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- Publisher Website: 10.1007/978-3-319-69659-1_16
- Scopus: eid_2-s2.0-85035148802
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Conference Paper: Harvesting Smartphone Privacy Through Enhanced Juice Filming Charging Attacks
Title | Harvesting Smartphone Privacy Through Enhanced Juice Filming Charging Attacks |
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Authors | |
Keywords | OCR technology Android and iOS Charging threat Juice filming charging attack Mobile privacy and security |
Issue Date | 2017 |
Citation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, v. 10599 LNCS, p. 291-308 How to Cite? |
Abstract | © 2017, Springer International Publishing AG. The increasingly high demand for smartphone charging in people’s daily lives has apparently encouraged much more public charging stations to be deployed in various places (e.g., shopping malls, airports). However, these public charging facilities may open a hole for cyber-criminals to infer private information and data from smartphone users. Juice filming charging (JFC) attack is a particular type of charging attacks, which is capable of stealing users’ sensitive information from both Android OS and iOS devices, through automatically monitoring and recording phone screen during the whole charging period. The rationale is that phone screen can be leaked through a standard micro USB connector, which adopts the Mobile High-Definition Link (MHL) standard. In practice, we identify that how to efficiently extract information from the captured videos remains a challenge for current JFC attack. To further investigate its practical influence, in this work, we focus on enhancing its performance in the aspects of extracting texts from images and correlating information, and then conducting a user study in a practical scenario. The obtained results demonstrate that our enhanced JFC attack can outperform the original one in collecting users’ information at large and extracting sensitive data with a higher accuracy. Our work aims to complement existing results and stimulate more efforts in defending smartphones against charging threats. |
Persistent Identifier | http://hdl.handle.net/10722/280859 |
ISSN | 2023 SCImago Journal Rankings: 0.606 |
DC Field | Value | Language |
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dc.contributor.author | Meng, Weizhi | - |
dc.contributor.author | Fei, Fei | - |
dc.contributor.author | Li, Wenjuan | - |
dc.contributor.author | Au, Man Ho | - |
dc.date.accessioned | 2020-02-17T14:35:07Z | - |
dc.date.available | 2020-02-17T14:35:07Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017, v. 10599 LNCS, p. 291-308 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | http://hdl.handle.net/10722/280859 | - |
dc.description.abstract | © 2017, Springer International Publishing AG. The increasingly high demand for smartphone charging in people’s daily lives has apparently encouraged much more public charging stations to be deployed in various places (e.g., shopping malls, airports). However, these public charging facilities may open a hole for cyber-criminals to infer private information and data from smartphone users. Juice filming charging (JFC) attack is a particular type of charging attacks, which is capable of stealing users’ sensitive information from both Android OS and iOS devices, through automatically monitoring and recording phone screen during the whole charging period. The rationale is that phone screen can be leaked through a standard micro USB connector, which adopts the Mobile High-Definition Link (MHL) standard. In practice, we identify that how to efficiently extract information from the captured videos remains a challenge for current JFC attack. To further investigate its practical influence, in this work, we focus on enhancing its performance in the aspects of extracting texts from images and correlating information, and then conducting a user study in a practical scenario. The obtained results demonstrate that our enhanced JFC attack can outperform the original one in collecting users’ information at large and extracting sensitive data with a higher accuracy. Our work aims to complement existing results and stimulate more efforts in defending smartphones against charging threats. | - |
dc.language | eng | - |
dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.subject | OCR technology | - |
dc.subject | Android and iOS | - |
dc.subject | Charging threat | - |
dc.subject | Juice filming charging attack | - |
dc.subject | Mobile privacy and security | - |
dc.title | Harvesting Smartphone Privacy Through Enhanced Juice Filming Charging Attacks | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/978-3-319-69659-1_16 | - |
dc.identifier.scopus | eid_2-s2.0-85035148802 | - |
dc.identifier.volume | 10599 LNCS | - |
dc.identifier.spage | 291 | - |
dc.identifier.epage | 308 | - |
dc.identifier.eissn | 1611-3349 | - |
dc.identifier.issnl | 0302-9743 | - |