Mayachitra, Inc.

Lakshmanan Nataraj

Bangalore S Manjunath

Shivkumar Chandrasekaran

Tajuddin Manhar Mohammed

Tejaswi Nanjundaswamy

Michael Gene Goebel

Methods, systems and computer programs are presented for classifying malware using audio and image signal processing. One method includes an operation for converting a software application to an audio signal and an image signal. Audio features are extracted from the audio signal and image features are extracted from the image signal and are used to classify the software application.

Malware classification and detection using audio and image descriptors

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.

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Chennai, India

Lakshmanan Nataraj