Hui Lin (University of Nevada, Reno), Jianing Zhuang (University of Nevada, Reno), Yih-Chun Hu (University of Illinois, Urbana-Champaign), Huayu Zhou (University of Nevada, Reno)

Reconnaissance is critical for adversaries to prepare attacks causing physical damage in industrial control systems (ICS) like smart power grids. Disrupting the reconnaissance is challenging. The state-of-the-art moving target defense (MTD) techniques based on mimicking and simulating system behaviors do not consider the physical infrastructure of power grids and can be easily identified.

To overcome those challenges, we propose physical function virtualization (PFV) that ``hooks'' network interactions with real physical devices and uses them to build lightweight virtual nodes following the actual implementation of network stacks, system invariants, and physical state variations of real devices. On top of PFV, we propose DefRec, a defense mechanism that significantly increases the reconnaissance efforts for adversaries to obtain the knowledge of power grids' cyber-physical infrastructures. By randomizing communications and crafting decoy data for the virtual physical nodes, DefRec can mislead adversaries into designing damage-free attacks. We implement PFV and DefRec in the ONOS network operating system and evaluate them in a cyber-physical testbed, which uses real devices from different vendors and HP physical switches to simulate six power grids. The experiment results show that with negligible overhead, PFV can accurately follow the behavior of real devices. DefRec can significantly delay passive attacks for at least five months and isolate proactive attacks with less than $10^{-30}$ false negatives.

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Michael Schwarz (Graz University of Technology), Moritz Lipp (Graz University of Technology), Claudio Canella (Graz University of Technology), Robert Schilling (Graz University of Technology and Know-Center GmbH), Florian Kargl (Graz University of Technology), Daniel Gruss (Graz University of Technology)

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Matthew Smith (University of Oxford), Martin Strohmeier (University of Oxford), Jonathan Harman (Vrije Universiteit Amsterdam), Vincent Lenders (armasuisse Science and Technology), Ivan Martinovic (University of Oxford)

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ABSynthe: Automatic Blackbox Side-channel Synthesis on Commodity Microarchitectures

Ben Gras (Vrije Universiteit Amsterdam, Intel Corporation), Cristiano Giuffrida (Vrije Universiteit Amsterdam), Michael Kurth (Vrije Universiteit Amsterdam), Herbert Bos (Vrije Universiteit Amsterdam), Kaveh Razavi (Vrije Universiteit Amsterdam)

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Data-Driven Debugging for Functional Side Channels

Saeid Tizpaz-Niari (University of Colorado Boulder), Pavol Černý (TU Wien), Ashutosh Trivedi (University of Colorado Boulder)

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