Online Synthesis of Adaptive Side-Channel Attacks Based On Noisy Observations
Online Synthesis of Adaptive Side-Channel Attacks Based On Noisy Observations
复制标题
基于噪声观测的自适应侧信道攻击的在线合成
DOI:
10.1109/eurosp.2018.00029
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发表时间:
2018
期刊:
影响因子:
--
通讯作者:
T. Bultan
中科院分区:
文献类型:
--
作者:
Lucas Bang;Nicolás Rosner;T. Bultan
We present an automated technique for synthesizing adaptive attacks to extract information from program functions that leak secret data through a side channel. We synthesize attack steps dynamically and consider noisy program environments. Our approach consists of an offline profiling phase using symbolic execution, witness generation, and profiling to construct a noise model. During our online attack synthesis phase, we use weighted model counting and numeric optimization to automatically synthesize attack inputs. We experimentally evaluate the effectiveness of our approach on DARPA benchmark programs created for testing side-channel analysis techniques.
DOI:
10.1109/csf.2016.34
发表时间:
2016-08
期刊:
2016 IEEE 29th Computer Security Foundations Symposium (CSF)
影响因子:
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作者:
C. Păsăreanu;Quoc-Sang Phan;P. Malacaria
通讯作者:
C. Păsăreanu;Quoc-Sang Phan;P. Malacaria
DOI:
10.1145/1920261.1920300
发表时间:
2010-12
期刊:
--
影响因子:
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作者:
J. Heusser;P. Malacaria
通讯作者:
J. Heusser;P. Malacaria
DOI:
10.1145/2382756.2382791
发表时间:
2012
期刊:
ACM SIGSOFT Software Engineering Notes
影响因子:
--
作者:
Phan Q
通讯作者:
Phan Q