Parinya Ekparinya (University of Sydney), Vincent Gramoli (University of Sydney and CSIRO-Data61), Guillaume Jourjon (CSIRO-Data61)

The vulnerability of traditional blockchains have been demonstrated at multiple occasions. Various companies are now moving towards Proof-of-Authority (PoA) blockchains with more conventional Byzantine fault tolerance, where a known set of n permissioned sealers, among which no more than t are Byzantine, seal blocks that include user transactions. Despite their wide adoption, these protocols were not proved correct.

In this paper, we present the Cloning Attack against the two mostly deployed PoA implementations of Ethereum, namely Aura and Clique. The Cloning Attack consists of one sealer cloning its pair of public-private keys into two distinct Ethereum instances that communicate with distinct groups of sealers. To identify their vulnerabilities, we first specify the corresponding algorithms. We then deploy one testnet for each protocol and demonstrate the success of the attack with only one Byzantine sealer. Finally, we propose counter-measures that prevent an adversary from double spending and introduce the necessary number of sealers needed to decide a block depending on n and t for both Aura and Clique to be safe.

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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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µRAI: Securing Embedded Systems with Return Address Integrity

Naif Saleh Almakhdhub (Purdue University and King Saud University), Abraham A. Clements (Sandia National Laboratories), Saurabh Bagchi (Purdue University), Mathias Payer (EPFL)

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Practical Traffic Analysis Attacks on Secure Messaging Applications

Alireza Bahramali (University of Massachusetts Amherst), Amir Houmansadr (University of Massachusetts Amherst), Ramin Soltani (University of Massachusetts Amherst), Dennis Goeckel (University of Massachusetts Amherst), Don Towsley (University of Massachusetts Amherst)

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BLAZE: Blazing Fast Privacy-Preserving Machine Learning

Arpita Patra (Indian Institute of Science, Bangalore), Ajith Suresh (Indian Institute of Science, Bangalore)

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