CRYPTO '99 Proceedings of the 19th Annual International Cryptology Conference on Advances in Cryptology
Timing Attacks on Implementations of Diffie-Hellman, RSA, DSS, and Other Systems
CRYPTO '96 Proceedings of the 16th Annual International Cryptology Conference on Advances in Cryptology
Differential Fault Analysis of Secret Key Cryptosystems
CRYPTO '97 Proceedings of the 17th Annual International Cryptology Conference on Advances in Cryptology
CHES '02 Revised Papers from the 4th International Workshop on Cryptographic Hardware and Embedded Systems
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Automatic code recognition for smart cards using a Kohonen neural network
CARDIS'02 Proceedings of the 5th conference on Smart Card Research and Advanced Application Conference - Volume 5
Markov Models for Pattern Recognition: From Theory to Applications
Markov Models for Pattern Recognition: From Theory to Applications
The Journal of Machine Learning Research
CHES '08 Proceeding sof the 10th international workshop on Cryptographic Hardware and Embedded Systems
How to Compare Profiled Side-Channel Attacks?
ACNS '09 Proceedings of the 7th International Conference on Applied Cryptography and Network Security
WISA'04 Proceedings of the 5th international conference on Information Security Applications
A stochastic model for differential side channel cryptanalysis
CHES'05 Proceedings of the 7th international conference on Cryptographic hardware and embedded systems
Efficient removal of random delays from embedded software implementations using hidden markov models
CARDIS'12 Proceedings of the 11th international conference on Smart Card Research and Advanced Applications
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For the last ten years, side channel research has focused on extracting data leakage with the goal of recovering secret keys of embedded cryptographic implementations. For about the same time it has been known that side channel leakage contains information about many other internal processes of a computing device. In this work we exploit side channel information to recover large parts of the program executed on an embedded processor. We present the first complete methodology to recover the program code of a microcontroller by evaluating its power consumption only. Besides well-studied methods from side channel analysis, we apply Hidden Markov Models to exploit prior knowledge about the program code. In addition to quantifying the potential of the created side channel based disassembler, we highlight its diverse and unique application scenarios.