The Trend of Mobile Malwares and Effective Detection Techniques

2019 ◽  
pp. 668-682
Author(s):  
Olawale Surajudeen Adebayo ◽  
Normaziah Abdul Aziz
Keyword(s):  
Mobile Devices ◽  
Mobile Phones ◽  
Text Messages ◽  
Mobile Platform ◽  
Desktop Computer ◽  
Detection Techniques ◽  
Mobile Malware ◽  
Windows Phone

The usefulness of mobile phones nowadays has gone beyond making calls and sending text messages. In fact, most of applications available on desktop computer are presently easily accessible on mobile devices, especially smartphone based on Androids, iOS, and Windows phone platforms. However, at the same time, malware is increasingly becoming pervasive on a mobile platform for financial, social and political exploitation. This chapter examines the trends of mobile malware and different efforts of anti-malware writers and researchers in addressing mobile malware on smartphones.

The Trend of Mobile Malwares and Effective Detection Techniques

2015 ◽  
pp. 219-233
Author(s):  
Olawale Surajudeen Adebayo ◽  
Normaziah Abdul Aziz
Keyword(s):  
Mobile Devices ◽  
Mobile Phones ◽  
Text Messages ◽  
Mobile Platform ◽  
Desktop Computer ◽  
Detection Techniques ◽  
Mobile Malware ◽  
Windows Phone

The usefulness of mobile phones nowadays has gone beyond making calls and sending text messages. In fact, most of applications available on desktop computer are presently easily accessible on mobile devices, especially smartphone based on Androids, iOS, and Windows phone platforms. However, at the same time, malware is increasingly becoming pervasive on a mobile platform for financial, social and political exploitation. This chapter examines the trends of mobile malware and different efforts of anti-malware writers and researchers in addressing mobile malware on smartphones.

scholarly journals Passive sensing on mobile devices to improve mental health services with adolescent and young mothers in low-resource settings: the role of families in feasibility and acceptability

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sujen Man Maharjan ◽  
Anubhuti Poudyal ◽  
Alastair van Heerden ◽  
Prabin Byanjankar ◽  
Ada Thapa ◽  
...  
Keyword(s):  
Data Collection ◽  
Health Services ◽  
Mobile Devices ◽  
Family Involvement ◽  
Mobile Phones ◽  
Young Mothers ◽  
Audio Recording ◽  
Low Resource Settings ◽  
Passive Sensing ◽  
Passive Data

Abstract Background Passive sensor data from mobile devices can shed light on daily activities, social behavior, and maternal-child interactions to improve maternal and child health services including mental healthcare. We assessed feasibility and acceptability of the Sensing Technologies for Maternal Depression Treatment in Low Resource Settings (StandStrong) platform. The StandStrong passive data collection platform was piloted with adolescent and young mothers, including mothers experiencing postpartum depression, in Nepal. Methods Mothers (15–25 years old) with infants (< 12 months old) were recruited in person from vaccination clinics in rural Nepal. They were provided with an Android smartphone and a Bluetooth beacon to collect data in four domains: the mother’s location using the Global Positioning System (GPS), physical activity using the phone’s accelerometer, auditory environment using episodic audio recording on the phone, and mother-infant proximity measured with the Bluetooth beacon attached to the infant’s clothing. Feasibility and acceptability were evaluated based on the amount of passive sensing data collected compared to the total amount that could be collected in a 2-week period. Endline qualitative interviews were conducted to understand mothers’ experiences and perceptions of passive data collection. Results Of the 782 women approached, 320 met eligibility criteria and 38 mothers (11 depressed, 27 non-depressed) were enrolled. 38 mothers (11 depressed, 27 non-depressed) were enrolled. Across all participants, 5,579 of the hour-long data collection windows had at least one audio recording [mean (M) = 57.4% of the total possible hour-long recording windows per participant; median (Mdn) = 62.6%], 5,001 activity readings (M = 50.6%; Mdn = 63.2%), 4,168 proximity readings (M = 41.1%; Mdn = 47.6%), and 3,482 GPS readings (M = 35.4%; Mdn = 39.2%). Feasibility challenges were phone battery charging, data usage exceeding prepaid limits, and burden of carrying mobile phones. Acceptability challenges were privacy concerns and lack of family involvement. Overall, families’ understanding of passive sensing and families’ awareness of potential benefits to mothers and infants were the major modifiable factors increasing acceptability and reducing gaps in data collection. Conclusion Per sensor type, approximately half of the hour-long collection windows had at least one reading. Feasibility challenges for passive sensing on mobile devices can be addressed by providing alternative phone charging options, reverse billing for the app, and replacing mobile phones with smartwatches. Enhancing acceptability will require greater family involvement and improved communication regarding benefits of passive sensing for psychological interventions and other health services. Registration International Registered Report Identifier (IRRID): DERR1-10.2196/14734

scholarly journals Research on the Use of Mobile Devices and Headphones on Pedestrian Crossings—Pilot Case Study from Slovakia

Safety ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 17
Author(s):  
Miroslava Mikusova ◽  
Joanna Wachnicka ◽  
Joanna Zukowska
Keyword(s):  
Mobile Phone ◽  
Mobile Devices ◽  
Mobile Phones ◽  
Slovak Republic ◽  
Pedestrian Behavior ◽  
The Road ◽  
Phone Calls ◽  
Lack Of Information ◽  
Interaction Factor ◽  
Future Work

The topic of the use of mobile devices and headphones on pedestrian crossings is much less explored in comparison to the use of the mobile phone while driving. Recent years have seen many discussions on this issue, especially in foreign countries. The Slovak Republic, however, has not been giving it enough attention (and it is not mentioned in the National Road Safety Plan for the Slovak Republic from 2011 to 2020). This paper aims to draw attention to this issue. It presents basic outputs of a pilot study on pedestrian safety, with a focus on the use of mobile devices and headphones at selected non-signalized pedestrian crossings in three Slovak cities. Overall, 9% of pedestrians used headphones or mobile devices at observed pedestrian crossings (4% of them used headphones, 1% used headphones and at same time used their mobile phone, 2% made phone calls and 2% used their mobile phones). While these numbers can be considered relatively low, the study proved that during weekdays every 2 min someone was using the crossing without fully focusing on crossing the road safely. Another main finding was that although the safety risk at pedestrian crossings is increased by factors such as rush hour traffic or reduced visibility, pedestrian behavior related to the use of mobile phones and headphones does not change. A safety assessment was also carried out at the crossings. The results show that pedestrian behavior is not affected by the level of safety of the crossing (e.g., visibility of the crossing for drivers). The results of the presented analysis suggest that action is needed to change that. Due to the lack of information about accidents involving pedestrians using mobile phones and headsets when crossing the road, no relevant statistical data could be analyzed. The dataset collected can be used as a basis for further investigation or comparisons with other countries of the relevant indicators. In future work, we would like to include a pedestrian–driver interaction factor focusing on driver speed behavior in relation to pedestrians (who are on or are about to step onto a pedestrian crossing) and identify critical situations caused by improper behavior of drivers and/or pedestrians. This will help to understand speed adjustment problems related to pedestrian crossings.

Authentication System for Biometric Applications Using Mobile Devices

2013 ◽  
Vol 457-458 ◽  
pp. 1224-1227
Author(s):  
Jian Feng Hu ◽  
Zhen Dong Mu
Keyword(s):  
Information Security ◽  
Mobile Devices ◽  
Information Exchange ◽  
Mobile Platform ◽  
Eeg Signal ◽  
Information Protection ◽  
Security Research ◽  
Authentication System ◽  
Identification Tool

Mobile equipment has now become a new platform for information exchange, spend a lot of information exchange, how to effectively protect the mobile platform information security? Research has shown that, EEG signal can be used as identification tool, the user's information protection and good, this paper to protect the information security of mobile devices to research how to use EEG; the EEG signal is feasible for mobile equipment identification.

scholarly journals An Enhanced Mobile Phone Dialler Application for Blind and Visually Impaired People

2013 ◽  
Vol 2 (4) ◽  
pp. 270 ◽  
Author(s):  
Rana Mohammad Yousef ◽  
Omar Adwan ◽  
Murad Abu-Leil
Keyword(s):  
Mobile Phone ◽  
Mobile Phones ◽  
Visually Impaired ◽  
Voice Recognition ◽  
Blind And Visually Impaired ◽  
Phone Calls ◽  
Visually Impaired People ◽  
Impaired People ◽  
Windows Phone ◽  
Innovative Concept

This paper presents the development of a new mobile phone dialler application which is designed to help blind and visually impaired people make phone calls. The new mobile phone dialler application is developed as a windows phone application to facilitate entering information to touch screen mobile phones by blind people. This application is advantageous through its innovative concept, its simplicity and its availability at an affordable cost. Feedback from users showed that this new application is easy to use and solves many problems of voice recognition applications such as inaccuracy, slowness and interpretation of unusual voices. In addition, this application has increased the users ability to dial phone numbers more independently and less stressfully.

scholarly journals Implementation for Quick Response Code

2019 ◽  
pp. 249-252
Author(s):  
K. Ravikumar ◽  
R. Geetha
Keyword(s):  
Mobile Devices ◽  
Mobile Phones ◽  
Teaching And Learning ◽  
Qr Code ◽  
Quick Response ◽  
Qr Codes ◽  
Response Code ◽  
Quick Response Code ◽  
The People ◽  
Identity Card

Quick Response (QR) codes are versatile. a chunk of long trilingual text, a connected URL, an automatic SMS message, an identity card or simply regarding any data is embedded into the two-dimensional barcode. as well as moderate equipped mobile devices, QR Codes will connect the users to the data quickly and simply. The operations to retrieve or store QR codes are unbelievably easy and fast, and with mobile devices, build them the best academic tools for teaching and learning. QR codes are all over and most of the people have mobile phones equipped with QR code readers. though QR codes existed for over fifteen years, there arent such a lot of analysis applications during this space.

scholarly journals Improving Retention in Care and Promoting Adherence to HIV Treatment: Protocol for a Multisite Randomized Controlled Trial of Mobile Phone Text Messaging (Preprint)

2019 ◽  
Author(s):  
Elvis Asangbeng Tanue ◽  
Dickson Shey Nsagha ◽  
Nana Njamen Theophile ◽  
Jules Clement Nguedia Assob
Keyword(s):  
Health Care ◽  
Health Outcomes ◽  
Mobile Phones ◽  
Text Messaging ◽  
Care Delivery ◽  
Retention In Care ◽  
Hiv Treatment ◽  
Text Messages ◽  
Adherence To Treatment ◽  
Randomized Controlled

BACKGROUND The World Health Organization has prioritized the use of new technologies to assist in health care delivery in resource-limited settings. Findings suggest that the use of SMS on mobile phones is an advantageous application in health care delivery, especially in communities with an increasing use of this device. OBJECTIVE The main aim of this trial is to assess whether sending weekly motivational text messages (SMS) through mobile phones versus no text messaging will improve retention in care and promote adherence to treatment and health outcomes among patients receiving HIV treatment in Fako Division of Cameroon. METHODS This is a multisite randomized controlled single-blinded trial. Computer-generated random block sizes shall be used to produce a randomization list. Participants shall be randomly allocated into the intervention and control groups determined by serially numbered sealed opaque envelopes. The 156 participants will either receive the mobile phone text message or usual standard of care. We hypothesize that sending weekly motivational SMS reminders will produce a change in behavior to enhance retention; treatment adherence; and, hence, health outcomes. Participants shall be evaluated and data collected at baseline and then at 2, 4, and 6 months after the launch of the intervention. Text messages shall be sent out, and the delivery will be recorded. Primary outcome measures are retention in care and adherence to treatment. Secondary outcomes are clinical (weight, body mass index), biological (virologic suppression, tuberculosis coinfection), quality of life, treatment discontinuation, and mortality. The analysis shall be by intention-to-treat. Analysis of covariates shall be performed to determine factors influencing outcomes. RESULTS Recruitment and random allocation are complete; 160 participants were allocated into 3 groups (52 in the single SMS, 55 in the double SMS, and 53 in the control). Data collection and analysis are ongoing, and statistical results will be available by the end of August 2019. CONCLUSIONS The interventions will contribute to an improved understanding of which intervention types can be feasible in improving retention in care and promoting adherence to antiretroviral therapy. CLINICALTRIAL Pan African Clinical Trial Registry in South Africa PACTR201802003035922; https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=3035 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/15680

scholarly journals Survey on Mobile Malware Analysis and Detection

2018 ◽  
Vol 7 (2.32) ◽  
pp. 279 ◽  
Author(s):  
K Swetha ◽  
K V.D.Kiran
Keyword(s):  
Mobile Phones ◽  
Malware Detection ◽  
Detection Methods ◽  
Classification Algorithms ◽  
Malware Analysis ◽  
Consistent System ◽  
Malware Classification ◽  
Mobile Malware

The amazing advances of mobile phones enable their wide utilize. Since mobiles are joined with pariah applications, bundles of security and insurance issues are incited. But, current mobile malware analysis and detection advances are as yet flawed, incapable, and incomprehensive. On account of particular qualities of mobiles such as constrained assets, user action and neighborhood correspondence ability, consistent system network, versatile malware detection faces new difficulties, particularly on remarkable runtime malware area. This paper provides overview on  malware classification, methodologies of assessment, analysis and on and off device detection methods on android. The work mainly focuses on different classification algorithms which are used as a part of dynamic malware detection on android.  

scholarly journals Security assessment of the selected mobile platform

2018 ◽  
Vol 9 ◽  
pp. 302-307
Author(s):  
Aleksandra Iwaniuk
Keyword(s):  
Mobile Devices ◽  
Questionnaire Survey ◽  
System Security ◽  
Mobile Platform ◽  
Security Assessment ◽  
Android System

Smartphones were gradually gaining popularity, so as to effectively replace traditional telephones. Devices creates many capabilities, but they can be a source of threats. In this article analyzed Android system security. Author checked what threats lurk for mobile devices and how the Android system tries to protect them. The questionnaire survey checked how the phone screens are blocked and how often changes are made to the blockade. To check if the screen lock can be removed, tests were performed using Google to find the device, as well as Fone. A summary of results was presented and conclusions were drawn.

scholarly journals Using Device Detection Techniques in M-Learning Scenarios

2013 ◽  
pp. 1188-1203
Author(s):  
Ricardo Queirós ◽  
Mário Pinto
Keyword(s):  
Web Service ◽  
Mobile Devices ◽  
Mobile Device ◽  
Web Interface ◽  
Mobile Web ◽  
Detection Techniques ◽  
Learning Content ◽  
Learning Scenarios ◽  
Rest Api ◽  
Over Time

Recent studies of mobile Web trends show the continued explosion of mobile-friend content. However, the wide number and heterogeneity of mobile devices poses several challenges for Web programmers, who want automatic delivery of context and adaptation of the content to mobile devices. Hence, the device detection phase assumes an important role in this process. In this chapter, the authors compare the most used approaches for mobile device detection. Based on this study, they present an architecture for detecting and delivering uniform m-Learning content to students in a Higher School. The authors focus mainly on the XML device capabilities repository and on the REST API Web Service for dealing with device data. In the former, the authors detail the respective capabilities schema and present a new caching approach. In the latter, they present an extension of the current API for dealing with it. Finally, the authors validate their approach by presenting the overall data and statistics collected through the Google Analytics service, in order to better understand the adherence to the mobile Web interface, its evolution over time, and the main weaknesses.

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