# mPrivacy: A Privacy Policy Engine and Safeguard Mechanism in Mobile Devices
###### Abstract  
Within the scope of mobile privacy, there are many attack methods that can leak users' private information. The communication between applications can be used to violate permissions and access private information without asking for the user's authorization. Hence, many researchers made protection mechanisms against privilege escalation. However, attackers can further utilize inference algorithms to derive new information out of available data or improve the information quality without violating privilege limits. In this work. we describe the notion of Information Escalation Attack and propose a detection and protection mechanism using Inference Graph and Policy Engine for the user to control their policy on the App's privilege in information escalation. Our implementation results show that the proposed privacy protection service is feasible and provides good useability. mobile privacy; privacy protection mechanism; information escalation; inference algorithm +
Footnote †: 10: 2021: 11629. [[https://doi.org/10.3390/app112411629](https://doi.org/10.3390/app112411629)]([https://doi.org/10.3390/app112411629](https://doi.org/10.3390/app112411629))  
Footnote †: 10: 2021: 11629. [[https://doi.org/10.3390/app11241629](https://doi.org/10.3390/app11241629)]([https://doi.org/10.3390/app11241629](https://doi.org/10.3390/app11241629))  
Footnote †: 10: 2021: 11629. [[https://doi.org/10.3390/app112411629](https://doi.org/10.3390/app112411629)]([https://doi.org/10.3390/app112411629](https://doi.org/10.3390/app112411629))
To protect the user's privacy, the device platform controls the permissions of the application to the resources in the device, and only authorized applications can access the allowed resources. Whether the access control is dynamic or not, attackers can still circumvent the permission mechanism by communicating with other applications with different permission sets. The attackers can use _colluding_[16; 17] or _confused deputy_ attacks [18; 19]. By _colluding_, the attackers can collude with other malicious applications. By _confused deputy_, the attackers can leverage legitimate interactions with a benign application. In the literature, this is called a privilege escalation attack. Furthermore, attackers can increase the accuracy of private information available to themselves by increasing the number of samples from sensors. This _inference attack_[10] leaks more information than is allowed to the attacker, and does not necessarily violate the access permission policy. In order to model all such permissions-based attacks along with inference-based attacks, we define _information escalation attack_ as an attack in which the attacker can gain more or higher quality information than they are allowed to possess. Researchers have made efforts on privacy mechanisms, allowing or prohibiting access when an application violates the privacy policy. However, we believe that privacy is not an issue of access control, but more an information control issue. To compromise privacy and utility, privacy policies that intentionally limit the amount or quality of information disclosed to third parties could provide benefits to both the users and service providers. This kind of privacy policy could be better than inflexible access control policies. In order to develop this privacy mechanism, we systematically designed privacy policies and execution mechanisms for information escalation attacks. In this paper, our contribution can be summarized as follows:  
* Defined a generic privacy attack model called information escalation attack. * Proposed a novel privacy-policy model based on the inference graph. * We designed our privacy-policy engine based on Android systems. * We designed and implemented one location escalation attack. * We tested our system with a designed location escalation attack. The rest of this work is structured as follows: Section 2 is about related works. Section 3 describes the privacy problem in the mobile device and introduces the concept of information escalation attack.