  Insider information and model uncertainty are two unavoidable problems for
the portfolio selection theory in reality. This paper studies the robust
optimal portfolio strategy for an investor who owns general insider information
under model uncertainty. On the aspect of the mathematical theory, we improve
some properties of the forward integral and use Malliavin calculus to derive
the anticipating It\^{o} formula . Then we use forward integrals to formulate
the insider-trading problem with model uncertainty. We give the half
characterization of the robust optimal portfolio and obtain the semimartingale
decomposition of the driving noise $W$ with respect to the insider information
filtration, which turns the problem turns to the nonanticipative stochastic
differential game problem. We give the total characterization by the stochastic
maximum principle. When considering two typical situations where the insider is
`small' and `large', we give the corresponding BSDEs to characterize the robust
optimal portfolio strategy, and derive the closed form of the portfolio and the
value function in the case of the small insider by the Donsker $\delta$
functional. We present the simulation result and give the economic analysis of
optimal strategies under different situations.
