Functionality-based mobile application recommendation system with security and privacy awareness

Rocha, Thiago Schmitz Marques da; Souto, Eduardo; El-Khatib, Khalil

doi:10.1016/j.cose.2020.101972

Cited by 10 publications

(7 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Music platforms are able to indicate new songs to individuals, based on their history and their interaction with the platform, which includes the likes and dislikes that the user provides for a given song (Anderson et al, 2020). Platforms that provide applications such as the Apple Store or the Google Play Store, indicate to the individual applications that may be of interest to him based on his history of use (Rocha, Souto & El-Khatib, 2020;Saborido et al, 2018). The same process is found on shopping platforms, which indicate products and services to the customer, based on their search history (on or off the platform, using Web Cookies), purchase history and geographic region, among other indicators (Smith & Linden, 2017).…”

Section: Apps That Know Usmentioning

confidence: 90%

Information management and exponencial learning in Society 5.0: foundations for an integrated system

Oliveira¹,

Pereira²

2021

Preprint

View full text Add to dashboard Cite

Humanity uses the information to reduce discomfort, effort, and errors. With this in mind, headphones were invented, so that the music could be heard without disturbing others; home appliances were created to reduce the effort in washing dishes or clothes, and calculating machines were developed so that human distraction would not cause an accident in calculating the weight that a bridge could support. But the information has hardly changed the certainties and doubts about which university course to take, what the individual's daily life will be like in the academic path, which includes when and what to study, what to eat and what to do in their free time. Is there a hobby that the individual could enjoy, but does not know? There is greater access to information, but many times instead of navigating this information, the individual sinks in the middle of it. In addition, teachers and students remain stuck in the curriculum, with the same menu being provided for carnivores, vegetarians or lactose intolerants. If before, students were beaten with wood in their hands and were attacked psychologically, having to learn the same as everyone else, nowadays only hands are no longer suffering from wood, at least in theory. Reducing mistakes in choosing a higher education course and the whole life that governs the academic path, can be a dream for many individuals, and software that collects enough information to learn about the individual and guide him/her on the beginning of their academic path could be an extremely useful compass. Knowing which university course to take, which discipline, among the electives, to choose, knowing the right time to get up according to the circadian cycle, what to do throughout the day, what and when to eat, are all informational outputs that utopian software could provide so as to contribute to the individual's success. But would such informational management drastically reduce the hassles, efforts, and mistakes to be made, or would it negatively affect the individual's life due to lack of experience with failure? Is the information learned from failure really necessary for success? This article starts from a brief history about information in education, analyses information management in Society 5.0, in the era of exponential technologies, and the construction of competence matrices. The goal is to start a debate about the delegation and trust in software, the management of personal information for individual success.

show abstract

Section: Apps That Know Usmentioning

confidence: 90%

Information management and exponencial learning in Society 5.0: foundations for an integrated system

Oliveira¹,

Pereira²

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Android Security Labware provides a hands-on mobile security experience, promotes interest, and keeps engaged in security [25]. This enables me to gain real-world experience in securing mobile devices, developing and securing mobile applications, and performing penetration testing for mobile devices and mobile applications [26]. This lab kit consists of seven standalone modules covering critical threats related to mobile device security and privacy, mobile application security, and mobile network and communications security (see Table 1).…”

Section: Methodsmentioning

confidence: 99%

Mobile Device Security Evaluation using Reverse TCP Method

Riadi¹,

Aprilliansyah

Sunardi³

2022

KINETIK

View full text Add to dashboard Cite

Security evaluation on Android devices is critical so that users of the operating system are protected from malware attacks such as remote access trojans that can steal users' credential data. Remote access trojan (RAT) attacks can be anticipated by detecting vulnerabilities in applications and systems. This study simulates a remote access trojan attack by exploiting it until the Attacker gains full access to the victim's device. The episode is carried out with several steps: creating a payload, installing applications to the victim's device, connecting listeners, and performing exploits to retrieve important information on the victim's device. Test material using Android 12, problems occurred when trying to install the application because a harmful warning will appear from Play Protect due to not using the latest version of privacy protection which causes the application to be indicated as malware and the like. On Android 11, the application injected with the backdoor was successfully installed on the device and successfully accessed by the attacker. Attackers also get vital information, including system information, contacts, call logs, messages, and full access to the victim's device system directory. Based on this research, it is expected that Android device users constantly update the Android version on the device they are using.

show abstract

“…Lin et al [148] and Cao et al [149] looked into version-sensitive app recommendation by considering the version update of apps. Rocha et al [151] and Gao et al [150] proposed using app permissions, to improve security degree of recommendations.…”

Section: App Usage Prediction and Recommendationmentioning

confidence: 99%

Smartphone App Usage Analysis: Datasets, Methods, and Applications

Tong

Wang

et al. 2022

IEEE Commun. Surv. Tutorials

View full text Add to dashboard Cite

As smartphones have become indispensable personal devices, the number of smartphone users has increased dramatically over the last decade. These personal devices, which are supported by a variety of smartphone apps, allow people to access Internet services in a convenient and ubiquitous manner. App developers and service providers can collect fine-grained app usage traces, revealing connections between users, apps, and smartphones. We present a comprehensive review of the most recent research on smartphone app usage analysis in this survey. Our survey summarizes advanced technologies and key patterns in smartphone app usage behaviors, all of which have significant implications for all relevant stakeholders, including academia and industry. We begin by describing four data collection methods: surveys, monitoring apps, network operators, and app stores, as well as nine publicly available app usage datasets. We then systematically summarize the related studies of app usage analysis in three domains: app domain, user domain, and smartphone domain. We make a detailed taxonomy of the problem studied, the datasets used, the methods used, and the significant results obtained in each domain. Finally, we discuss future directions in this exciting field by highlighting research challenges.

show abstract

Functionality-based mobile application recommendation system with security and privacy awareness

Cited by 10 publications

References 29 publications

Information management and exponencial learning in Society 5.0: foundations for an integrated system

Information management and exponencial learning in Society 5.0: foundations for an integrated system

Mobile Device Security Evaluation using Reverse TCP Method

Smartphone App Usage Analysis: Datasets, Methods, and Applications

Contact Info

Product

Resources

About