Comparative Analysis Of Privacy Settings And Battery Life Of Mobile Operating Systems

Objectives

Title: Comparison of some aspect of mobile phone performance or features

Mobile phone performance is defined as the efficient way a mobile phone works and how it is enjoyable to use for the users (Niya et al. 2018). Mobile phone performance is different for different users of mobile phones.

The researcher of this study shall be conducting a comparative analysis of privacy settings and battery life of mobile using qualitative and quantitative data

The main aim of this study is to compare the privacy settings and battery life of mobile Operating Systems such as Android, Windows, and Apple iOS.

The objectives of this study are as followings:

• To evaluate the privacy settings in Android, Windows, and iPhone.
• To compare the battery life of the Android phone, Windows phone and iPhone.
• To identify the best phone based on high privacy settings and the best battery life.

The objectives of the study shall be fulfilled using both quantitative and qualitative data, where quantitative data was gathered using an online survey, and qualitative data was gathered from recently published journal articles.

The hypothesis of this study is as followings:

• Null hypothesis: Privacy settings and battery life do not have a significant impact on the performance of mobile phones.
• Alternate hypothesis: Privacy settings and battery life have a significant impact on the performance of mobile phones.

As discussed by Ntonja and Ashawa (2020), there are numerous sensitive information stored in mobile phones that need to be protected from security threats, and the basic security cover is provided by the Operating Systems used in the device. The literature stated that mobile security is one of the top priorities of the users of smartphones.

According to Zhou et al. (2019), sharing current location is one of the top breaches capitalized by social engineers while breaching the privacy settings of a mobile phone. The literature stated that each Operating System (OS) used in mobile phones provides fundamental security coverage from the privacy settings. The literature stated that iOS provides maximum coverage to address the privacy concerns arising from sharing the current location.

 

Figure 1: Comparison of location protection

(Source: Zhou et al. 2019)

The literature stated that sharing current location using guest mode in Android is helping this OS to have better privacy settings in Android mobiles. Supporting the above discussion, Gerber et al. (2018), stated that multiple user settings could help protect sensitive information in Android devices. The prime strength of this literature is the conduction of a laboratory study and survey, which helped determine that the security cover of iOS is more than that of Android and Windows-based phones.

Even though, as Scoccia, Autili and Inverardi (2020), discussed, Android Flexible Permissions (AFP) approach is used in Android devices to regulate access to sensible APIs. AFP helps protect the sensitive information of users and helps them set feature-based permission for each data block. Considering the AFP server and AFP enforcer, the AFP architecture helps provide both levels-based and feature-based permission.  The overview of the AFP approach can be comprehended from the following illustration.

 

Figure 2: Overview of the AFP approach

(Source: Scoccia, Autili and Inverardi 2020)

The lack of critical analysis is the main drawback of this literature, and the detailed illustrations for supporting the discussions are the strength of this literature.

Based on the discussion of Leith (2021), it can be comprehended that Apple iOS have a Cydia substrate which helps in carrying out the SSL certificate. These certificates help protect the system from privacy concerns (Ataei, Degbelo and Kray 2018). On the other hand, Mitmproxy CA is the trusted certificate used by Android devices.

Hypothesis

Supporting the above argument, as Ataei, Degbelo and Kray (2018) discussed, sharing the current location is one reason behind privacy issues in mobile phones. The literature highlighted that Apple Corporation allows users to customize their privacy settings (Apple.com 2022). It can allow the users to customer the location sharing settings and disable the precise location setting so that the privacy of the users is ensured.

 

Figure 3: Privacy cover of iOS

(Source: Ataei, Degbelo and Kray 2018)

According to Ullah, Boreli and Kanhere (2020), the security vulnerabilities of iPhones are difficult to identify compared to Windows and Android phones. The literature stated that the integrated design of the Apple products helps then to address the security vulnerabilities unlike Windows phones. Apple phone supports NordVPN, and it helps them address the security threats coming from the third parties of a business setting. The literature stated that Apple encrypts its source codes, unlike Android mobile phones, which helps have a competitive edge over them.  The literature stated that the best security patches Apple is more effective than Android. On the other hand, the security cover of Android phones is restricted to two-factor authentication, enabling the automatic update of the latest security patches, hiding sensitive information from the lock screen, and blocking access to the mic and camera (Samsung 2022). The literature stated that the use of incognito mode could help the users to protect the sensitive data extracted from numerous data sources; however, there are numerous security loopholes in Android based mobile phones as it allows social engineers to have a look at the source code, which makes this OS more prone to hacking as compared to iOS and Windows.

Supporting the above discussion, there are numerous bugs in the security patches of Android; hence it is more susceptible to security flaws (Microsoft.com. 2022). The disk encryption method in Apple is more useful for this corporation to help their consumers protect sensitive data from their mobile devices. The literature stated that Apple Corporation created both software and hardware, whereas Microsoft Corporation works with different business brands; as a result, there are numerous security loopholes on their devices (Pramanik et al. 2019). A tracker is available on iPhones, which helps them track the destination and location of sensitive data. The literature stated that the security cover of iOS 14 beta helps maintain privacy by introducing an alert system whenever any suspicious activity can be identified. The prime strength of this literature is the detailed explanation of the security measures of the iPhone, and generalized discussion is the drawback of this literature (Duan, Liu and Huang 2019). The business model followed by Apple Corporation is much more innovative than the model followed by Microsoft and Google Corporation.

Sowmiya and Abinaya (2021), discussed that the battery life of Android devices has improved over the years; previously, shorter battery life was a concern for most Android users; however, this problem is now addressed. The literature stated that numerous factors directly impact the battery consumption in mobile phones, such as Bluetooth, Global Positioning System, and Near Field Communication systems. On the other hand, there is a battery saver mode in Android mobile systems that can help reduce battery consumption. However, it can be observed that the performance of the device gets depleted with the selection of battery saving mode. Goel, Ludin and Steiner (2020), stated that the clock speed of the CPU of Android phones is disrupted, screen brightness is lowered, limiting the use of Wi-Fi, disables power consuming location sharing settings, and reduces application background activity. This literature also stated that Android phones such as Samsung Galaxy S5, Samsung Galaxy S8, and Note 8 also do not provide any automatic power-saving mode; the entire battery-saving procedure needs to be done manually. As Saborido et al. (2018) discussed, famous Android mobile phones such as LG Nexus 4 have major battery life issues. However, the scholars of this literature helped comprehend that the deployment of SparseIntArray can help Android mobile phones improve their battery life. Thus, this literature indicated that there are numerous challenges confronted by Android users regarding the battery life of their mobile devices.

Comparison of Privacy Settings of Mobile Operating Systems

On the other hand, as Sun et al. (2019), argued, battery reliability and safety assurance provided by Apple Corporation is way better than that of Android and Windows-based mobile phones. The literature identified factors connected to reduced battery capacity in iPhones, such as low ambient temperature and high C rates. Performance decay and capacity fade are the major challenges to the battery life of Apple devices (Dunia, Rambe and Fauzi 2018). However, the efficiency of energy consumption of Apple devices is more than that of Android and Windows based mobile systems. This organization has battery replacements programs, unlike Google and Windows-based smartphones, which allows this organization to have a competitive edge. The literature stated that the iPhone 5s has battery concerns; hence Apple Corporation changed its battery suppliers. The manufacturing defects of the batteries were reduced significantly by this global business (He and Shin 2017). The chemical aging process of the battery of the iPhone is better than that of Android phones, as per the arguments of the scholars. Detailed description of the factors affecting the battery life of Apple mobile phones is the strength of this literature, and the lack of critical analysis of the discussions is the

On the other hand, as Tyhaar (2021), mentioned, the battery life of the iPhone 12 Pro max is the best globally, and the battery technology used in this global organization is helping them improve the consumer journey of the clients. The literature stated that Windows mobile phones such as Lumia 640 have lower battery life and are preferred only for the 2G network (Mahmud et al. 2017). The scholars highlighted that battery drainage is a concern in most Windows-based mobile phones. However, new Android-based business organizations such as POCO, Xiaomi, and Asus are working tirelessly in improve the battery life of their mobile devices. Generalised discussion is the drawback of this literature, and the improvement made by Android in recent times is the strength of this article. Based on the discussions of Kol, Zimand-Sheiner & Levy (2021), major global organizations like Apple Corporation make the most out of Expectancy Theory to understand and study consumer behavior. The literature stated that the deployment of this theory helps this organization to make all the necessary adjustments to the innovative products that this organization offers (Dave 2018). This theory helped the organization comprehend the need to change their suppliers who were providing faulty raw material while assembling the iPhone 5S.

Few areas were not covered in the literature analysis, such as the improvements made over the years by global mobile organizations for improving their privacy settings and battery life. The different categories of cyber-attacks which can be conducted by compromising the privacy settings of Android and Windows based mobile systems were not discussed in this literature. The literature failed to identify some of the best practices of the users of mobile devices, which can help them address the privacy concerns associated with the sensitive information stored in mobile phones. Detailed analysis of the battery life of the recent models on Android and Windows phones was also missing from the literature. Thus, it can be comprehended that a few areas were not discussed in this literature.  

Mobile Security of Different Operating Systems

The gaps in the secondary data were fulfilled by the researcher of this study with the conduction of primary research. The researcher conducted an online survey using a structured questionnaire created using the Likert scale. The questionnaire created for the participants has two segments, demographic questions for comprehending the personal information of the participants and quantitative questions for fulfilling the objectives of the study. Informed consent forms were provided to each participant before sending the questionnaire to get their legal permission to work on this study. The sample size of the survey was 50; each sample considered in this study used both Android and iPhones and has in-depth knowledge about the features provided by each of these mobile operating systems. Thus, it can be said that the researcher considered the probabilistic sampling method while selecting the online survey participants. There are numerous advantages associated with selecting this sampling technique, such as it helps in providing an unbiased representation of the total population of mobile phone users in the UK who have used different categories of mobile operating systems. Thus, systematic bias can be a drawback of conducting an online survey, which was successfully addressed with the selection of probabilistic sampling technique.

Demographic Questions

 

Figure 4: Gender

(Source: Created by author)

Findings and analysis

The above illustration helps comprehend that 46% of the online survey participants are male, 44% are female, and 10% have not disclosed their identities. Thus, it can be said that the researcher successfully addressed gender biasedness.

 

Figure 5: Age group

(Source: Created by author)

Findings and analysis

The above graph indicates the age group of the samples selected in this primary research, and it was identified that 56% are between 31to 45 years, 36% are between 18 to 30 years, and 8% are above 46 years. It can be observed that samples from different age groups participated in the online survey. Based on the findings, it can be analyzed that the researcher in this survey also avoided age-related biasedness.

Quantitative Questions 

 

Figure 6: Awareness

(Source: Created by author)

Findings and analysis

Awareness of the diverse categories of privacy concerns from the perspective of mobile phone users was identified from the graphical representation. It was identified that 36 knows, 7 do not know, and the remaining 7 cannot reveal their stand about the privacy concerns connected to Android and Windows-based phone. Thus, based on the findings, it can be analyzed that there are privacy concerns connected to Windows and Android phones. 

 

Figure 7: Sharing Current location

(Source: Created by author)

Findings and analysis

Opinions of participants about the cause of privacy issues can be comprehended from this graphical representation. 22 strongly agreed, 12 agreed, 4 strongly disagreed, 5 disagreed, and 7 remained neutral when asked if sharing current location leads to privacy issues in mobile systems. Based on the findings, it can be analyzed that out of 50 participants, 34 believe that sharing the current location in a mobile device can lead to privacy concerns in mobile OSs. 

 

Figure 8: iPhone security

(Source: Created by author)

Findings and analysis

Opinion of the samples regarding the security cover provided by Apple Corporation can be comprehended from the graph. 18 agreed, 14 strongly agreed, 3 strongly disagreed, 6 disagreed, and the remaining 9 stayed neutral when asked about the role of security cover provided by Apple Corporation to restrict the loss of sensitive information. Thus, the findings can assist in analyzing the security measures of iPhones, allowing their users to protect sensitive information from privacy concerns.

 

Figure 9: Drainage issue in iPhone

(Source: Created by author)

Findings and analysis

The challenges confronted by the participants to deal with low battery issues can be comprehended from this graphical representation. 23 strongly agreed, 14 disagreed, 6 strongly agreed, 2 agreed, and the remaining 5 stayed neutral when asked if they ever confronted any drainage issue on iPhone. Based on the findings, it can be analyzed that iPhones do not have any drainage issues, unlike Android and Windows based mobile systems. It can also be assumed that the participants who have agreed to this question might have used iPhone 5S, which had battery drainage concerns. 

 

Figure 10: Awareness of performance issue

(Source: Created by author)

Findings and analysis

This graph can comprehend the opinions of participants of a survey regarding the performance issue in Android phones, which is triggered due to the selection of power saving mode. 46 is aware, and 7 is not aware of this concern triggered by the selection of battery saving mode. Based on the findings, it can be analyzed that most participants believe that selecting battery saving mode can lead to performance issues in Android phones.  

 

Figure 11: Usefulness of battery replacement programs

(Source: Created by author)

Findings and analysis

The opinion of participants about the utility of battery replacement programs provided by Apple Corporation can be comprehended from the illustration. 18 strongly agreed, 16 agreed, 7 disagreed, 5 strongly disagreed, and 4 remained neutral when asked if battery replacement programs provided by Apple Corporation are helping them. Hence, based on the findings, it can be analyzed that consumers of Apple Corporation are happier due to their post delivery service. 

 

Figure 12: Usefulness of iPhone  

(Source: Created by author)

Findings and analysis

Opinions of participants on the usefulness of the iPhone in terms of better battery life and enhanced privacy settings can be comprehended from the above graph. 22 strongly agreed, 11 agreed, 3 disagreed, 8 strongly disagreed, and 6 remained neutral when asked about the competitiveness of the iPhone over Android and Windows phones.

Conclusion and Future Work 

The conduction of quantitative analysis and qualitative analysis was helpful in comprehending that Privacy Settings and Battery life are the two significant factors which has a significant impact on the performance of mobile phones. Hence, it can be said that this research was successful in proving the alternate hypothesis. The research helps in concluding that the battery life and privacy settings of iPhone is more superior as compared to Android and Windows based mobile phones. Based on the findings of the study, it can be concluded that battery replacement programs of Apple Corporation is proving them a competitive edge over Android and Windows mobile phones.

The recommendations which need to be considered by the users to mobile phones before buying a new smartphone is evaluating the probable screentime of the device.

Long-lasting battery: If multiple applications need to run simultaneously in the new phone, then iPhone can be bought as it makes the most out of Lithium Ion Technology, which has a higher density power, so it lasts longer (Novac et al. 2017).

Two prime limitations were confronted by the researcher while working on this mini-project such as the followings:

• Lack of sufficient time: It restricted the researcher in the data gathering procedure to gather primary data with a smaller sample size using an online survey, as it can be conducted quickly.
• Lack of sufficient budget: It restricted the research to MS Excel, an open source statistical that can be used for data analysis. However, the quality of data analysis could have been improved with the selection of SPSS, which has more efficiency than MS Excel.

The scope of improvements of this mini project are as followings:

• Data collection: Conduction of personal interviews can help the researcher comprehend more comparison into the processors, SD cards, and RAM used across the different mobile operating system types.
• Data analysis: The effectiveness of data analysis can be improved by selecting advanced statistical tools like SPSS. The quality of the outcome of this mini-project can be enhanced with the future scope of the study.

References

Apple (United Kingdom). 2022. Privacy. [online] Available at: <https://www.apple.com/uk/privacy/> [Accessed 6 April 2022].

Ataei, M., Degbelo, A. and Kray, C., 2018. Privacy theory in practice: designing a user interface for managing location privacy on mobile devices. Journal of Location Based Services, 12(3-4), pp.141-178.

Dave, J.G., 2018. A Case Study on Marketing Strategy: Apple i-Phone. IJRAR-International Journal of Research and Analytical Reviews (IJRAR), 5(4), pp.106-114.

Duan, Z., Liu, Y. and Huang, K., 2019, May. Mobile Phone Sales Forecast Based on Support Vector Machine. In Journal of Physics: Conference Series (Vol. 1229, No. 1, p. 012061). IOP Publishing.

Dunia, A.I.M., Rambe, A.H. and Fauzi, R., 2018, March. Measuring the power consumption of social media applications on a mobile device. In Journal of Physics: Conference Series (Vol. 978, No. 1, p. 012104). IOP Publishing. https://iopscience.iop.org/article/10.1088/1742-6596/978/1/012104/pdf

Gerber, N., Gerber, P., Drews, H., Kirchner, E., Schlegel, N., Schmidt, T. and Scholz, L., 2018, December. FoxIT: enhancing mobile users’ privacy behavior by increasing knowledge and awareness. In Proceedings of the 7th Workshop on Socio-Technical Aspects in Security and Trust (pp. 53-63). https://www.researchgate.net/profile/Nina-Gerber-2/publication/325924054_FoxIT_Enhancing_Mobile_Users%27_Privacy_Behavior_by_Increasing_Knowledge_and_Awareness/links/5b2cc8284585150d23c23bd4/FoxIT-Enhancing-Mobile-Users-Privacy-Behavior-by-Increasing-Knowledge-and-Awareness.pdf

Goel, U., Ludin, S. and Steiner, M., 2020. Web performance with Android’s battery-saver mode. arXiv preprint arXiv:2003.06477.

He, L. and Shin, K.G., 2017. How Long Will My Phone Battery Last?. arXiv preprint arXiv:1711.03651.

Kol, O., Zimand-Sheiner, D., & Levy, S. (2021). A (local) apple a day: pandemic-induced changes in local food buying, a generational cohort perspective.

Leith, D.J., 2021, September. Mobile Handset Privacy: Measuring The Data iOS and Android Send to Apple And Google. In International Conference on Security and Privacy in Communication Systems (pp. 231-251). Springer, Cham.

Mahmud, M.S., Wang, H., Esfar-E-Alam, A.M. and Fang, H., 2017. A wireless health monitoring system using mobile phone accessories. IEEE Internet of Things Journal, 4(6), pp.2009-2018.

Niya, S.R., Shüpfer, F., Bocek, T. and Stiller, B., 2018, April. Setting up flexible and light weight trading with enhanced user privacy using smart contracts. In NOMS 2018-2018 IEEE/IFIP Network Operations and Management Symposium (pp. 1-2). IEEE. https://www.researchgate.net/profile/Sina-Rafati-Niya/publication/324917551_Setting_up_Flexible_and_Light_Weight_Trading_Contracts_with_Enhanced_User_Privacy_Using_Smart_Contracts/links/5aeb04a3aca2725dabb66004/Setting-up-Flexible-and-Light-Weight-Trading-Contracts-with-Enhanced-User-Privacy-Using-Smart-Contracts.pdf

Novac, O.C., Novac, M., Gordan, C., Berczes, T. and Bujdosó, G., 2017, June. Comparative study of Google Android, Apple iOS and Microsoft Windows phone mobile operating systems. In 2017 14th international conference on engineering of modern electric systems (EMES) (pp. 154-159). IEEE.

Ntonja, M. and Ashawa, M., 2020. Examining artifacts generated by setting Facebook Messenger as a default SMS application on Android: Implication for personal data privacy. Security and Privacy, 3(6), p.e128. https://dspace.lib.cranfield.ac.uk/bitstream/handle/1826/16164/Examining_artifacts_generated_by_setting_Facebook_Messenger_as_a_default_SMS-2020.pdf?sequence=1&isAllowed=y

Pramanik, P.K.D., Sinhababu, N., Mukherjee, B., Padmanaban, S., Maity, A., Upadhyaya, B.K., Holm-Nielsen, J.B. and Choudhury, P., 2019. Power consumption analysis, measurement, management, and issues: A state-of-the-art review of smartphone battery and energy usage. IEEE Access, 7, pp.182113-182172. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8930492

Saborido, R., Morales, R., Khomh, F., Guéhéneuc, Y.G. and Antoniol, G., 2018. Getting the most from map data structures in Android. Empirical Software Engineering, 23(5), pp.2829-2864.

Samsung ca. 2022. Better protect your data privacy on your Galaxy phone. [online] Available at: <https://www.samsung.com/ca/support/mobile-devices/galaxy-phone-preserve-your-data-privacy/#:~:text=Your%20device%20comes%20with%20several,Settings%2C%20and%20then%20tap%20Privacy.> [Accessed 6 April 2022].

Scoccia, G.L., Autili, M. and Inverardi, P., 2020, August. A self-configuring and adaptive privacy-aware permission system for Android apps. In 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS) (pp. 38-47). IEEE. https://journals.riverpublishers.com/index.php/JCSANDM/article/view/5925/5561

Sowmiya, R. and Abinaya, S., NFC Enabled Wearable Device Connected With Android Smart Phone For Virtual Assistant Applications.

Sun, Y., Kong, L., Khan, H.A. and Pecht, M.G., 2019. Li-ion battery reliability–a case study of the apple iphone®. IEEE Access, 7, pp.71131-71141.

Support.microsoft.com. 2022. Change privacy settings in Windows. [online] Available at: <https://support.microsoft.com/en-gb/Windows/change-privacy-settings-in-Windows-55466b7b-14de-c230-3ece-6b75557c5227> [Accessed 6 April 2022].

Tyhaar, J.L., 2021. The continuous exploration of needs: sentiment feedback from Twitter for product innovation and improvement (at the example of the Apple iPhone) (Bachelor’s thesis, University of Twente).

Ullah, I., Boreli, R. and Kanhere, S.S., 2020. Privacy in targeted advertising: A survey. arXiv preprint arXiv:2009.06861. https://arxiv.org/pdf/2009.06861.pdf

Zhou, Y., Qi, L., Raake, A., Xu, T., Piekarska, M. and Zhang, X., 2019. User attitudes and behaviors toward personalized control of privacy settings on smartphones. Concurrency and Computation: Practice and Experience, 31(22), p.e4884.