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We search for a candidate with a strong background in practical system level security. The candidate is expected to support supervision of PhD students, contribute to our on-going projects, and also contribute to future project proposals to strengthen our research profile. Our group is member of multiple national and European research projects with strong links to industry. One example is the currently ongoing CRISALIS FP7 project (http://www.crisalisproject.eu/).
Successful candidates must hold a PhD degree in computer science or a closely related discipline and have demonstrated their excellence by top-class publications.
Please submit your application via the link provided below including:
The position will be closed as soon as a suitable candidate is found.
operations in lattice cryptography, namely, generating a hard lattice
$\\Lambda$ together with a ``strong\'\' trapdoor, and sampling from a
discrete Gaussian distribution over a desired coset of $\\Lambda$ using
the trapdoor. These are the central operations of many cryptographic
schemes: for example, they are exactly the key-generation and signing
operations (respectively) for the GPV signature scheme, and they are
the public parameter generation and private key extraction operations
(respectively) for the GPV IBE. We also provide a protocol for
trapdoor delegation, which is used in lattice-based hierarchical IBE
schemes. Our work therefore directly transfers all these systems to
the threshold setting.
Our protocols provide information-theoretic (i.e., statistical)
security against adaptive corruptions in the UC framework, and they
are private and robust against an
optimal number of semi-honest or malicious parties. Our Gaussian
sampling protocol is both noninteractive and efficient, assuming
either a trusted setup phase (e.g., performed as part of key
generation) or a sufficient amount of interactive but offline
precomputation, which can be performed before the inputs to the
sampling phase are known.
We introduce a new score function for non-binary bias-based traitor tracing. It has three special properties that have long been sought after:
(i) The expected score of an innocent user is zero in each content position.
(ii) The variance of an innocent user\'s score is~1 in each content position.
(iii) The expectation of the coalition\'s score does not depend on the
We also find a continuous bias distribution that optimizes the asymptotic (large coalition) performance.
In the case of a binary alphabet our scheme reduces exactly to the
symmetrized Tardos traitor tracing system.
Unfortunately, the asymptotic fingerprinting rate
of our new scheme decreases with growing alphabet size.
We regret to inform you that this grail has holes.