EDBT 2026 Demo / reviewers in the wild / expert
Mohammad Kavousi
dblp:305/3315
· DBLP profile ↗
3ranked-venue papers
1as first author
3since 2021 · last 2023
0000-0002-3378-2315ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 3 · 1 first-author · 3 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Full-stack vulnerability analysis of the cloud-native platform
Qingyang Zeng, Mohammad Kavousi, Yinhong Luo, Ling Jin 0005, Yan Chen 0004 |
Comput. Secur. | 2 |
| 2022 | RATScope: Recording and Reconstructing Missing RAT Semantic Behaviors for Forensic Analysis on WindowsabstractRemote Access Trojan (RAT) attacks have become an extensively prevailing and serious threat to enterprise security. A forensic system targeting RAT attacks is needed to record and reconstruct fine-grained semantic behaviors of RATs. However, existing forensic systems suffer from various issues such as intrusive instrumentation, nontrivial recording overhead, and RAT behavior blindness. In this article, we first conduct a large-scale study of a representative set of real-world RAT families active from 1999 to 2016. This is the first study to understand the landscape of RATs in the literature. Based on the study, we then proposeRATScope, an instrumentation-free RAT forensic system targeting Windows platform. Specifically,RATScopeoffers an audit logging module to efficiently record system logs by leveraging Event Tracing for Windows (ETW), and provides a novel program behavior modeling technique to reconstruct semantic behaviors of RATs accurately. We implement a prototype ofRATScopeand evaluate the recording overhead and the behavior identification accuracy. The results show that the audit logging module only incurs 3.7 percent runtime overhead on average. Our system can achieve around 90 percent true positive rate in the cross-family experiment, around 80 percent true positive rate in the two-year spanning temporal experiment, and nearzerofalse positive rate. Runqing Yang, Xutong Chen, Haitao Xu 0002, Yueqiang Cheng, Chun-lin Xiong, Linqi Ruan, Mohammad Kavousi, Zhenyuan Li, Liheng Xu, Yan Chen 0004 |
IEEE Trans. Dependable Secur. Comput. | 7 |
| 2021 | SemFlow: Accurate Semantic Identification from Low-Level System Data
Mohammad Kavousi, Runqing Yang, Shiqing Ma, Yan Chen 0004 |
SecureComm (1) | 1 |