This is an implementation of python script to detect a series of forgeries that can happen in a document. Our basic module supports -signature fraud detection and analysis -copy and move forgery detection -identification document forgery detection -And normal document forgery detection and analysis.

1. We have tried impelementing a cloud based web application where user is asked to choose whether he wants to check signature forgery or document forgery.
2. Based on his choice he is asked to upload the scanned document. Our machine learning algorithms and neurals network based artificial intelligence detection technique.
3. The results generate a graph of the analysis and shows the areas where the forgery has been done. It shows a percentage accuracy of the report which is classified as follows 0% - 10% : Authenic 10% - 55% : Suspicious 55% - 60% : Foreged

-The source code of all the python files used for analysis. -The backend and frontend code of the web application -Several analysis results generated from the code with the disrepencies underlined. -Design of the web-app

1. Farid, H., 2009. Seeing is not believing. IEEE Spectrum, 46(8).
2. Farid, H., 2009. Image forgery detection. IEEE Signal processing magazine, 26(2), pp.16-25.
3. Johnson, M.K. and Farid, H., 2005, August. Exposing digital forgeries by detecting inconsistencies in lighting. In Proceedings of the 7th workshop on Multimedia and security (pp. 1-10). ACM.