  Bribery in election (or computational social choice in general) is an
important problem that has received a considerable amount of attention. In the
classic bribery problem, the briber (or attacker) bribes some voters in
attempting to make the briber's designated candidate win an election. In this
paper, we introduce a novel variant of the bribery problem, "Election with
Bribed Voter Uncertainty" or BVU for short, accommodating the uncertainty that
the vote of a bribed voter may or may not be counted. This uncertainty occurs
either because a bribed voter may not cast its vote in fear of being caught, or
because a bribed voter is indeed caught and therefore its vote is discarded. As
a first step towards ultimately understanding and addressing this important
problem, we show that it does not admit any multiplicative $O(1)$-approximation
algorithm modulo standard complexity assumptions. We further show that there is
an approximation algorithm that returns a solution with an additive-$\epsilon$
error in FPT time for any fixed $\epsilon$.
