A Deep-Learning Technique to Locate Cryptographic Operations in
  Side-Channel Traces
Giuseppe Chiari Davide Galli Francesco Lattari Matteo Matteucci Davide Zoni
Side-channel attacks allow extracting secret information from the execution
of cryptographic primitives by correlating the partially known computed data
and the measured side-channel signal. However, to set up a successful
side-channel attack, the attacker has to perform i) the challenging task of
locating the time instant in which the target cryptographic primitive is
executed inside a side-channel trace and then ii)the time-alignment of the
measured data on that time instant. This paper presents a novel deep-learning
technique to locate the time instant in which the target computed cryptographic
operations are executed in the side-channel trace. In contrast to
state-of-the-art solutions, the proposed methodology works even in the presence
of trace deformations obtained through random delay insertion techniques. We
validated our proposal through a successful attack against a variety of
unprotected and protected cryptographic primitives that have been executed on
an FPGA-implemented system-on-chip featuring a RISC-V CPU.