VLDB 2026 Research / reviewers in the wild / expert
Steven Wirsz
dblp:198/2004
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2024
0009-0000-5394-9760ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 2 · 2 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Deep Dive into Client-Side Anti-Phishing: A Longitudinal Study Bridging Academia and IndustryabstractClient-side anti-phishing methods are crucial for safeguarding individuals against phishing attacks, offering a proactive approach beyond traditional blocklisting strategies. This study expands the scope to include a comprehensive evaluation of client-side anti-phishing techniques within the Chrome browser, alongside an in-depth analysis of academic research in the field of phishing over the past five years. Our findings highlight the inherent limitations of current client-side anti-phishing measures, which demonstrated a detection rate of only 14% for phishing websites and blocked merely 10% of login-based phishing sites within the first hour, resulting in a substantial false negative rate. Additionally, our analysis reveals that attackers can readily circumvent these defenses by altering the content of phishing websites. The study also critically assesses recent academic contributions to understand their alignment and potential integration with client-side anti-phishing frameworks. Based on these insights, we propose targeted recommendations to enhance the efficacy and responsiveness of the client-side anti-phishing ecosystem, addressing the challenges of low detection coverage, slow response times, and high rates of false negatives. Rana Pourmohamad, Steven Wirsz, Adam Oest, Tiffany Bao, Yan Shoshitaishvili, Ruoyu Wang 0001, Adam Doupé, Rida A. Bazzi |
AsiaCCS | 2 |
| 2024 | Fuzz to the Future: Uncovering Occluded Future Vulnerabilities via Robust FuzzingabstractThe security landscape of software systems has witnessed considerable advancements through dynamic testing methodologies, especially fuzzing. Traditionally, fuzzing involves a sequential, cyclic process where software is tested to identify crashes. These crashes are then triaged and patched, leading to subsequent cycles that uncover further vulnerabilities. While effective, this method is not efficient as each cycle potentially reveals new issues previously obscured by earlier crashes, thus resulting in vulnerabilities being discovered sequentially. Arvind S. Raj, Wil Gibbs, Fangzhou Dong, Jayakrishna Vadayath, Michael Tompkins, Steven Wirsz, Zhenghao Hu, Gokulkrishna Praveen Menon, Brendan Dolan-Gavitt, Adam Doupé, Ruoyu Wang 0001, Yan Shoshitaishvili, Tiffany Bao |
CCS | 6 |