Kostas Drakonakis (FORTH), Sotiris Ioannidis (Technical University of Crete), Jason Polakis (University of Illinois at Chicago)

Black-box web vulnerability scanners are invaluable for security researchers and practitioners. Despite recent approaches tackling emph{some} of the inherent limitations of scanners, many have not sufficiently evolved alongside web browsers and applications, and often lack the capabilities for handling the inherent challenges of navigating and interacting with modern web applications. Instead of building an alternative scanner that could naturally only incorporate a limited set of the wide range of vulnerability-finding capabilities offered by the multitude of existing scanners, in this paper we propose an entirely different strategy. We present ReScan, a emph{scanner-agnostic} middleware framework that emph{transparently} enhances scanners' capabilities by mediating their interaction with web applications in a realistic and robust manner, using an orchestrated, fully-fledged modern browser. In essence, our framework can be used in conjunction with emph{any} vulnerability scanner, thus allowing users to benefit from the capabilities of existing and future scanners. Our extensible and modular framework includes a collection of enhancement techniques that address limitations and obstacles commonly faced by state-of-the-art scanners. Our experimental evaluation demonstrates that despite the considerable (and expected) overhead introduced by a fully-fledged browser, our framework significantly improves the code coverage achieved by popular scanners (168% on average), resulting in a 66% and 161% increase in the number of reflected and stored XSS vulnerabilities detected, respectively.

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Securing Federated Sensitive Topic Classification against Poisoning Attacks

Tianyue Chu (IMDEA Networks Institute), Alvaro Garcia-Recuero (IMDEA Networks Institute), Costas Iordanou (Cyprus University of Technology), Georgios Smaragdakis (TU Delft), Nikolaos Laoutaris (IMDEA Networks Institute)

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Anomaly Detection in the Open World: Normality Shift Detection,...

Dongqi Han (Tsinghua University), Zhiliang Wang (Tsinghua University), Wenqi Chen (Tsinghua University), Kai Wang (Tsinghua University), Rui Yu (Tsinghua University), Su Wang (Tsinghua University), Han Zhang (Tsinghua University), Zhihua Wang (State Grid Shanghai Municipal Electric Power Company), Minghui Jin (State Grid Shanghai Municipal Electric Power Company), Jiahai Yang (Tsinghua University), Xingang Shi (Tsinghua University), Xia…

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CANtropy: Time Series Feature Extraction-Based Intrusion Detection Systems for...

Md Hasan Shahriar, Wenjing Lou, Y. Thomas Hou (Virginia Polytechnic Institute and State University)

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