  According to the current standard model of Cosmology, matter in the Universe
arranges itself along a network of filamentary structure. These filaments
connect the main nodes of this so-called 'Cosmic Web', which are clusters of
galaxies. Although its large-scale distribution is clearly characterized by
numerical simulations, constraining the dark matter content of the cosmic web
in reality turns out to be difficult. The natural method of choice is
gravitational lensing. However, the direct detection and mapping of the elusive
filament signal is challenging and in this work we present two
methods,specifically tailored to achieve this task. A linear matched filter
aims at the detection of the smooth mass component of filaments and is
optimized to perform a shear decomposition that follows the anisotropic
component of the lensing signal. Filaments clearly inherit this property due to
their morphology. At the same time, the contamination arising from the central
massive cluster is controlled in a natural way. The filament 1 {\sigma}
detection is of about {\kappa} ~ 0.01-0.005 according to the filter's template
width and length, enabling the detection of structures out of reach with other
approaches. The second, complementary method seeks to detect the clumpy
component of filaments. The detection is determined by the number density of
sub-clump identifications in an area enclosing the potential filament, as it
was found within the observed field with the filter approach. We test both
methods against Mock observations based on realistic N-Body simulations of
filamentary structure and prove the feasibility of detecting filaments with
ground-based data.
