience of mobile web browsing along with utmost performance. © 2013 Springer Science+Business Media New York.Item An android GPS-based navigation application for blind(Association for Computing Machinery, 2014) Nisha, K.K.; Pruthvi, H.R.; Hadimani, S.N.; Guddeti, G.R.M.; Ashwin, T.S.; Domanal, S.G.Visual Impairment makes the person depend on another person for all his works and daily chores. Through the application proposed in this paper, we aim to eliminate this dependency of a visually impaired person when travelling from one place to another. The main goal is to provide information regarding the current location, how much distance and time is required to reach the destination as well as provide the user with the directions and turns to be taken while travelling by providing continuous audio feedback in his understandable language. © is held by the author/owner(s).Item Data synchronization on Android clients(Institute of Electrical and Electronics Engineers Inc., 2015) Kedia, A.; Prakash, A.Past decade has witnessed meteoric advances in the field of mobile computing owing to the development of affordable hardware technologies as well as user-friendly software platforms. Android, the platform marketed by Google has boomed in sales over the past few years making it one of the major mobile platforms in the market. The steady growth of wireless information and communication technology in convergence with rise in the penetration of Internet has led to the evolution of a wide range of mobile applications like news, multi-player games, social networking, messaging, etc. that need to access remote data. For the optimal functioning of all these applications an efficient synchronization mechanism is vital. However smart-phones have limited computational resources, power restrictions and intermittent Internet connections which pose a challenge for smooth synchronization. This paper proposes a two-way data synchronization mechanism between multiple Android clients and a central server to address these challenges. We employ a batching logic to ensure efficient data transfer in poor network environments and a server-side conflict resolution mechanism to reduce overhead on the clients, which ensures optimal processing and battery power consumption by the clients. © 2015 IEEE.Item Smartphone based emotion recognition and classification(Institute of Electrical and Electronics Engineers Inc., 2017) Sneha, H.R.; Rafi, M.; Manoj Kumar, M.V.; Thomas, L.; Annappa, B.This paper proposes a method that classifies the emotion status of a human being based on one's interactions with the smart phone. Due to one or the other practical limitations, the existing set of emotion recognition methods are difficult to use on daily basis (most of the known methods cause inconvenience to user since they require devices like wearable sensors, camera, or answering a questionnaire). The essence of this paper is to analyze the textual content of the message and user typing behavior to build a classifier that efficiently classifies the future instances. Each observation in the data set consists of 14 features. A machine learning technique called Naive Bayes classifier is applied to construct the classifier. Method proposed is capable of classifying emotions in one of the seven classes (anger, disgust, happy, sad, neutral, surprised, and fear). Experimental result has shown 72% accuracy in classification. © 2017 IEEE.Item Comparative Analysis of Modern Mobile Operating Systems(Institute of Electrical and Electronics Engineers Inc., 2021) Chandrashekar, A.; Kumar, P.V.; Chandavarkar, B.R.The importance of smartphones has grown exponentially since their emergence. Smartphones have fundamentally modified the way people live by allowing them to easily access information and communicate with one another. With this meteoric rise, the operating systems run by these mobile devices have also come a long way in terms of their functionalities and their features. The operating system plays a vital and essential role in the use of these devices and cannot be overlooked. The operating system acts as the foundation of the device. The quality of the operating system directly impacts the quality of the device and also determines the usability of the device. A wide range of mobile operating systems, each with its own set of characteristics and features, currently exist in the market. This paper looks into some of the popular operating systems used in mobile devices and aims to compare and evaluate their different characteristics like architecture, security, and other attributes. This paper also analyzes a few of the advantages and disadvantages of these operating systems. © 2021 IEEE.Item IoT Smart Plug based on ESP8266 Wi-Fi Chip(Institute of Electrical and Electronics Engineers Inc., 2022) Garg, R.; Dastagiri Reddy, B.D.The 'Internet of Things' or IoT is a term that has been gaining a lot of traction over the last couple of years. It is intricately linked with the ideas of home automation and making devices 'smart' by connecting them to the internet. Smart versions of everyday devices found in homes are now manufactured on large scales, from smart TVs all the way to smart refrigerators. Such devices are fitted with a slew of different sensors along with in built Wi-Fi capabilities. While these devices can be readily purchased, it is not always feasible to replace existing devices with their smart counterparts. Instead, regular non-smart devices can be made smart through external means. This project proposes to build a plug which can fit into the standard single phase 6A wall socket, to which regular devices/ appliances of the appropriate rating can be connected. Doing so will give the connected device smart capabilities, such as being able to control it remotely using a smartphone from anywhere in the world. The proposed 'smart plug' will be based on the ESP8266 Wi-Fi chip, a relay circuit, and an Android application to control it. © 2022 IEEE.Item Malware Detection in Android Applications Using Machine Learning(Institute of Electrical and Electronics Engineers Inc., 2023) Singh, M.P.; Khan, H.K.Android is a widely used smartphone operating system. Because of its open-source architecture, it is becoming increasingly important in our lives. Android applications are now commonly used in several devices like smartphones, smart tv, etc. Due to many different applications and fundamental features, users often trust Android to protect data. However, research has shown that Android is prone to security issues such as malware. Android malware detection is a hot research topic and requires immediate attention and resolution. This research examines the numerous factors of the Android Application Package (APK) and presents a machine learning-based model for detecting malware in Android applications. Experimental analysis of the proposed model using a standard dataset shows that it can be a viable solution in the future. © 2023 IEEE.Item Experimental analysis of Android malware detection based on combinations of permissions and API-calls(Springer-Verlag France 22, Rue de Palestro Paris 75002, 2019) Singh, A.K.; Jaidhar, C.D.; M.a, M.A.A.Android-based smartphones are gaining popularity, due to its cost efficiency and various applications. These smartphones provide the full experience of a computing device to its user, and usually ends up being used as a personal computer. Since the Android operating system is open-source software, many contributors are adding to its development to make the interface more attractive and tweaking the performance. In order to gain more popularity, many refined versions are being offered to customers, whose feedback will enable it to be made even more powerful and user-friendly. However, this has attracted many malicious code-writers to gain anonymous access to the user’s private data. Moreover, the malware causes an increase of resource consumption. To prevent this, various techniques are currently being used that include static analysis-based detection and dynamic analysis-based detection. But, due to the enhancement in Android malware code-writing techniques, some of these techniques are getting overwhelmed. Therefore, there is a need for an effective Android malware detection approach for which experimental studies were conducted in the present work using the static features of the Android applications such as Standard Permissions with Application Programming Interface (API) calls, Non-standard Permissions with API-calls, API-calls with Standard and Nonstandard Permissions. To select the prominent features, Feature Selection Techniques (FSTs) such as the BI-Normal Separation (BNS), Mutual Information (MI), Relevancy Score (RS), and the Kullback-Leibler (KL) were employed and their effectiveness was measured using the Linear-Support Vector Machine (L-SVM) classifier. It was observed that this classifier achieved Android malware detection accuracy of 99.6% for the combined features as recommended by the BI-Normal Separation FST. © 2019, Springer-Verlag France SAS, part of Springer Nature.