VLDB 2026 Research / reviewers in the wild / expert
Eric K. T. Cheng
dblp:198/0911
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 2Systems, architecture and hardware · 1
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% | |
| Computer networks
1 paper |
Network measurement and analytics · 77% Cellular and mobile networks · 23% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Web and mobile security
mobile application security |
0.4 | 1 | 2019 | Understanding Open Ports in Android Applications: Discovery, Diagnosis, and Security Assessment · NDSS 2019 |
Network measurement and analytics › mobile network measurement
mobile network monitoring |
0.3 | 1 | 2017 | MopEye: Opportunistic Monitoring of Per-app Mobile Network Performance · USENIX ATC 2017 |
Web and mobile security › mobile security
android application security |
0.1 | 1 | 2019 | Understanding Open Ports in Android Applications: Discovery, Diagnosis, and Security Assessment · NDSS 2019 |
Cellular and mobile networks
mobile network performance |
0.1 | 1 | 2017 | MopEye: Opportunistic Monitoring of Per-app Mobile Network Performance · USENIX ATC 2017 |
Methods — techniques the papers use, named apart from their topics
static analysis · 0.4dynamic analysis · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Towards Understanding Android System Vulnerabilities: Techniques and InsightsabstractAs a common platform for pervasive devices, Android has been targeted by numerous attacks that exploit vulnerabilities in its apps and the operating system. Compared to app vulnerabilities, system-level vulnerabilities in Android, however, were much less explored in the literature. In this paper, we perform the first systematic study of Android system vulnerabilities by comprehensively analyzing all 2,179 vulnerabilities on the Android Security Bulletin program over about three years since its initiation in August 2015. To this end, we propose an automatic analysis framework, upon a hierarchical database structure, to crawl, parse, clean, and analyze vulnerability reports and their publicly available patches. This framework includes (i) a lightweight technique to pinpoint the affected modules of given vulnerabilities; (ii) a robust method to study the complexity of patch code; and most importantly, (iii) a similarity-based algorithm to cluster patch code patterns. Our clustering algorithm first extracts patch code's essential changes that not only concisely reflect syntactic changes but also keep important semantics, and then leverages affinity propagation to automatically generate clusters based on their pairwise similarity. It allows us to obtain 16 vulnerability patterns, including six new ones not known in the literature, and we further analyze their characteristics via case studies. Besides identifying these useful patterns, we also find that 92% Android vulnerabilities are located in the low-level modules (mostly in native libraries and the kernel), whereas the framework layer causes only 5% vulnerabilities, and that half of the vulnerabilities can be fixed in fewer than 10 lines of code each, with 110 out of 1,158 cases requiring only one single line of code change. We further discuss the implications of all these results. Overall, we provide a clear overview and new insights about Android system vulnerabilities. Daoyuan Wu, Debin Gao, Eric K. T. Cheng, Yichen Cao, Jintao Jiang, Robert H. Deng |
AsiaCCS | 3 |
| 2019 | Understanding Open Ports in Android Applications: Discovery, Diagnosis, and Security Assessment
Daoyuan Wu, Debin Gao, Rocky K. C. Chang, En He, Eric K. T. Cheng, Robert H. Deng |
NDSS | 5 |
| 2017 | MopEye: Opportunistic Monitoring of Per-app Mobile Network Performance
Daoyuan Wu, Rocky K. C. Chang, Weichao Li 0001, Eric K. T. Cheng, Debin Gao |
USENIX ATC | 4 |