In collisionless space and astrophysical plasmas dissipation of macroscopic energy into heat in the absence of collisions is a major unsolved problem. Most plausible mechanism for the dissipation in collisioneless plasma is the turbulent cascade of energy from macroscopic scales to kinetic scales where plasma processes can dissipates the energy. Space observations alongside with computer simulations show that kinetic scale current sheets self-consistently formed in the turbulent are the sites of the energy dissipation. Kinetic processes in current sheets such as magnetic reconnection, Fermi acceleration and Landau and cyclotron damping by waves considered to be the cause of energy dissipation are directly or indirectly influenced by plasma instabilities which depend on free energy sources, structures and physical parameters of current sheets. The the objective in this research work is identification and characterization of current sheets formed in collisionless plasma turbulence. We develop a computer program in python language implementing an algorithm for identification of current sheets in the turbulence. The algorithm was developed and used by [Zhdankin et al., The Astrophysical Journal, 771:124, 2013] to identify and characterize current sheets in Magnetohydrodynamic turbulence. We validate the newly developed python program against test data generated by mathematical formula. We then apply the program to the turbulence data generated by hybrid simulations of collsionless plasma turbulence to identify and characterize current sheets formed therein. The algorithm has three parameters to be chosen. The simulation data is chosen at times when current sheets have formed but not become unstable. We characterize current sheets by first choosing appropriate values of the three algorithm parameters, viz., a threshold to get rid of background fluctuations, size of the local region around current sheet peaks and value of current density at the current sheet boundary. Robustness of the results is checked against small variation of the algorithm parameters. Current sheets are characterized in terms of peak current density, half-thickness, length and aspect ratio. Results show that current sheet thins down to grid scale have tendency to become thinner if allowed by reducing the grid spacing in the simulations. Peak current density in current sheets enhances with thinning. Current sheets have lengths several tens times larger than their thicknesses and thus a large aspect ratio (length/thickness). Implication of the characterization results for plasma instabilities in current sheets are discussed. In the last part of this research work we have presented the results of identification and characterization of current sheets from statistical point of view and compared it with theoretical aspect of plasma instabilities and discussed about the probability occurrence of these instabilities.