Benjamin Zi Hao Zhao (University of New South Wales and Data61 CSIRO), Hassan Jameel Asghar (Macquarie University and Data61 CSIRO), Mohamed Ali Kaafar (Macquarie University and Data61 CSIRO)

We assess the security of machine learning based biometric authentication systems against an attacker who submits uniform random inputs, either as feature vectors or raw inputs, in order to find an emph{accepting sample} of a target user. The average false positive rate (FPR) of the system, i.e., the rate at which an impostor is incorrectly accepted as the legitimate user, may be interpreted as a measure of the success probability of such an attack. However, we show that the success rate is often higher than the FPR. In particular, for one reconstructed biometric system with an average FPR of 0.03, the success rate was as high as 0.78. This has implications for the security of the system, as an attacker with only the knowledge of the length of the feature space can impersonate the user with less than 2 attempts on average. We provide detailed analysis of why the attack is successful, and validate our results using four different biometric modalities and four different machine learning classifiers. Finally, we propose mitigation techniques that render such attacks ineffective, with little to no effect on the accuracy of the system.

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Learning-based Practical Smartphone Eavesdropping with Built-in Accelerometer

Zhongjie Ba (Zhejiang University and McGill University), Tianhang Zheng (University of Toronto), Xinyu Zhang (Zhejiang University), Zhan Qin (Zhejiang University), Baochun Li (University of Toronto), Xue Liu (McGill University), Kui Ren (Zhejiang University)

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Dynamic Searchable Encryption with Small Client Storage

Ioannis Demertzis (University of Maryland), Javad Ghareh Chamani (Hong Kong University of Science and Technology & Sharif University of Technology), Dimitrios Papadopoulos (Hong Kong University of Science and Technology), Charalampos Papamanthou (University of Maryland)

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IMP4GT: IMPersonation Attacks in 4G NeTworks

David Rupprecht (Ruhr University Bochum), Katharina Kohls (Ruhr University Bochum), Thorsten Holz (Ruhr University Bochum), Christina Poepper (NYU Abu Dhabi)

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Measuring the Deployment of Network Censorship Filters at Global...

Ram Sundara Raman (University of Michigan), Adrian Stoll (University of Michigan), Jakub Dalek (Citizen Lab, University of Toronto), Reethika Ramesh (University of Michigan), Will Scott (Independent), Roya Ensafi (University of Michigan)

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