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Han Yan 0013

dblp:63/49-13 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0003-2571-6470ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Web and mobile security · 100%
Software engineering, system software, and programming languages
1 paper
Operating systems · 50% Software testing · 50%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Web and mobile security › mobile security
android security
0.512021
App's Auto-Login Function Security Testing via Android OS-Level Virtualization · ICSE 2021
Web and mobile security
mobile security
0.512021
App's Auto-Login Function Security Testing via Android OS-Level Virtualization · ICSE 2021
Operating systems › virtualization
OS-level virtualization
0.112021
App's Auto-Login Function Security Testing via Android OS-Level Virtualization · ICSE 2021
Software testing › non-functional testing
security testing
0.112021
App's Auto-Login Function Security Testing via Android OS-Level Virtualization · ICSE 2021

Methods — techniques the papers use, named apart from their topics

device fingerprint simulation · 1.0OS-level virtualization · 1.0
YearPublicationVenuePosition
2021 App's Auto-Login Function Security Testing via Android OS-Level Virtualization
abstract
Limited by the small keyboard, most mobile apps support the automatic login feature for better user experience. Therefore, users avoid the inconvenience of retyping their ID and password when an app runs in the foreground again. However, this auto-login function can be exploited to launch the so-called "data-clone attack": once the locally-stored, auto-login depended data are cloned by attackers and placed into their own smartphones, attackers can break through the login-device number limit and log in to the victim's account stealthily. A natural countermeasure is to check the consistency of device-specific attributes. As long as the new device shows different device fingerprints with the previous one, the app will disable the auto-login function and thus prevent data-clone attacks. In this paper, we develop VPDroid, a transparent Android OS-level virtualization platform tailored for security testing. With VPDroid, security analysts can customize different device artifacts, such as CPU model, Android ID, and phone number, in a virtual phone without user-level API hooking. VPDroid's isolation mechanism ensures that user-mode apps in the virtual phone cannot detect device-specific discrepancies. To assess Android apps' susceptibility to the data-clone attack, we use VPDroid to simulate data-clone attacks with 234 most-downloaded apps. Our experiments on five different virtual phone environments show that VPDroid's device attribute customization can deceive all tested apps that perform device-consistency checks, such as Twitter, WeChat, and PayPal. 19 vendors have confirmed our report as a zero-day vulnerability. Our findings paint a cautionary tale: only enforcing a device-consistency check at client side is still vulnerable to an advanced data-clone attack.
Wenna Song, Jiang Ming 0002, Han Yan 0013, Jianming Fu, Guojun Peng
ICSE4