File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: SenDroid: Auditing Sensor Access in Android System-Wide

TitleSenDroid: Auditing Sensor Access in Android System-Wide
Authors
KeywordsAndroid security
audit
hooking
senDroid
sensor
Issue Date2020
Citation
IEEE Transactions on Dependable and Secure Computing, 2020, v. 17, n. 2, p. 407-421 How to Cite?
AbstractSensors are widely used in modern mobile devices (e.g., smartphones, watches) and may gather abundant information from environments as well as about users, e.g., photos, sounds and locations. The rich set of sensor data enables various applications (e.g., health monitoring) and personalized apps as well. However, the powerful sensing abilities provide opportunities for attackers to steal both personal sensitive data and commercial secrets like never before. Unfortunately, the current design of smart devices only provides a coarse access control on sensors and does not have the capability to audit sensing. We argue that knowing how often the sensors are accessed and how much sensor data are collected is the first-line defense against sensor data breach. Such an ability is yet to be designed. In this paper, we propose a framework that allows users to acquire sensor data usages. In particular, we leverage a hook-based track method to track sensor accesses. Thus, with no need to change the source codes of the Android system and applications, we can intercept sensing operations to graphic sensors, audio sensors, location sensors, and standard sensors, and audit them from four aspects: flow audit, frequency audit, duration audit and invoker audit. Then, we implement a prototype, referred to as senDroid, which visually shows the quantitative usages of these sensors in real time at a performance overhead of [0.04-8.05] percent. senDroid allows Android users to audit the applications even when they bypass the Android framework via JNI invocations or when the malicious codes are dynamically loaded from the server side. Our empirical study on 1,489 popular apps in three well-known Android app markets shows that 26.32 percent apps access sensors when the apps are launched, and 11.01 percent apps access sensors while the apps run in the background. Furthermore, we analyze the relevance between sensor usage patterns and third-party libraries, and reverse-engineering on suspicious third-party libraries shows that 77.27 percent apps access sensors via third-party libraries. Our results call attentions to address the users' privacy concerns caused by sensor access.
Persistent Identifierhttp://hdl.handle.net/10722/346654
ISSN
2023 Impact Factor: 7.0
2023 SCImago Journal Rankings: 2.222

 

DC FieldValueLanguage
dc.contributor.authorHan, Weili-
dc.contributor.authorCao, Chang-
dc.contributor.authorChen, Hao-
dc.contributor.authorLi, Dong-
dc.contributor.authorFang, Zheran-
dc.contributor.authorXu, Wenyuan-
dc.contributor.authorWang, X. Sean-
dc.date.accessioned2024-09-17T04:12:21Z-
dc.date.available2024-09-17T04:12:21Z-
dc.date.issued2020-
dc.identifier.citationIEEE Transactions on Dependable and Secure Computing, 2020, v. 17, n. 2, p. 407-421-
dc.identifier.issn1545-5971-
dc.identifier.urihttp://hdl.handle.net/10722/346654-
dc.description.abstractSensors are widely used in modern mobile devices (e.g., smartphones, watches) and may gather abundant information from environments as well as about users, e.g., photos, sounds and locations. The rich set of sensor data enables various applications (e.g., health monitoring) and personalized apps as well. However, the powerful sensing abilities provide opportunities for attackers to steal both personal sensitive data and commercial secrets like never before. Unfortunately, the current design of smart devices only provides a coarse access control on sensors and does not have the capability to audit sensing. We argue that knowing how often the sensors are accessed and how much sensor data are collected is the first-line defense against sensor data breach. Such an ability is yet to be designed. In this paper, we propose a framework that allows users to acquire sensor data usages. In particular, we leverage a hook-based track method to track sensor accesses. Thus, with no need to change the source codes of the Android system and applications, we can intercept sensing operations to graphic sensors, audio sensors, location sensors, and standard sensors, and audit them from four aspects: flow audit, frequency audit, duration audit and invoker audit. Then, we implement a prototype, referred to as senDroid, which visually shows the quantitative usages of these sensors in real time at a performance overhead of [0.04-8.05] percent. senDroid allows Android users to audit the applications even when they bypass the Android framework via JNI invocations or when the malicious codes are dynamically loaded from the server side. Our empirical study on 1,489 popular apps in three well-known Android app markets shows that 26.32 percent apps access sensors when the apps are launched, and 11.01 percent apps access sensors while the apps run in the background. Furthermore, we analyze the relevance between sensor usage patterns and third-party libraries, and reverse-engineering on suspicious third-party libraries shows that 77.27 percent apps access sensors via third-party libraries. Our results call attentions to address the users' privacy concerns caused by sensor access.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Dependable and Secure Computing-
dc.subjectAndroid security-
dc.subjectaudit-
dc.subjecthooking-
dc.subjectsenDroid-
dc.subjectsensor-
dc.titleSenDroid: Auditing Sensor Access in Android System-Wide-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TDSC.2017.2768536-
dc.identifier.scopuseid_2-s2.0-85032810346-
dc.identifier.volume17-
dc.identifier.issue2-
dc.identifier.spage407-
dc.identifier.epage421-
dc.identifier.eissn1941-0018-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats