Re: [pl-seminar] Tomorrow's talk


Date: Mon, 24 Apr 2017 16:51:30 +0000
From: Qinheping HU <qhu28@xxxxxxxx>
Subject: Re: [pl-seminar] Tomorrow's talk

Reminder: talk in 10 minutes.


From: Pl-seminar <pl-seminar-bounces@xxxxxxxxxxx> on behalf of Qinheping HU <qhu28@xxxxxxxx>
Sent: Sunday, April 23, 2017 11:51:35 PM
To: pl-seminar@xxxxxxxxxxx
Subject: [pl-seminar] Tomorrow's talk
 

Hi everyone,


Tomorrow noon at 4310 John will give a talk about Decomposition Instead of Self-Composition fo k-Safety.


Abstract:

We describe a novel technique for proving $k$-safety properties (non-interference, determinism, etc.) via a decomposition that enables one to leverage non-relational reasoning techniques. The key is the inter-operation of the following principles. First, we observe that many $k$-safety properties of interest have a particular structure that we call $\psi$\emph{-quotient partitionability} where $\psi$ is a $k$-ary formula. Second, we develop a partitioning strategy of execution traces based on the $k$-safety property $\Phi$ of interest such that if $\psi$ holds for $k$ traces then they must be in the same partition. Finally, within a partition component $T_i$, we observe that we can prove $k$-safety by instead proving a universal property: all traces within the partition satisfy some common property $P_i$, chosen to be strong enough that it implies the $k$-safety property $\Phi$ of any $k$-tuple of traces in components $T_i$.

We apply this strategy to the task of discovering timing side channels. A key feature of our approach is a demand-driven partitioning strategy that uses high/low-annotated regex-like \emph{trails} to reason about one partition component of execution traces at a time. We have applied our technique in a prototype implementation tool called {\sc Blazer}, based on WALA, PPL, Z3, and the brics automaton library. We have proved non-interference of (or synthesized an attack specification for) 25 programs written in Java bytecode, including 7 classic examples from the literature, and 6 examples extracted from the DARPA STAC challenge problems.

Best,
Qinheping Hu

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