Touch-dynamics based Behavioural Biometrics on Mobile Devices – A Review from a Usability and Performance Perspective

2020 ◽  
Vol 53 (6) ◽  
pp. 1-36
Author(s):  
Elakkiya Ellavarason ◽  
Richard Guest ◽  
Farzin Deravi ◽  
Raul Sanchez-Riello ◽  
Barbara Corsetti

Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 229
Author(s):  
Xianzhong Tian ◽  
Juan Zhu ◽  
Ting Xu ◽  
Yanjun Li

The latest results in Deep Neural Networks (DNNs) have greatly improved the accuracy and performance of a variety of intelligent applications. However, running such computation-intensive DNN-based applications on resource-constrained mobile devices definitely leads to long latency and huge energy consumption. The traditional way is performing DNNs in the central cloud, but it requires significant amounts of data to be transferred to the cloud over the wireless network and also results in long latency. To solve this problem, offloading partial DNN computation to edge clouds has been proposed, to realize the collaborative execution between mobile devices and edge clouds. In addition, the mobility of mobile devices is easily to cause the computation offloading failure. In this paper, we develop a mobility-included DNN partition offloading algorithm (MDPO) to adapt to user’s mobility. The objective of MDPO is minimizing the total latency of completing a DNN job when the mobile user is moving. The MDPO algorithm is suitable for both DNNs with chain topology and graphic topology. We evaluate the performance of our proposed MDPO compared to local-only execution and edge-only execution, experiments show that MDPO significantly reduces the total latency and improves the performance of DNN, and MDPO can adjust well to different network conditions.



2012 ◽  
Vol 8 (4) ◽  
pp. 117 ◽  
Author(s):  
Luca Mainetti ◽  
Luigi Patrono ◽  
Roberto Vergallo

The evolution of modern mobile devices towards novel Radio Frequency (RF) capabilities, such as Near Field Communication, leads to a potential for delivering innovative mobile services, which is still partially unexplored. Mobile proximity payment systems are going to enhance the daily shopping experience, but the access to payment security resources of a mobile device (e.g. the “Secure Element”) by third party applications is still blocked by smartphone and Operating System manufacturers. In this paper, the IDA-Pay system is presented, an innovative and secure NFC micro-payment system based on Peer-to-Peer NFC operating mode for Android mobile phones. It allows to deliver mobile-to-POS micro-payment services, bypassing the need for special hardware. A validation scenario and a system evaluation are also reported to demonstrate the system effectiveness and performance.



2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Qingqing Xie ◽  
Fan Dong ◽  
Xia Feng

The blockchain technology achieves security by sacrificing prohibitive storage and computation resources. However, in mobile systems, the mobile devices usually offer weak computation and storage resources. It prohibits the wide application of the blockchain technology. Edge computing appears with strong resources and inherent decentralization, which can provide a natural solution to overcoming the resource-insufficiency problem. However, applying edge computing directly can only relieve some storage and computation pressure. There are some other open problems, such as improving confirmation latency, throughput, and regulation. To this end, we propose an edge-computing-based lightweight blockchain framework (ECLB) for mobile systems. This paper introduces a novel set of ledger structures and designs a transaction consensus protocol to achieve superior performance. Moreover, considering the permissioned blockchain setting, we specifically utilize some cryptographic methods to design a pluggable transaction regulation module. Finally, our security analysis and performance evaluation show that ECLB can retain the security of Bitcoin-like blockchain and better performance of ledger storage cost in mobile devices, block mining computation cost, throughput, transaction confirmation latency, and transaction regulation cost.



2019 ◽  
Vol 60 (2) ◽  
pp. 409-420 ◽  
Author(s):  
Jalal Khan ◽  
Daniyal Ali Sehrai ◽  
Mushtaq Ahmad Khan ◽  
Haseeb Ahmad Khan ◽  
Salman Ahmad ◽  
...  


2012 ◽  
pp. 1978-2000
Author(s):  
Raúl Aquino ◽  
Luis Villaseñor ◽  
Víctor Rangel ◽  
Miguel García ◽  
Artur Edwards

This chapter describes the implementation and performance evaluation of a novel routing protocol called Pandora, which is designed for social applications. This protocol can be implemented in a broad number of devices, such as commercial wireless routers and laptops. It also provides a robust backbone integrating and sharing data, voice and video between computers and mobile devices. Pandora offers great performance with both fixed and mobile devices and includes important features such as: geographic positioning, residual battery energy monitoring, and bandwidth utilization. In addition, Pandora also considers the number of devices attached to the network. Pandora is experimentally evaluated in a testbed with laptops for the first stage and commercial wireless routers for the second stage. The main goal of Pandora is to provide a reliable backbone for social applications requiring a quality of service (QoS) guarantee. With this in mind, the following evaluation of Pandora considers the following types of traffic sources: transport control protocol (TCP), voice, video and user datagram protocol (UDP) without marks. Pandora is also compared with different queuing disciplines, including: priority queuing discipline (PRIO), hierarchical token bucket (HTB) and DSMARK. Finally, an Internet radio transmission is employed to test the network re-configurability. Results show that queuing the PRIO and HTB disciplines, which prioritizes UDP traffic, performed the best.



Author(s):  
Robin Deegan

Humans are approaching a new and intriguing time with regards to Mobile Human Computer Interaction. For years we have observed the processing power, memory capabilities and battery life of the mobile device increase exponentially. While at the same time mobile devices were converging with additional technologies such as increased connectivity, external peripherals, GPS and location based services etc. But what are the cognitive costs associated with these advancements? The software used on mobile devices is also becoming more sophisticated, demanding more from our limited mental resources. Furthermore, this complex software is being used in distracting environments such as in cars, busses, trains and noisy communal areas. These environments, themselves, have steadily become increasingly more complex and cognitively demanding. Increasingly complex software, installed on increasingly complex mobile devices, being used in increasing complex environments is presenting Mobile HCI with serious challenges. This paper presents a brief overview of five experiments before presenting a final experiment in detail. These experiments attempt to understand the relationship between cognition, distraction, usability and performance. The research determines that some distractions affect usability and not performance while others affect performance but not usability. This paper concludes with a reinforced argument for the development of a cognitive load aware system.





2015 ◽  
Vol 2015 ◽  
pp. 1-23 ◽  
Author(s):  
Chi-Yo Huang ◽  
Yu-Sheng Kao

The smart mobile devices have emerged during the past decade and have become one of the most dominant consumer electronic products. Therefore, exploring and understanding the factors which can influence the acceptance of novel mobile technology have become the essential task for the vendors and distributors of mobile devices. The Phablets, integrated smart devices combining the functionality and characteristics of both tablet PCs and smart phones, have gradually become possible alternatives for smart phones. Therefore, predicting factors which can influence the acceptance of Phablets have become indispensable for designing, manufacturing, and marketing of such mobile devices. However, such predictions are not easy. Meanwhile, very few researches tried to study related issues. Consequently, the authors aim to explore and predict the intentions to use and use behaviors of Phablets. The second generation of the Unified Theory of Acceptance and Use of Technology (UTAUT2) is introduced as a theoretic basis. The Decision Making Trial and Evaluation Laboratory (DEMATEL) based Network Process (DNP) will be used to construct the analytic framework. In light of the analytic results, the causal relationships being derived by the DEMATEL demonstrate the direct influence of the habit on other dimensions. Also, based on the influence weights being derived, the use intention, hedonic motivation, and performance expectancy are the most important dimensions. The analytic results can serve as a basis for concept developments, marketing strategy definitions, and new product designs of the future Phablets. The proposed analytic framework can also be used for predicting and analyzing consumers’ preferences toward future mobile devices.



Author(s):  
Hosam Alamleh ◽  
Ali Abdullah S. AlQahtani

<p>Mobile devices can sense different types of radio signals. For example, broadcast signals. These broadcasted signals allow the device to establish a connection to the access point broadcasting it. Moreover, mobile devices can record different physical layer measurements. These measurements are an indication of the service quality at the point they were collected. These measurements data can be aggregated to form physical layer measurement maps. These maps are useful for several applications such as location fixing, navigation, access control, and evaluating network coverage and performance. Crowdsourcing can be an efficient way to create such maps. However, users in a crowdsourcing application tend to have different devices with different capabilities, which might impact the overall accuracy of the generated maps. In this paper, we propose a method to build physical layer measurements maps by crowdsourcing physical layer measurements, GPS locations, from participating mobile devices. The proposed system gives different weights to each data point provided by the participating devices based on the data source’s trustworthiness. Our tests showed that the different models of mobile devices return GPS location with different location accuracies. Consequently, when building the physical layer measurements maps our algorithm assigns a higher weight to data points coming from devices with higher GPS location accuracy. This allows accommodating a wide range of mobile devices with different capabilities in crowdsourcing applications. An experiment and a simulation were performed to test the proposed method. The results showed improvement in crowdsourced map accuracy when the proposed method is implemented.</p>



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