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Luman Shi

dblp:243/0114 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2020
—ORCID · none

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

Computer networks · 1 · 1 first-authorSecurity and privacy · 1 · 1 first-author

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
2 papers
Malware analysis · 38% Systems and software security · 35% Web and mobile security · 26%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Malware analysis
android malware
0.412020
VAHunt: Warding Off New Repackaged Android Malware in App-Virtualization's Clothing · CCS 2020
Web and mobile security › mobile security
android security
0.412019
"Jekyll and Hyde" is Risky: Shared-Everything Threat Mitigation in Dual-Instance Apps · MobiSys 2019
Malware analysis
malware detection
0.112019
"Jekyll and Hyde" is Risky: Shared-Everything Threat Mitigation in Dual-Instance Apps · MobiSys 2019

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

fingerprinting · 0.4
YearPublicationVenuePosition
2020 VAHunt: Warding Off New Repackaged Android Malware in App-Virtualization's Clothing
abstract
Repackaging popular benign apps with malicious payload used to be the most common way to spread Android malware. Nevertheless, since 2016, we have observed an alarming new trend to Android ecosystem: a growing number of Android malware samples abuse recent app-virtualization innovation as a new distribution channel. App-virtualization enables a user to run multiple copies of the same app on a single device, and tens of millions of users are enjoying this convenience. However, cybercriminals repackage various malicious APK files as plugins into an app-virtualization platform, which is flexible to launch arbitrary plugins without the hassle of installation. This new style of repackaging gains the ability to bypass anti-malware scanners by hiding the grafted malicious payload in plugins, and it also defies the basic premise embodied by existing repackaged app detection solutions.
Luman Shi, Jiang Ming 0002, Jianming Fu, Guojun Peng, Dongpeng Xu 0001, Xuanchen Pan
CCS1
2019 "Jekyll and Hyde" is Risky: Shared-Everything Threat Mitigation in Dual-Instance Apps
abstract
Recent developed application-level virtualization brings a groundbreaking innovation to Android ecosystem: a host app is able to load and launch arbitrary guest APK files without the hassle of installation. Powered by this technology, the so-called "dual-instance apps" are becoming increasingly popular as they can run dual copies of the same app on a single device (e.g., login Facebook simultaneously with two different accounts). Given the large demand from smartphone users, it is imperative to understand how secure dual-instance apps are. However, little work investigates their potential security risks. Even worse, new Android malware variants have been accused of skimming the cream off application-level virtualization. They abuse legitimate virtualization engines to launch phishing attacks or even thwart static detection. We first demonstrate that, current dual-instance apps design introduces serious "shared-everything" threats to users, and severe attacks such as permission escalation and privacy leak have become tremendously easier. Unfortunately, we find that most critical apps cannot discriminate between host app and Android system. In addition, traditional fingerprinting features targeting Android sandboxes are futile as well. To inform users that an app is running in an untrusted environment, we study the inherent features of dual-instance app environment and propose six robust fingerprinting features to detect whether an app is being launched by the host app. We test our approach, called DiPrint, with a set of dual-instance apps collected from popular app stores, Android systems, and virtualization-based malware. Our evaluation shows that DiPrint is able to accurately identify dual-instance apps with negligible overhead.
Luman Shi, Jianming Fu, Zhengwei Guo, Jiang Ming 0002
MobiSys1