Haohuang Wen (The Ohio State University), Phillip Porras (SRI International), Vinod Yegneswaran (SRI International), Ashish Gehani (SRI International), Zhiqiang Lin (The Ohio State University)

Over the past several years, the mobile security community has discovered a wide variety of exploits against link and session-establishment protocols. These exploits can be implemented on software-defined radios (SDRs) that disrupt, spoof, or flood layer-3 (L3) messages to compromise security and privacy, which still apply to the latest 5G mobile network standard. Interestingly, unlike the prior generations of closed (proprietary) mobile network infrastructures, 5G networks are migrating toward a more intelligent and open-standards-based fully interoperable mobile architecture, called Open RAN or O-RAN. The implications of transitioning mobile infrastructures to a software-defined architectural abstraction are quite significant to the INFOSEC community, as it allows us to extend the mobile data plane and control plane with security-focused protocol auditing services and exploit detection. Based on this design, we present 5G-SPECTOR, the first comprehensive framework for detecting the wide spectrum of L3 protocol exploits on O-RAN. It features a novel security audit stream called MOBIFLOW that transfers fine-grained cellular network telemetry, and a programmable control-plane xApp called MOBIEXPERT. We present an extensible prototype of 5G-SPECTOR which can detect 7 types of cellular attacks in real time. We also demonstrate its scalability to 11 unknown attacks as well as 31 real-world cellular traces, with effective performance (high accuracy, no false alarms) and low (<2% CPU, <100 MB memory) overhead.

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TextGuard: Provable Defense against Backdoor Attacks on Text Classification

Hengzhi Pei (UIUC), Jinyuan Jia (UIUC, Penn State), Wenbo Guo (UC Berkeley, Purdue University), Bo Li (UIUC), Dawn Song (UC Berkeley)

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EyeSeeIdentity: Exploring Natural Gaze Behaviour for Implicit User Identification...

L Yasmeen Abdrabou (Lancaster University), Mariam Hassib (Fortiss Research Institute of the Free State of Bavaria), Shuqin Hu (LMU Munich), Ken Pfeuffer (Aarhus University), Mohamed Khamis (University of Glasgow), Andreas Bulling (University of Stuttgart), Florian Alt (University of the Bundeswehr Munich)

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Aligning Confidential Computing with Cloud-native ML Platforms

Angelo Ruocco, Chris Porter, Claudio Carvalho, Daniele Buono, Derren Dunn, Hubertus Franke, James Bottomley, Marcio Silva, Mengmei Ye, Niteesh Dubey, Tobin Feldman-Fitzthum (IBM Research)

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