  Cosmic ray muon tomography is considered a promising method for the
non-invasive inspection of shipping containers and trucks. It utilizes highly
penetrating cosmic-ray muons and their interactions with various materials to
generate three-dimensional images of large and dense, like inter-modal shipping
containers, typically not transparent with conventional X-ray radiography
technique. The commonly used methods for imaging with muons are based on muon
scattering or absorption-transmission data analysis. Due to large thickness of
cargo material in shipping container substantial scattering and absorption
occur when muons passing through cargo.
  One of the key tasks of customs and border security is to verify shipping
container declarations to prevent illegal trafficking, and muon tomography
could be a viable choice for this task. In this paper, we demonstrate through
Monte Carlo simulations using the GEANT4 toolkit that a combined analysis of
muon scattering and absorption data can improve the identification of cargo
materials compared to using scattering or absorption data alone. The
statistical differences in scattering and absorption data for several cargo
materials are quantified. For a particular smuggling scenario where tobacco
declared as paper towel rolls, it is demonstrated that the combined analysis
can accurately distinguish between tobacco and paper towel rolls with
5.5$\sigma$ accuracy for detector spatial resolution (FWHM) of 0.235 mm,
4.5$\sigma$ for 1.175 mm resolution (FWHM), and 3.5$\sigma$ accuracy for 2.35
mm spatial resolution (FWHM), in a short scanning time of 10 seconds. This
rapid detection capability has significant implications for anti-smuggling
efforts and cargo inspection.
