Mayachitra, Inc.

Tajuddin Manhar Mohammed

Bangalore S Manjunath

Shivkumar Chandrasekaran

Tejaswi Nanjundaswamy

Michael Gene Goebel

Lakshmanan Nataraj

Systems and methods herein describe a malware visualization system that is configured to access a computer file, generate a first image of the computer file, determine a frequency count of bi-grams in the computer file, compute a discrete cosine transform (DCT) of the frequency count of bi-grams, generate a second image of the computer file based on the DCT of the frequency count of bi-grams, analyze the first image and the second image using an image classification neural network and generate a classification of the computer file.

Malware detection using frequency domain-based image visualization and deep learning

Systems, devices, methods and instructions are described for detecting GAN generated images. On embodiment involves receiving an images, generating co-occurrence matrices on color channels of the image, generating analysis of the image by using a convolutional neural network trained to analyze image features of the images based on the generated co-occurrence matrices and determining whether the image is a GAN generated image based on the analysis.

Detecting digital human face image manipulations

Detecting digital image manipulations

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Goleta, CA, United States of America

Tajuddin Manhar Mohammed