Demo Data from EDBT 2026 / reviewers in the wild / expert
Jiayuan Xin
dblp:392/3387
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0007-0905-1604ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 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 |
Network security · 50% Systems and software security · 50% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Network security › intrusion detection and prevention › intrusion detection › malicious traffic detection
web attack detection |
0.8 | 1 | 2024 | SWIDE: A Semantic-aware Detection Engine for Successful Web Injection Attacks · CCS 2024 |
Methods — techniques the papers use, named apart from their topics
syntactic analysis · 0.8semantic analysis · 0.8obfuscation detection · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | SWIDE: A Semantic-aware Detection Engine for Successful Web Injection AttacksabstractWeb attacks, a primary vector for system breaches, pose a significant challenge within the cybersecurity landscape. The growing intensity of web attack attempts has led to "alert fatigue" where enterprises are inundated by excessive alerts. Although extensive research is being conducted on automated methods for detecting web attacks, it remains an open problem to identify whether the attacks are successful. Towards this end, we present SWIDE (Successful Web Injection Detection Engine), an engine to pinpoint successful web injection attacks (e.g., PHP command injection, SQL injection). This enables enterprises to focus exclusively on those crucial threats. Our methodology builds on two insights: Firstly, while attackers tend to apply payload obfuscation techniques to evade detection, all successful web injection attacks must comply with the programming language syntax to be executable; Secondly, these attacks inevitably produce observable effects, such as returning execution result or creating backdoors for future access by the attacker. Consequently, we leverage advanced syntactic and semantic analysis to 1) detect malicious syntax features in obfuscated payloads and 2) perform semantic analysis of the payload to recover the intention of the attack. With a two-stage design, namely, attack identification and confirmation mechanisms, SWIDE can accurately identify successful attacks, even amidst intricate obfuscations. Unlike proof-of-concept studies, SWIDE has been deployed and validated in real-world environments through collaborations with a cybersecurity firm. Serving 5,045 enterprise users, our system identifies that roughly 15% of enterprises have suffered from successful attacks on a weekly basis - an alarmingly high rate. Moreover, we perform a detailed analysis of six months' data and discover 60 zero-day vulnerabilities exploited in the wild, including 12 high-risk ones acknowledged by relevant authorities. These findings underscore the practical effectiveness of SWIDE. Ronghai Yang, Xianbo Wang, Kaixuan Luo, Jiayuan Xin, Wing Cheong Lau |
CCS | 6 |