Relevant bibliographies by topics / APP PERMISSION

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'APP PERMISSION'

Author: Grafiati
Published: 16 January 2024

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Journal articles on the topic "APP PERMISSION"

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Xu, Guosheng, Shengwei Xu, Chuan Gao, Bo Wang, and Guoai Xu. "PerHelper: Helping Developers Make Better Decisions on Permission Uses in Android Apps." Applied Sciences 9, no. 18 (September 5, 2019): 3699. http://dx.doi.org/10.3390/app9183699.

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Permission-related issues in Android apps have been widely studied in our research community, while most of the previous studies considered these issues from the perspective of app users. In this paper, we take a different angle to revisit the permission-related issues from the perspective of app developers. First, we perform an empirical study on investigating how we can help developers make better decisions on permission uses during app development. With detailed experimental results, we show that many permission-related issues can be identified and fixed during the application development phase. In order to help developers to identify and fix these issues, we develop PerHelper, an IDEplugin to automatically infer candidate permission sets, which help guide developers to set permissions more effectively and accurately. We integrate permission-related bug detection into PerHelper and demonstrate its applicability and flexibility through case studies on a set of open-source Android apps.
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Naga Malleswari, D., A. Dhavalya, V. Divya Sai, and K. Srikanth. "A detailed study on risk assessment of mobile app permissions." International Journal of Engineering & Technology 7, no. 1.1 (December 21, 2017): 297. http://dx.doi.org/10.14419/ijet.v7i1.1.9706.

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Mobile phone have user’s personal and private information. When mobile applications have the permission to access to this information they may leak it to third parties without user’s consent for their own benefits. As users are not aware of how their personal information would be used once applications are installed and permissions are granted, this raises a potential privacy concern. Therefore, there is a need for a risk assessment model that can intimate the users about the threats the mobile application poses to the user's private information. We propose an approach that helps in increasing user’s awareness of the privacy risk involved with granting permissions to Android applications. The proposed model focuses on the requested permissions of the application and determines the risk based on the permission set asked and gives a risk score.
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Ullah, Salim, Muhammad Sohail Khan, Choonhwa Lee, and Muhammad Hanif. "Understanding Users’ Behavior towards Applications Privacy Policies." Electronics 11, no. 2 (January 13, 2022): 246. http://dx.doi.org/10.3390/electronics11020246.

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Recently, smartphone usage has increased tremendously, and smartphones are being used as a requirement of daily life, equally by all age groups. Smartphone operating systems such as Android and iOS have made it possible for anyone with development skills to create apps for smartphones. This has enabled smartphone users to download and install applications from stores such as Google Play, App Store, and several other third-party sites. During installation, these applications request resource access permissions from users. The resources include hardware and software like contact, memory, location, managing phone calls, device state, messages, camera, etc. As per Google’s permission policy, it is the responsibility of the user to allow or deny any permissions requested by an app. This leads to serious privacy violation issues when an app gets illegal permission granted by a user (e.g., an app might request for granted map permission and there is no need for map permission in the app, and someone can thereby access your location by this app). This study investigates the behavior of the user when it comes to safeguarding their privacy while installing apps from Google Play. In this research, first, seven different applications with irrelevant permission requests were developed and uploaded to two different Play Store accounts. The apps were live for more than 12 months and data were collected through Play Store analytics as well as the apps’ policy page. The preliminary data analysis shows that only 20% of users showed concern regarding their privacy and security either through interaction with the development team through email exchange or through commenting on the platform and other means accordingly.
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Onik, Md Mehedi Hassan, Chul-Soo Kim, Nam-Yong Lee, and Jinhong Yang. "Personal Information Classification on Aggregated Android Application’s Permissions." Applied Sciences 9, no. 19 (September 24, 2019): 3997. http://dx.doi.org/10.3390/app9193997.

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Android is offering millions of apps on Google Play-store by the application publishers. However, those publishers do have a parent organization and share information with them. Through the ‘Android permission system’, a user permits an app to access sensitive personal data. Large-scale personal data integration can reveal user identity, enabling new insights and earn revenue for the organizations. Similarly, aggregation of Android app permissions by the app owning parent organizations can also cause privacy leakage by revealing the user profile. This work classifies risky personal data by proposing a threat model on the large-scale app permission aggregation by the app publishers and associated owners. A Google-play application programming interface (API) assisted web app is developed that visualizes all the permissions an app owner can collectively gather through multiple apps released via several publishers. The work empirically validates the performance of the risk model with two case studies. The top two Korean app owners, seven publishers, 108 apps and 720 sets of permissions are studied. With reasonable accuracy, the study finds the contact number, biometric ID, address, social graph, human behavior, email, location and unique ID as frequently exposed data. Finally, the work concludes that the real-time tracking of aggregated permissions can limit the odds of user profiling.
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Paul, Nishtha, Arpita Jadhav Bhatt, Sakeena Rizvi, and Shubhangi. "Malware Detection in Android Apps Using Static Analysis." Journal of Cases on Information Technology 24, no. 3 (July 2022): 1–25. http://dx.doi.org/10.4018/jcit.20220701.oa6.

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Frequency of malware attacks because Android apps are increasing day by day. Current studies have revealed startling facts about data harvesting incidents, where user’s personal data is at stake. To preserve privacy of users, a permission induced risk interface MalApp to identify privacy violations rising from granting permissions during app installation is proposed. It comprises of multi-fold process that performs static analysis based on app’s category. First, concept of reverse engineering is applied to extract app permissions to construct a Boolean-valued permission matrix. Second, ranking of permissions is done to identify the risky permissions across category. Third, machine learning and ensembling techniques have been incorporated to test the efficacy of the proposed approach on a data set of 404 benign and 409 malicious apps. The empirical studies have identified that our proposed algorithm gives a best case malware detection rate of 98.33%. The highlight of interface is that any app can be classified as benign or malicious even before running it using static analysis.
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Naderi, Hamid, and Behzad Kiani. "Security Challenges in Android mHealth Apps Permissions: A Case Study of Persian Apps." Frontiers in Health Informatics 9, no. 1 (September 2, 2020): 41. http://dx.doi.org/10.30699/fhi.v9i1.224.

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Introduction: In this study, Persian Android mobile health (mhealth) applications were studied to describe usage of dangerous permissions in health related mobile applications. So the most frequently normal and dangerous permissions used in mhealth applications were reviewed.Materials and Methods: We wrote a PHP script to crawl information of Android apps in “health” and “medicine” categories from Cafebazaar app store. Then permission information of these application were extracted.Results: 11627 permissions from 3331 studied apps were obtained. There was at least one dangerous permission in 48% of reviewed apps. 41% of free applications, 53% of paid applications and 71% of in-purchase applications contained dangerous permissions. 1321 applications had writing permission to external storage of phone (40%), 1288 applications had access to read from external storage (39%), 422 applications could read contact list and ongoing calls (13%) and 188 applications were allowed to access phone location (5%).Conclusion: Most of Android permissions are harmless but significant number of the apps have at least one dangerous permission which increase the security risk. So paying attention to the permissions requested in the installation step is the best way to ensure that the application installed on your phone can only access what you want.
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Xiong, Aiping, Huangyi Ge, Wanling Zou, Ninghui Li, and Robert W. Proctor. "Increasing the Influence of Permission Safety on App Selections by Changes in Visual Representation." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 797. http://dx.doi.org/10.1177/1541931213601692.

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Previous studies have shown that inclusion of a permission safety score/cue in the early stage of selecting an app assists users in making safer choices (Chen, Gates, Li, & Proctor, 2015; Gates, Chen, Li, & Proctor, 2014; Rajivan & Camp, 2016). Yet, user ratings were typically weighted more in app-selection decisions than a summary permission safety score, suggesting that app-associated risks are not fully understood or known by users. In daily interactions, people make privacy decisions not just based on rational considerations but also on heuristics (e.g., take the first, Dogruel, Joeckel, & Bowman, 2015). Interfaces of popular online services and systems sometimes exploit these heuristics and biases to nudge people to act in ways that are not always aligned with their own intentions (Stutzma, Gross, & Acquisti, 2013). On the contrary, the goal of present study was to evaluate various formats for presenting the permission safety scores to nudge users to make decisions that are in better agreement with their security and privacy objectives. With 2 studies, we found that a 3-color representation of permission safety promotes safe behavior and communicates privacy of apps well. In Experiment 1, the permission safety score was placed above or below the user rating, and it was conveyed by a number from 1 to 5 paired with a shield or lock icon. The user rating was presented as a number from 1 to 5, paired with a gray star. Participants completed six app-selection tasks, in which, for each, two apps out of six were chosen. The percentage of app selection was higher with increased safety as well as increased user ratings. Permission safety interacted with user rating: For apps with lower user ratings the permission safety did not influence app selection, but for apps with higher user ratings an increased permission safety score led to more app selection. However, neither location (above or below) nor the icon type showed a main effect, nor did they interact. In Experiment 2, the 3-level permission safety score was conveyed by color (red, yellow, green), emoticons (frown, neutral, smile), color with emoticons, or a number from 1 to 3 paired with a lock icon. Participants performed the same tasks as Experiment 1. The results were similar as Experiment 1 except that presentation format interacted with permission safety score. Further analysis showed that that the permission safety score had more influence on app selection when it was represented by conditions with color coding, indicating that permission safety was weighted more in the app-selection decisions when permission safety was presented with 3-color-coding. The role of color in enhancing risk perception is consistent with the role of color in enhancing hazard perception in warning literature (Wogalter, 2006). Given the relative quickness of the decision and the limited cues that users consider during app selection, their attention should be directed to more important app-specific privacy characteristics. Our results provided evidence that 3-color coding can shift users’ attention and influence users to make safer app selections. In designing a visual privacy rating to nudge people away from risky apps, leveraging visual attributes that are prevalent for conveying valence is recommended.
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Reimer, Helmut. "App „Permission Watcher“ für Android-Smartphones." Datenschutz und Datensicherheit - DuD 36, no. 3 (March 2012): 218. http://dx.doi.org/10.1007/s11623-012-0079-5.

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Liu, Zhongxin, Xin Xia, David Lo, and John Grundy. "Automatic, highly accurate app permission recommendation." Automated Software Engineering 26, no. 2 (March 19, 2019): 241–74. http://dx.doi.org/10.1007/s10515-019-00254-6.

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Yilmaz, Saliha, and Mastaneh Davis. "Hidden Permissions on Android: A Permission-Based Android Mobile Privacy Risk Model." European Conference on Cyber Warfare and Security 22, no. 1 (June 19, 2023): 717–24. http://dx.doi.org/10.34190/eccws.22.1.1453.

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The continuously increasing amount of data input on mobile devices has made collating and monitoring users’ data not only uniquely personalised but easier than ever. Along with that, mobile security threats have overtaken with rising numbers in bank fraud and personal information leaks. This suggests that there is a significant lack of awareness of security issues among mobile users. Specifically, permission-based passive content leaks are getting more attention due to the emerging issues in data privacy. One reason for this is that permissions are running in the background collecting and transmitting data between applications within the same permission group, without the user's knowledge. This means, that a supposedly innocent application like the Clock, which is linked with the Calendar to provide the date and time functionality, can have access to any other application within the same Calendar permission group, which is compromising confidentiality. Moreover, this can lead to a violation of data privacy as the user is not aware of which assets are being shared between permissions. Developers of mobile platforms have implemented permission-based models to counteract these issues, however, application designers have shown that they are not necessarily complying with the General Data Protection Regulations (GDPR). For the mobile user, this means that app developers, app providers, and third parties who are included in the applications, can gain access to sensitive data without user consent or awareness. To address this issue, this study examines permissions that are inherent in the Android mobile infrastructure and exemplifies how they can reveal delicate user information, identify user behaviour, and can be shared among other applications - without obviously breaching GDPR guidelines. 10 first-party Android applications were statically analysed by their permissions and manually investigated for their actual purpose and privacy risk. Finally, considering the affected area, these permissions were categorised into four asset groups that form the base of a risk model. With risk levels from low to high, this model provides detection of risks on data privacy in mobile permissions and highlights the difficulty with GDPR compliance, which we therefore named PRAM, a permission-based Android Mobile Privacy Risk Assessment Model.
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Dissertations / Theses on the topic "APP PERMISSION"

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Kulkarni, Keyur. "Android Malware Detection through Permission and App Component Analysis using Machine Learning Algorithms." University of Toledo / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1525454213460236.

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Rustgi, Pulkit. "The Evaluation of an Android Permission Management System Based on Crowdsourcing." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/6033.

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Mobile and web application security, particularly concerning the area of data privacy, has received much attention from the public in recent years. Most applications are installed without disclosing full information to users and clearly stating what they have access to. This often raises concerns when users become aware of unnecessary information being collected or stored. Unfortunately, most users have little to no technical knowledge in regard to what permissions should be granted and can only rely on their intuition and past experiences to make relatively uninformed decisions. DroidNet, a crowdsource based Android recommendation tool and framework, is a proposed avenue for the technically incapable. DroidNet alleviates privacy concerns and presents users with permission recommendations of high confidence based on the decisions from expert users on the network who are using the same applications. The framework combines an interactive user interface, used for data collection and presenting permission recommendations to users, with a transitional Bayesian inference model and multiple algorithms used for rating users based on their respective expertise levels. As a result, the recommendations that are provided to users are based on aggregated expert responses and their confidence levels. This work presents the completed DroidNet project in its entirety, including the implementation of the application, algorithms, and user interface itself. Additionally, this thesis presents and utilizes a unique collection of real-world data from actual Android users. The primary goal of this work is to evaluate the effectiveness and accuracy of DroidNet's recommendations and to show that regular mobile device users can benefit from crowdsourcing.
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Lu, Can. "Revisiting the Evolution of Android Permissions." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535377084768501.

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Almuhimedi, Hazim. "Helping Smartphone Users Manage their Privacy through Nudges." Research Showcase @ CMU, 2017. http://repository.cmu.edu/dissertations/1103.

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The two major smartphone platforms (Android and iOS) have more than two mil- lion mobile applications (apps) available from their respective app stores, and each store has seen more than 50 billion apps downloaded. Although apps provide desired functionality by accessing users’ personal information, they also access personal information for other purposes (e.g., advertising or profiling) that users may or may not desire. Users can exercise control over how apps access their personal information through permission managers. However, a permission manager alone might not be sufficient to help users manage their app privacy because: (1) privacy is typically a secondary task and thus users might not be motivated enough to take advantage of the permission manager’s functionality, and (2) even when using the permission manager, users often make suboptimal privacy decisions due to hurdles in decision making such as incomplete information, bounded rationality, and cognitive and behavioral biases. To address these two challenges, the theoretical framework of this dissertation is the concept of nudges: “soft paternalistic” behavioral interventions that do not restrict choice but account for decision making hurdles. Specifically, I designed app privacy nudges that primarily address the incomplete information hurdle. The nudges aim to help users make better privacy decisions by (1) increasing users’ awareness of privacy risks associated with apps, and (2) temporarily making privacy the primary task to motivate users to review and adjust their app settings. I evaluated app privacy nudges in three user studies. All three studies showed that app privacy nudges are indeed a promising approach to help users manage their privacy. App privacy nudges increased users’ awareness of privacy risks associated with apps on their phones, switched users’ attention to privacy management, and motivated users to review their app privacy settings. Additionally, the second study suggested that not all app privacy nudge contents equally help users manage their privacy. Rather, more effective nudge contents informed users of: (1) contexts in which their personal information has been accessed, (2) purposes for apps’ accessing their personal information, and (3) potential implications of secondary usage of users’ personal information. The third study showed that user engagement with nudges decreases as users receive repeated nudges. Nonetheless, the results of the third experiment also showed that users are more likely to engage with repeated nudges (1) if users have engaged with previous nudges, (2) if repeated nudges contain new in- formation (e.g., additional apps, not shown in earlier nudges, that accessed sensitive resources), or (3) if the nudge contents of repeated nudges resonate with users. The results of this dissertation suggest that mobile operating system providers should enrich their systems with app privacy nudges to assist users in managing their privacy. Additionally, the lessons learned in this dissertation may inform designing privacy nudges in emerging areas such as the Internet of Things.
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Dahlberg, Daniel, Tim Irmel, and Jacob Forsström. "Android-användaren och appbehörigheter : Attityder och beteenden kopplat till säkerhet på mobilen." Thesis, Umeå universitet, Institutionen för informatik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-148004.

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The Android OS is ever growing on the global market, reaching more and more people. This have led to the distribution of millions of applications, that the Android user can interact with. However, the usage of Android apps is not risk free and there are various methods deployed by Google Play to protect the privacy of the Android owner. One of these protective measures are permissions. However, as permissions are controlled by the user, there is a need of comprehending the user behaviour and attitude to the permissions. Lack of understanding the importance, and of the permission itself, could present a real danger of privacy trespassing to the user. In this paper we evaluate the rate of attitude and behaviour by questionnaire and empirical quality-driven interviews. We compare and scrutinize our data with older studies. We identify factors contributing the failure to comply with permission warnings. Also, we find that there are connections between factors such as gender and age, for how the user behaviour and attitude conclude with permissions. In the end we present an exhaustive analysis and discussion to our results, ending with a conclusion that there are differences to be found from older studies and that there are connections in gender and age with how the user acts by permissions.
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Su, Shu-Miaw. "English planning permission and Taiwanese development permission : the relevant measures of planning permission - a lesson from English experience." Thesis, University College London (University of London), 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.298175.

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Sagar, Shraddha. "PREDICTION OF PROTECTED-PERMISSIVE LEFT-TURN PHASING CRASHES BASED ON CONFLICT ANALYSIS." UKnowledge, 2017. https://uknowledge.uky.edu/ce_etds/60.

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Left-turning maneuvers are considered to be the highest risk movements at intersections and two-thirds of the crashes associated with left-turns are reported at signalized intersections. Left-turning vehicles typically encounter conflicts from opposing through traffic. To separate conflicting movements, transportation agencies use a protected-only phase at signalized intersections where each movement is allowed to move alone. However, this could create delays and thus the concept of a protected-permissive phase has been introduced to balance safety and delays. However, the permissive part of this phasing scheme retains the safety concerns and could increase the possibility of conflicts resulting in crashes. This research developed a model that can predict the number of crashes for protected-permissive left-turn phasing, based on traffic volumes and calculated conflicts. A total of 103 intersections with permissive-protected left-turn phasing in Kentucky were simulated and their left-turn related conflicts were obtained from post processing vehicle trajectories through the Surrogate Safety Assessment Model (SSAM). Factors that could affect crash propensity were identified through the Principal Component Analysis in Negative Binomial Regression. Nomographs were developed from the models which can be used by traffic engineers in left-turn phasing decisions with enhanced safety considerations.
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Jamil, Eva, and Mazdak Shirazi. "Spelar behörighetskrav någon roll? : En kvantitativ studie av Android användares beteende och förståelse." Thesis, Högskolan i Borås, Akademin för bibliotek, information, pedagogik och IT, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-12225.

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Problem - Android är det ledande operativsystemet på marknaden, samtidigt har tidigare forskning påvisat att skadlig kod och mobila attacker främst har riktats mot Androidenheter. Attacker utförs genom att applikationer som innehar skadlig kod, får den åtkomst på enheten som de begär genom att applikationsbehörigheter godkänns av användaren före installation av en applikation. Ett stort problem är att användarna i dagsläget väljer att ignorera behörigheterna före installation samt inte förstår dess betydelse. Frågeställning och syfte - Studien syftar till att undersöka tre frågeställningar. Den första forskningsfrågan behandlar hypoteser kring hur pass medvetna Androidanvändarna är om riskerna som finns hos tio applikationsbehörigheter vilket ofta förekommer bland skadliga applikationer. Vidare var målet med studien att undersöka om det finns ett samband mellan användarnas medvetenhet och nedladdningsbeteende. Den sista frågeställningen undersöker om användarna läser igenom applikationsbehörigheter före installation av en applikation och vilka bakgrundsorsaker det finns ifall de inte gör det. Metod - Kvantitativa metoder har använts i form av att det empiriska materialet inhämtats med hjälp av en enkätundersökning. I studien deltog 116 respondenter och resultatet togs fram med hjälp av stapeldiagram, korstabeller, Chi2-tester och frekvenstabeller. Resultat och slutsats - Målet har uppfyllts till hög grad, dock hade det varit gynnsamt att ha ett större urval för att möjligen kunna säkerställa samt stärka signifikansen i Chi2-testerna. Resultatet visade att en hög grad av användarna inte är medvetna om riskerna hos de undersökta behörigheterna. Vidare visade fynden att det finns ett visst samband mellan användarnas medvetenhet och nedladdningsbeteende då sex av tio hypoteser bekräftats. Resultatet visade även att 62 procent av användarna aldrig alternativt sällan läser igenom behörigheterna före installation, samt att orsaken till detta är att de inte förstår behörigheternas beskrivning alternativt inte lägger märke till behörigheterna. Slutligen påpekade respondenterna att de inte förstår behörigheternas beskrivning på grund av att de är för korta samt innehåller för många tekniska termer. Originalitet - Studiens resultat nyttjar främst Androidanvändarna för att öka deras kunskap vilket skyddar dem mot de risker som finns. Resultatet ger dock även nytta för vidare utveckling av applikationsbehörigheterna för att mer effektivt fungera som en varningsmetod vid nedladdning. Det som är nytt och värdefullt i studien är att vi baserat på problemen som påvisats hos tidigare forskning, valt att ytterligare fördjupa oss inom ämnet. Studien har undersökt om det finns ett samband mellan användarnas medvetenhet och nedladdningsbeteende, samt vilka bakgrundsorsaker det finns som medfört att användarna inte läser igenom samt inte förstår sig på applikationsbehörigheterna. Originalitet finns även i studien då vi avgränsat oss till att specifikt undersöka medvetenheten kring tio behörigheter som ofta förekommer bland skadliga applikationer, men som även uppkommer hos vanliga applikationer på Google Play.
Problem – Android is the leading operative system on the market, while previous studies have shown that malware and attacks have mostly been targeted at Android units. Attacks are executed when applications that consist malware gets access of the permissions they demand of the unit. This is by the approval of the user before an installation of an application. A problem is that many users ignores or don’t understand the permission they give applications access to. Purpose - The study aims to examine three issues. The first research question contains hypotheses about how aware Android users are of the risks which ten application permissions contain. These permissions often occurs among malicious applications but are also included among safe applications at Google Play. Furthermore, the objective of this study is to investigate whether there is a connection between the user awareness and their downloading behavior. The last issue examines whether users read through the application permissions before installing an application, and what possible reasons that causes them to not read the permissions. Methodology - Quantitative methods have been used by gathering the empirical material through a questionnaire. The study involved 116 respondents and the results were created by using bar graphs, crosstabs, Chi-square tests and frequency tables. Results and Conclusion - The goal has been met to a large extent, however, it would have been beneficial to have a larger selection to possibly be able to ensure and strengthen the significance of the Chi-square tests. The result showed that a high degree of users are not aware of the risks of the investigated permissions. Further findings showed that there is some connection between the user’s awareness and download behavior, since six out of ten hypotheses got confirmed. The results also showed that 62 percent of the users never alternatively rarely read permissions before installation. The reason for this is that they don’t understand the permissions associated description, alternatively don’t notice the permissions at all. Finally, the respondents indicated that they do not understand the description of the permissions because they are too short and have too many technical terms. Originality - The results of the study mainly benefits the Android users since it increases their knowledge which protects them against the risks. The result, however, also benefit the further development of the application permissions, to make them work more effectively as a warning method. What’s new and valuable in the study is that it’s based on the problems that was identified in previous research and we decided to further immerse ourselves in the subject. The study has investigated whether there is a connection between the user awareness and downloading behavior, as well as the background causes which makes the users ignore and don’t understand the permissions. Originality is also found in the study since we limited ourselves to specifically investigate ten permissions that often occur among malicious applications. The study is written in Swedish.
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RAWAL, PRAVEEN SINGH. "APP PERMISSION CLASSIFICATION : STATIC AND DYNAMIC METHODS." Thesis, 2023. http://dspace.dtu.ac.in:8080/jspui/handle/repository/20424.

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It is no secret that Android is one of the most widely used smartphone operating systems globally, boasting a staggering 2.5 billion active users. However, data secu¬rity has become a crucial aspect of smartphone usage with the increasing reliance on smartphones to store sensitive personal information. Unfortunately, many apps tend to collect user data without the user's knowledge or consent, which can harm data security. To counter this, Android has included an inbuilt security feature called app permission to enable users to control app access. This feature enables users to grant or decline app access to various phone features such as camera, microphone, and location data. The study proposes two methodology for classification app permissions. Firstly, static novel three-tiered system called APEC (App Permission Classification with Efficient Clustering).The study provides an insightful analysis of app permissions using a dataset of 2 million app permissions and app categories from the Google Play Store. The static novel three-tiered system called APEC (App Permission Classification with Efficient Clustering) aims to determine the safety of app permis¬sions based on their usage frequency within specific app categories. This system categorizes apps into three levels, clustering, approval, and classification, to ensure users can select appropriate permissions and developers can establish the minimum requirements for their apps to function smoothly. To accomplish this, APEC uses DBSCAN clustering to group apps based on their respective categories and evalu¬ate the safety of their permissions. Furthermore, it employs the Decision Tree and Random Forest machine learning algorithms to classify new app permissions as safe or unsafe. The proposed system achieved an impressive accuracy rating of 93.8% and 95.8% using the Decision Tree and Random Forest algorithms, respectively. Secondly, a dynamic methodology App Permission Classification Dynamic Model (APCM) based on APEC with added features and capabilities. It keeps track of the app permissions requested by various apps using a dataset of 2 million apps from the Google Play Store to train a random forest-based model using DBSCAN clustering. The APCM analyses each permission request's frequency in a category and creates a frequency map accordingly. This model is critical in rating the app permission as safe or unsafe by using DBSCAN clustering and predicting using a random forest machine learning algorithm. The APCM further enhances the results by using PSO¬BO optimization over the random forest, which is considered a highly accurate approach. The APCM provides a better experience and ensures that users can use apps safely without any concerns about their security. By analyzing the frequency of each permission request in a category, the APCM can identify safe and unsafe permissions and ensure that users can use apps without any worries. This model considers user preferences while classifying apps using the Dataset, ensuring a more personalized and satisfying user experience. The APCM has achieved an impressive accuracy of 87% in classifying an app's permission as safe or unsafe. Overall, the APCM is a highly innovative and effective approach that can help users ensure their apps are safe and secure. The use of DBSCAN clustering and random forest machine learning algorithms, and PSO-BO optimization ensure that the APCM is highly accurate and can provide a reliable classification of app permissions. This model is also highly user-friendly, ensuring users can use apps safely and securely without concerns about their security or data privacy.
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Wu, Min-Xun, and 吳旻訓. "Understanding the Impacts of Permission Requested on Mobile App Adoption." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/ykzfa4.

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碩士
國立中山大學
資訊管理學系研究所
102
Because of the expanding of smartphones, the applications on smartphones, Apps, are widely discussed. In Android platform, Apps have to acquire permissions in order to provide various functions for users. However, Apps might request more permissions than they need. Users have to grant permissions requested by Apps before downloading Apps. The purpose of this study is understanding the impacts of permissions on users'' intention to download mobile Apps. We proposed the concept of &;quot;permission-function fit (PFF)&;quot;, and included perceived privacy risk and social exchange theory into TAM to explore the research purpose. The results of this study are: (1) users'' attitude toward the App positively influences their download intention. (2) Users'' perceived usefulness and the ranking of the App positively influence users'' attitude toward the App; perceived privacy risk negatively affect users'' attitude; when App requests more permissions than it needs, users have negative attitude toward it. Perceived usefulness has the strongest effect on attitude. (3)The privacy level of permissions positively affects users'' perception of privacy risk; when Apps request more permissions than they need, users perceive higher privacy risk.
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Books on the topic "APP PERMISSION"

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Sayles, Victoria. 11. Licences and proprietary estoppel. Oxford University Press, 2018. http://dx.doi.org/10.1093/he/9780198815198.003.0011.

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Each Concentrate revision guide is packed with essential information, key cases, revision tips, exam Q&As, and more. Concentrates show you what to expect in a law exam, what examiners are looking for, and how to achieve extra marks. This chapter discusses licences. A licence is permission given by the licensor to the licensee to allow the latter to enter the land of the former, which, without such permission would otherwise amount to a trespass. Different types of licences have different rules in relation to the original parties and successors in title. A bare licence is revocable by the licensor and does not bind a third party. A licence coupled with an interest, ie a profit à prendre, may be irrevocable and may bind a third party whilst the interest remains. Contractual licences arise under the terms of a contract. An estoppel licence arises as a result of a representation by the licensor and a detrimental reliance by the licensee. It is binding between these two parties but is also capable of binding a third party.
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Polivach, A., and P. Gudev. Polivach A.P., Gudev P.A. The IMEMO Sea Powers’ Rankings 2021 (2.0). – Moscow, IMEMO, 2021. – 178 p. Primakov National Research Institute of World Economy and International Relations, Russian Academy of Sciences (IMEMO), 23, Profsoyuznaya Str., Moscow, 117997, Russian Federation, 2021. http://dx.doi.org/10.20542/978-5-9535-0601-4.

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This book describes the system of indexes, developed by the IMEMO for evaluation of the overall maritime potential of a country. The Index of Maritime Might (IMM) is atop this system. This research includes the rankings of the top-100 countries according to their involvement in the maritime domain. The countries are compared by their ability to conduct a variety of maritime activities, either military or economical, which were calculated on the basis of statistical data as of the 1st of January 2021. This edition contains an updated version (2.0) of the indexes. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, or otherwise without the prior permission of the IMEMO. The terms country, power and nation as used in this book do not imply any judgment of the authors or the IMEMO concerning the legal status of any territory or the endorsement or acceptance of particular boundaries. The terms are used for research purposes only as maritime statistical data for a range of geographically self-contained economic areas are maintained on a separate and independent basis.
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Manson, Leigh, and Shona Muir. Advance care planning in New Zealand: our Voice—tō tātou reo. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198802136.003.0021.

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Advance care planning (ACP) in New Zealand has grown as a people’s movement resourced by passionate individuals across the country. This people’s movement is a whole of systems approach led by the national ACP Cooperative. The approach has provided a permissive platform for the national evolution of ACP and has allowed ACP to quickly gain momentum. It has facilitated the collaboration of multiple interest groups with consumers at the centre and has provided an environment for innovation. The ACP Cooperative used a deployment model to drive the work. The model insured that the movement focused on engaging healthcare leadership and the community, educating clinicians, and the public, whilst keeping the patient and their family/whānau values at the centre of the process. The Cooperative is acutely aware that providing patient value-based care for people as they approach the end of their lives sets the precedent for how all healthcare could be delivered.
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Stephens, Keri K. Mobile Workers in a Hospital. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190625504.003.0009.

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Hospitals are busy places, and healthcare professionals are literally always on the move. These mobile workers have challenging communication needs because they shift from being with patients and collaborating with peers to dictating and entering patient data into electronic healthcare records. As if being mobile and having many communication partners weren’t enough, these workers also have to worry about patient privacy and their high-stakes decisions. This chapter features a study of a hospital implementing a permissive BYOD policy and a mobile text-messaging app. It’s hard to develop trust when teams are constantly changing, something essential for successful mobile text messaging. Their devices serve to reinforce job-role status and hierarchy differences. Finally, some people don’t want to combine their private and work conversations on a personal mobile device, the stakes being simply too high. Control still exists at multiple levels in this organization, even though mobile use is encouraged.
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Clarke, Sandra, and Sarah Greer. Land Law Directions. Oxford University Press, 2018. http://dx.doi.org/10.1093/he/9780198809555.001.0001.

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Land Law Directions provides engaging and straightforward explanations of difficult concepts. Case summaries, photographs, and examples are used throughout to provide real-life context and to clarify abstract ideas, while diagrams and definitions ensure the text is easy to follow and that key points are understood. The book provides a full range of resources designed to help build upon and further existing understanding, including thinking points, end of chapter questions, and tips on linking topics together. A final chapter pulls together key details from each chapter, showing how topics link together and apply to a fictional piece of land. An additional separate chapter focuses on preparing for exams, offering advice on approaching assessment questions and revision technique. This edition includes a new chapter on proprietary estoppel, and consolidation of the law on land registration into one chapter (4). New cases covered include Regency Villas Title Ltd v Diamond Resorts (Europe) Ltd [2017] EWCA Civ 238; [2017] 2 P & CR DG8 (CA (Civ Div)) on rights of recreation as easements which pass with the land to each successive owner; Gore v Naheed & Ahmed [2017] EWCA Civ 369, which considered the old rule in Harris v Flower in relation to easements of way; Smith v Molyneaux [2016] UKPC 35 on unilateral permission/licences in adverse possession.
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Book chapters on the topic "APP PERMISSION"

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Mathur, Akshay, Ethan Ewoldt, Quamar Niyaz, Ahmad Javaid, and Xiaoli Yang. "Permission-Educator: App for Educating Users About Android Permissions." In Intelligent Human Computer Interaction, 361–71. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98404-5_34.

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Shen, Yidong, Ming Xu, Ning Zheng, Jian Xu, Wenjing Xia, Yiming Wu, Tong Qiao, and Tao Yang. "Android App Classification and Permission Usage Risk Assessment." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 567–77. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00916-8_52.

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Raber, Frederic, and Antonio Krueger. "Towards Understanding the Influence of Personality on Mobile App Permission Settings." In Human-Computer Interaction – INTERACT 2017, 62–82. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68059-0_4.

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Huang, Keman, Jinjing Han, Shizhan Chen, and Zhiyong Feng. "A Skewness-Based Framework for Mobile App Permission Recommendation and Risk Evaluation." In Service-Oriented Computing, 252–66. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46295-0_16.

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Huang, Hsiao-Ying, and Masooda Bashir. "Android App Permission and Users’ Adoption: A Case Study of Mental Health Application." In Human Aspects of Information Security, Privacy and Trust, 110–22. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58460-7_8.

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MacDuffie, Jason K., and Patricia A. Morreale. "Comparing Android App Permissions." In Design, User Experience, and Usability: Technological Contexts, 57–64. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40406-6_6.

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Schwarz, Torsten. "Grundlagen des Permission Marketing." In Das Handbuch Direct Marketing & More, 983–1005. Wiesbaden: Gabler Verlag, 2002. http://dx.doi.org/10.1007/978-3-322-90220-7_55.

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Bierhoff, Kevin, Nels E. Beckman, and Jonathan Aldrich. "Practical API Protocol Checking with Access Permissions." In Lecture Notes in Computer Science, 195–219. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03013-0_10.

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Sharma, Akanksha, and Subrat Kumar Dash. "Mining API Calls and Permissions for Android Malware Detection." In Cryptology and Network Security, 191–205. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12280-9_13.

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Chowdhury, Md Naseef-Ur-Rahman, Qudrat E. Alahy, and Hamdy Soliman. "Advanced Android Malware Detection Utilizing API Calls and Permissions." In Lecture Notes in Electrical Engineering, 123–34. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4118-3_12.

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Conference papers on the topic "APP PERMISSION"

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Rawal, Praveen Singh, and Divyashikha Sethia. "App Permission Classification dynamic Model(APCM)." In 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2023. http://dx.doi.org/10.1109/icccnt56998.2023.10307201.

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Li, Shanlin, Weiyi Jiang, Yongming Yao, and Chenyu Xu. "Permission analysis based on android app store." In International Conference on Cyber Security, Artificial Intelligence, and Digital Economy (CSAIDE 2023), edited by Pavel Loskot and Shaozhang Niu. SPIE, 2023. http://dx.doi.org/10.1117/12.2681726.

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Pan, Lanlan Pan, Ruonan Qiu, Zhenming Chen, Gen Li, Dian Wen, and Minghui Yang. "Enhance Calling Definition Security for Android Custom Permission." In 4th International Conference on Natural Language Processing and Machine Learning. Academy and Industry Research Collaboration Center (AIRCC), 2023. http://dx.doi.org/10.5121/csit.2023.130808.

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Custom permission is an important security feature of Android system. Permission resource app defines the custom permission. Resource provider app can share the app resources with the resource consumer apps which have gained the custom permission. However, evil app may potentially make permission squatting attacks, get ahead of legitimate permission source app to define the custom permission. If permission squatting attack is successful, then evil app can gain the access to the resource shared by resource provider app, and finally lead to security vulnerabilities and user data leakage. In this paper, we propose a scheme to provide permission source validation for the resource provider apps, which can enhance the calling context security for android custom permission, resistant to permission squatting attack, and suitable for app's self-protection.
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Liu, Xueqing, Yue Leng, Wei Yang, Chengxiang Zhai, and Tao Xie. "Mining Android App Descriptions for Permission Requirements Recommendation." In 2018 IEEE 26th International Requirements Engineering Conference (RE). IEEE, 2018. http://dx.doi.org/10.1109/re.2018.00024.

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Zeng, Huan, Yan Ren, Qing-Xian Wang, Neng-Qiang He, and Xu-Yang Ding. "Detecting malware and evaluating risk of app using Android permission-API system." In 2014 11th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). IEEE, 2014. http://dx.doi.org/10.1109/iccwamtip.2014.7073445.

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Hu, Xiaocao, and Hui Wang. "Category-Aware App Permission Recommendation based on Sparse Linear Model." In 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 2022. http://dx.doi.org/10.1109/compsac54236.2022.00133.

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Krutz, Daniel E., Nuthan Munaiah, Anthony Peruma, and Mohamed Wiem Mkaouer. "Who Added That Permission to My App? An Analysis of Developer Permission Changes in Open Source Android Apps." In 2017 IEEE/ACM 4th International Conference on Mobile Software Engineering and Systems (MOBILESoft). IEEE, 2017. http://dx.doi.org/10.1109/mobilesoft.2017.5.

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He, Yi, and Qi Li. "Detecting and defending against inter-app permission leaks in android apps." In 2016 IEEE 35th International Performance Computing and Communications Conference (IPCCC). IEEE, 2016. http://dx.doi.org/10.1109/pccc.2016.7820624.

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Mujahid, Suhaib. "Detecting wearable app permission mismatches: a case study on Android wear." In ESEC/FSE'17: Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3106237.3121279.

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Olukoya, Oluwafemi, Lewis Mackenzie, and Inah Omoronyia. "Permission-based Risk Signals for App Behaviour Characterization in Android Apps." In 5th International Conference on Information Systems Security and Privacy. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007248701830192.

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