A Review and Survey on Smartphones: The Closest Enemy to Privacy (original) (raw)

Evaluating the Data Privacy of Mobile

2020

Consumers are largely unaware regarding the use being made to the data that they generate through smart devices, or their GDPR-compliance, since such information is typically hidden behind vague privacy policy documents, which are often lengthy, difficult to read (containing legal terms and definitions) and frequently changing. This paper describes the activities of the CAP-A project, whose aim is to apply crowdsourcing techniques to evaluate the privacy friendliness of apps, and to allow users to better understand the content of Privacy Policy documents and, consequently, the privacy implications of using any given mobile app. To achieve this, we developed a set of tools that aim at assisting users to express their own privacy concerns and expectations and assess the mobile apps’ privacy properties through collective intelligence.

Survey on Mobile User's Data Privacy Threats and Defense Mechanisms

Nowadays, mobile devices have become an integral part of our daily life. These have proven to be an advantageous scientific invention that fills personal and business needs in a very efficient manner. In this era, the availability of mobile services has significantly increased because of the rich variety of mobile devices and essential applications provided by mobile device manufacturers. At the same time, numerous mobile security issues and data privacy threats are challenging both manufacturers and users. Therefore, mobile devices are an ideal target for various security issues and data privacy threats in a mobile ecosystem. In this paper, we provide a brief survey of the security challenges, threats, and vulnerabilities of a mobile ecosystem. Furthermore, we discussed some key points required to ensure mobile security and defend against data privacy threats. The emphasis of the discussion is, strong protection and the restriction of malicious activity at the application developer end, application stores end, and operating system and mobile device manufactures end by preventing the user from using non-recommended applications (which may be malicious) and considering biometric features for the authentication of real users in the mobile devices. Also briefly discussing the defense mechanisms that are considered to be a relatively better approach for securing personal and business related data or information in the mobile devices.

SoK: Privacy on Mobile Devices – It’s Complicated

Proceedings on Privacy Enhancing Technologies, 2016

Modern mobile devices place a wide variety of sensors and services within the personal space of their users. As a result, these devices are capable of transparently monitoring many sensitive aspects of these users’ lives (e.g., location, health, or correspondences). Users typically trade access to this data for convenient applications and features, in many cases without a full appreciation of the nature and extent of the information that they are exposing to a variety of third parties. Nevertheless, studies show that users remain concerned about their privacy and vendors have similarly been increasing their utilization of privacy-preserving technologies in these devices. Still, despite significant efforts, these technologies continue to fail in fundamental ways, leaving users’ private data exposed.In this work, we survey the numerous components of mobile devices, giving particular attention to those that collect, process, or protect users’ private data. Whereas the individual compon...

Privacy in a World of Mobile Devices

2014

Our individual privacy is increasingly at risk in a world full of smart mobile devices. The situation will only get worse with the rise of an Internet of Things. One way to address this problem is through the use of systems that better understand their context and and whose information gathering and sharing behaviors can be controlled or influenced by context-aware policies. We illustrate the the problem and an approach to address it through recent work on FaceBlock, a project that protects the privacy of people around Google Glass users by making pictures taken by the latter, Privacy-Aware. Through sharing of privacy policies, users can choose whether or not to be included in pictures.

Snooping on Mobile Phones: Prevalence and Trends

2016

Personal mobile devices keep private information which people other than the owner may try to access. Thus far, it has been unclear how common it is for people to snoop on one another's devices. Through an anonymity-preserving survey experiment, we quantify the pervasiveness of snooping attacks, defined as "looking through someone else's phone without their permission." We estimated the 1-year prevalence to be 31% in an online participant pool. Weighted to the U.S. population, the data indicates that 1 in 5 adults snooped on at least one other person's phone, just in the year before the survey was conducted. We found snooping attacks to be especially prevalent among young people, and among those who are themselves smartphone users. In a follow-up study, we found that, among smartphone users, depth of adoption, like age, also predicts the probability of engaging in snooping attacks. In particular, the more people use their devices for personal purposes, the more...