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This thesis is dedicated to models and algorithms for the use in physical cryptanalysis which is a new evolving discipline in implementation security of information systems.
Physical observables such as the power consumption or electromagnetic emanation of a cryptographic module are so-called `side channels'. They contain exploitable information about internal states of an implementation at runtime. Physical effects can also be used for the injection of faults. Fault injection is successful if it recovers internal states by examining the effects of an erroneous state propagating through the computation.
The best currently known approach in physical cryptanalysis is a thorough experimental verification at a profiling stage, which is included in methods achieving maximum power. The final multivariate algorithms of this thesis can be seen as the most efficient ones in side channel cryptanalysis.
This paper presents implementation results of several side channel countermeasures for protecting the scalar multiplication of ECC (Elliptic Curve Cryptography) implemented on an ARM Cortex M3 processor that is used in security sensitive wireless sensor nodes. Our implementation was done for the ECC curves P-256, brainpool256r1, and Ed25519. Investigated countermeasures include Double-And-Add Always, Montgomery Ladder, Scalar Randomization, Randomized Scalar Splitting, Coordinate Randomization, and Randomized Sliding Window. Practical side channel tests for SEMA (Simple Electromagnetic Analysis) and MESD (Multiple Exponent, Single Data) are included. Though more advanced side channel attacks are not evaluated, yet, our results show that an appropriate level of resistance against the most relevant attacks can be reached.