NDSS 2020 Data-Driven Debugging for Functional Side Channels
SESSION 5B-3 Data-Driven Debugging for Functional Side Channels
Information leaks through side channels are a pervasive problem, even in security-critical applications. Functional side channels arise when an attacker knows that a secret value of a server stays fixed for a certain time. Then, the attacker can observe the server executions on a sequence of different public inputs, each paired with the same secret input. Thus for each secret, the attacker observes a (partial) function from public inputs to execution time, for instance, and she can compare these functions for different secrets.
First, we introduce a notion of noninterference for functional side channels. We focus on the case of noisy observations, where we demonstrate with examples that there is a practical functional side channel in programs that would be deemed information-leak-free or be underestimated using the standard definition. Second, we develop a framework and techniques for debugging programs for functional side channels. We extend evolutionary fuzzing techniques to generate inputs that exploit functional dependencies of response times on public inputs. We adapt existing results and algorithms in functional data analysis (such as functional clustering) to model the functions and discover the existence of side channels. We use a functional extension of standard decision tree learning to pinpoint the code fragments causing a side channel if there is one.
We empirically evaluate the performance of our tool FUCHSIA on a series of micro-benchmarks, as well as on realistic Java programs. On the set of micro-benchmark, we show that FUCHSIA outperforms the state-of-the-art techniques in detecting side channel classes. On the realistic programs, we show the scalability of FUCHSIA in analyzing functional side channels in Java programs with thousands of methods. In addition, we show the usefulness of FUCHSIA in finding (and locating in code) side channels including a zero-day vulnerability in Open Java Development Kit and another Java web server vulnerability that was since fixed by the original developers.
PAPER
https://www.ndss-symposium.org/wp-con...
SLIDES
AUTHORS
Saeid Tizpaz-Niari (University of Colorado Boulder)
Pavol Černý (TU Wien)
Ashutosh Trivedi (University of Colorado Boulder)
Network and Distributed System Security (NDSS) Symposium 2020, 23-26 February 2019, Catamaran Resort Hotel & Spa in San Diego, California.
https://www.ndss-symposium.org/ndss-p...
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The Network and Distributed System Security Symposium (NDSS) fosters information exchange among researchers and practitioners of network and distributed system security. The target audience includes those interested in practical aspects of network and distributed system security, with a focus on actual system design and implementation. A major goal is to encourage and enable the Internet community to apply, deploy, and advance the state of available security technologies.
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