Summary of In-application Defense Against Evasive Web Scans Through Behavioral Analysis, by Behzad Ousat et al.
In-Application Defense Against Evasive Web Scans through Behavioral Analysis
by Behzad Ousat, Mahshad Shariatnasab, Esteban Schafir, Farhad Shirani Chaharsooghi, Amin Kharraz
First submitted to arxiv on: 9 Dec 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Cryptography and Security (cs.CR); Information Theory (cs.IT)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary WebGuard is an in-application forensics engine designed to identify and monitor automated web scanners, mitigating security risks. The system focuses on low-overhead integration into web applications without modifying software components or infrastructure. WebGuard’s real-time detection capabilities, within hundreds of milliseconds, rely on multi-modal behavioral monitoring mechanisms, including spatio-temporal data and browser events. Supervised and unsupervised learning architectures are used for human and automated agent attribution. Information theoretic analysis shows that multi-modal data analysis improves time-to-detection and attribution accuracy compared to uni-modal analysis relying solely on mouse movement dynamics. Real-world evaluations using WebGuard-collected data demonstrate high accuracy in hundreds of milliseconds, with a communication overhead below 10 KB per second. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary WebGuard is an important tool for keeping the internet safe from bad actors like hackers. Right now, it’s hard to tell when someone or something is trying to hack into websites and steal passwords. WebGuard helps by watching what people do on websites and quickly identifying any suspicious behavior. It can even figure out who is behind the hacking attempt! This is super important because cybercrime costs billions of dollars every year. |
Keywords
» Artificial intelligence » Multi modal » Supervised » Unsupervised
